Information processing device, information processing method, and program

Abstract

The present technology pertains to an information processing device, an information processing method, and a program that make it easy to accept even uninterested information during a selection operation. In the present technology: a commodity recommended to a user is compared with commodity information related to a commodity in which the user is interested, presentation information including an information category of information in which the recommended commodity is dominant is generated and presented to the user, thereby causing interest in a recommended commodity in which the user is not interested initially; and the recommended information is presented once the acceptability of the recommended information by the user becomes high enough.

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and a program, and more particularly to an information processing apparatus, an information processing method, and a program that make it easier to accept even uninteresting information during a selection operation. Background Art

[0002] In a product selection scenario, it may not be a search for a product with a clear purpose, and decisions are often made without much deliberation.

[0003] Incidentally, in information retrieval without a clear purpose, that is, "non-purpose information retrieval", the following technique has been proposed (see Non-Patent Document 1). By presentation control based on classification of information, the stimulation level of the information to be browsed is quantified so that it falls within an appropriate range, thereby performing internal drive, preventing loss of interest, and maintaining information retrieval.

[0004] Therefore, by applying the technique of Non-Patent Document 1 in a product selection scenario, it is conceivable to maintain information search about products and lead to the purchase of a specific product.

[0005] Citation List

[0006] Non-Patent Document

[0007] Non-Patent Document 1: Psycho-Physiological Approach to Non-Purpose Information Search - Information Design Based on the Optimal Stimulation Level Theory - Miwa Nakanishi, Motoya Takahashi (Journal of the Human Interface Society / Vol. 21 (2019) No. 3) Summary of the Invention

[0008] Problems to be Solved by the Invention

[0009] However, even when information is presented, if the information is uninteresting to the user, the user may unconsciously filter the presented information, or may not have the motivation to actively obtain the information, and may not accept the presented information.

[0010] In addition, even if the presented information is information of some interest, in the case of a cognitive / understanding load, such as a large amount of information, the user may also filter the presented information or not accept the information in a similar manner as above.

[0011] The present disclosure has been made in view of such circumstances. In particular, at the time of a selection operation, the presented information is designed so that even uninteresting information can be easily accepted.

[0012] Solutions to the Problems

[0013] An information processing apparatus or program according to the present technology is the following information processing apparatus or a program for causing a computer to function as such an information processing apparatus. The information processing apparatus includes: an interest degree estimation unit that estimates an index of the intensity of a user's interest in a predetermined object as the interest degree; a presentation processing unit that generates presentation information for comparing interest object information, which is information related to an interest object, with recommendation object information, which is information related to a recommendation object to be recommended to the user, and presents the presentation information to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree; and an acceptance degree calculation unit that calculates an acceptance degree, which is an index of the ease of acceptance of the recommendation object information by the user, based on the user's interest degree in the presentation information, wherein the presentation processing unit presents the recommendation object information when the acceptance degree of the recommendation object information by the user is higher than a predetermined value.

[0014] An information processing method according to the present technology is an information processing method including the following steps: estimating an index of the intensity of a user's interest in a predetermined object as the interest degree; generating presentation information for comparing interest object information, which is information related to an interest object, with recommendation object information, which is information related to a recommendation object to be recommended to the user, and presenting the presentation information to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree; and calculating an acceptance degree, which is an index of the ease of acceptance of the recommendation object information by the user, based on the user's interest degree in the presentation information, wherein the recommendation object information is presented when the acceptance degree of the recommendation object information by the user is higher than a predetermined value.

[0015] In one aspect of the present technology, an index of the intensity of a user's interest in a predetermined object is estimated as the interest degree, presentation information for comparing interest object information, which is information related to an interest object, with recommendation object information, which is information related to a recommendation object to be recommended to the user, is generated and presented to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree, an acceptance degree, which is an index of the ease of acceptance of the recommendation object information by the user, is calculated based on the user's interest degree in the presentation information, and the recommendation object information is presented when the acceptance degree of the recommendation object information by the user is higher than a predetermined value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a diagram illustrating an overview of the present disclosure.

[0017] Figure 2 is a diagram illustrating an overview of the present disclosure.

[0018] Figure 3 is a diagram illustrating the external configuration of an information processing system according to a preferred embodiment of the present disclosure.

[0019] Figure 4 shows Figure 3Diagram of the configuration example of an information processing system.

[0020] Figure 5 Diagram explaining acceptance and acceptance difficulty.

[0021] Figure 6 Diagram explaining interest level.

[0022] Figure 7 Diagram explaining the calculation method of acceptance.

[0023] Figure 8 Diagram showing a specific calculation example of acceptance.

[0024] Figure 9 Diagram explaining the calculation method of acceptance difficulty.

[0025] Figure 10 Diagram showing a specific calculation example of acceptance difficulty.

[0026] Figure 11 Diagram explaining the process of guided presentation for improving the acceptance of recommended object information.

[0027] Figure 12 Diagram showing an example of a predetermined range in the line-of-sight direction recognized by an eye tracker.

[0028] Figure 13 Diagram explaining Figure 12 Specific examples of the acceptance difficulty of each product and each information category within the predetermined range in the recognized line-of-sight direction shown in

[0029] Figure 14 Diagram explaining Figure 12 Specific examples of the acceptance of each product and each information category within the predetermined range in the recognized line-of-sight direction shown in

[0030] Figure 15 Diagram explaining based on Figure 13 The acceptance difficulty of Figure 14 And the acceptable and unacceptable information based on the acceptance of

[0031] Figure 16 Diagram showing an example of the presentation of presentation information including product summaries.

[0032] Figure 17 Diagram showing specific examples of acceptance after presenting presentation information including Figure 16 The product summary of

[0033] Figure 18 Diagram showing an example of the presentation of presentation information including product details.

[0034] Figure 19 It is a figure showing a specific example of acceptance after presenting presentation information including Figure 18 the product details.

[0035] Figure 20 It is a figure showing a presentation example of presentation information of an information category with the amount of dietary fiber added.

[0036] Figure 21 It is a figure showing a specific example of acceptance after presenting the presentation information in Figure 20 .

[0037] Figure 22 It is a figure showing an information category in which information including advantages is included in the recommended object information in the acceptance table of Figure 21 .

[0038] Figure 23 It is a figure showing a presentation example of presentation information generated based on an information category in which information including advantages is included in the recommended object information in the acceptance table of Figure 21 .

[0039] Figure 24 It is a figure showing a specific example of acceptance after presenting the presentation information in Figure 23 .

[0040] Figure 25 It is a figure showing an information category when presenting information in which the recommended object information is dominant compared with other products in the acceptance table of Figure 24 .

[0041] Figure 26 It is a figure showing a presentation example of presentation information when presenting information in which the recommended object information is dominant compared with other products.

[0042] Figure 27 It is a figure showing a flowchart of the presentation process guided by the recommended object information.

[0043] Figure 28 It is a figure showing a flowchart of the guided presentation process.

[0044] Figure 29 It is a figure showing a flowchart of the presentation process of the recommended object information.

[0045] Figure 30 It is a figure showing a configuration example of a general personal computer. Detailed implementation manners

[0046] Hereinafter, embodiments of the present technology will be described with reference to the accompanying drawings.

[0047] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Note that in this specification and the accompanying drawings, configuration elements having substantially the same functional configuration are denoted by the same reference numerals, and redundant descriptions are omitted.

[0048] Hereinafter, modes for implementing the present technology will be described. The description will be given in the following order.

[0049] 1. Overview of the present disclosure

[0050] 2. Preferred embodiments

[0051] 3. Application examples

[0052] 4. Examples implemented by software

[0053] <<1. Overview of the present disclosure>>

[0054] In the present disclosure, when a selection action is performed, the information to be presented is designed so that even information that is not of interest can be easily accepted. Therefore, first, an overview of the present disclosure will be described.

[0055] Note that making even information that is not of interest easily accepted here means making even information that is not of interest easily received. More specifically, making even information that is not of interest easily accepted means making even information that is not of interest become interesting, making the information be actively understood, making the information remain in memory, etc.

[0056] In addition, here as an example of a selection action, the case where a user selects a product to purchase from various types of products in a store or the like is taken as an example.

[0057] In addition, the following example is described: When products recommended for sale among the products sold in a store or the like are preset and the products recommended for sale are products that the user is not interested in, even if product information of products that the user is not interested in and that are recommended for sale is presented, the product information is easily accepted.

[0058] Hereinafter, the product recommended for sale will be referred to as the product to be recommended or the recommended product, and the product information of the product recommended for sale will be referred to as the recommended information.

[0059] As Figure 1 shown in the upper part of, consider the following situation: Products A to E are displayed on a product shelf or the like. Among products A to E, the object of interest of user H who is a visitor to the store is product A, and the recommended product is product E.

[0060] That is to say, here, the ultimate goal is to make it easy for user H to accept the product information (recommended object information) of product E as the recommended object, and to promote the sales of product E by presenting the product information of product E.

[0061] However, as Figure 1 shown in the left part of the upper side of, the object of interest to user H is product A, rather than product E which is the recommended object.

[0062] Therefore, the recommended object information, which is the product information related to the product E to be recommended, is naturally information that user H is not interested in.

[0063] Therefore, as Figure 1 shown in the upper right part of, in this state, even if the recommended object information D1 related to the product E to be recommended is presented to user H, since the recommended object information D1 is information that the user is not interested in, it is considered that the recommended object information D1 is difficult to be accepted and is not accepted.

[0064] Generally, humans do not know the information they are not interested in, but have the characteristic of obediently listening to or trying to obtain information related to the objects they are strongly interested in.

[0065] Therefore, in the present disclosure, by utilizing human characteristics, before presenting the uninteresting recommended object information, information for comparing the product information of the interesting product that is easy to accept with the product information of the uninteresting product that is difficult to accept is presented, so as to guide the interest in the uninteresting product, and the recommended object information is presented after making the recommended object information easy to accept.

[0066] That is to say, as Figure 1 shown in the lower part of, the product information D11 of the interesting product A is presented. At this time, since this information is the product information D11 of the product A which is the object of interest, it can be considered that user H can easily accept this information.

[0067] Next, relay information D12 for comparing the product information of the product A which is the object of interest with the product information of the product E which is the uninteresting recommended object is presented.

[0068] In the case of presenting the relay information D12, since the product information of the interesting product A is information that is easy to accept, by presenting the product information of the recommended object product E by comparing it with the product information of product A, the recommended object information can also be easily accepted.

[0069] Then, by presenting the relay information D12, after the recommended object information, that is, the product information of the product E as the recommended object, becomes easy to accept for user H, the recommended object information D1 is presented.

[0070] After presenting the product information D11 of interest in this way, relay information D12 is presented, so that after creating a ready state for easily accepting the recommended object information D1 that the user is not yet interested in, the recommended object information D1 is presented. Note that the relay information D12 is not limited to presenting one message, and multiple messages can also be presented.

[0071] More specifically, as Figure 2 indicated by the first stage St1 in the lower part of

[0072] In the first stage St1, when it is detected that the user H shows an interest level greater than or equal to a predetermined value with respect to the product that is the object of the user H's interest, but the user H is not strongly interested, that is, the user H has a weak interest, the process proceeds to the second stage St2. This corresponds to Figure 2 "Weak interest in the product detected" in the lower left part of

[0073] Then, in the second stage St2, a guiding presentation D21 for guiding the user to have a strong interest in the product that is the object of interest is presented. Through the guiding presentation D21, the user H is guided to a state where the user H has a strong interest in the product that is the object of the user H's interest.

[0074] Note that if, through the processing of the first stage St1, the user H is in a state of being strongly interested in the product that is the object of the user H's interest, the processing of the second stage St2 is omitted. The state where the processing of the second stage St2 is omitted corresponds to Figure 2 "Strong interest in the product detected" in the lower left part of

[0075] In the third stage St3, a guiding presentation D22 is presented, which is used to guide to a ready state for accepting the recommended object information, including comparison information such as the product to be recommended has an advantage over the strongly interested product.

[0076] In Figure 2 it is assumed that the user H is guided to a ready state for accepting the recommended object information through the processing of the third stage St3.

[0077] In other words, the products to be recommended are initially products that user H is not interested in. However, through the processing from the first stage St1 to the third stage St3, by presenting the guiding presentation D22 including comparison information with the products the user is interested in, the products to be recommended become objects of interest, and the recommended object information D23 is guided to the preparatory information that can be accepted. Thus, in the fourth stage St4, the recommended object information D23 is presented to user H in an easily acceptable state.

[0078] Note that Figure 2 the guiding presentations D21, S22 correspond to Figure 1 the product information D11, relay information D12, Figure 2 the recommended object information D23 corresponds to Figure 1 the recommended object information D1.

[0079] However, since the above processing is to guide the interest of user H, the guidance may not succeed, and the user may not be guided to a state of having a strong interest in the recommended object. In such a case where the guidance fails, it is necessary to increase or change the presentation content of the guiding presentation D22.

[0080] For example, in the case where there are multiple pieces of comparison information indicating that the products to be recommended have advantages over the products that are objects of strong interest, the guiding presentation D22 can repeatedly present the advantageous comparison information while switching the advantageous comparison information until the recommended object information becomes acceptable, thereby guiding the recommended object information to the preparatory state of acceptable recommended object information.

[0081] Through such processing, after guiding the recommended object information of the originally uninterested recommended object to a gradually acceptable state and then presenting the recommended object information, it is possible to easily accept the recommended object information.

[0082] <<2. Preferred Embodiment>>

[0083] Next, a configuration example of a preferred embodiment of the information processing system applying the present disclosure will be described with reference to Figure 3 FIG.

[0084] Figure 3 FIG. shows an external configuration example of the information processing system 11. The information processing system 11 is installed in a store or the like that sells products. The information processing system 11 detects the degree of interest of user 21 in products A to J arranged on the product shelf 35 as the interest degree based on the gazing direction and gazing time of user 21 who is a visitor to the store, whether there is contact, the distance to the products, the distance and time to the products, the reaction to the presented information, etc.

[0085] Then, the information processing system 11 generates and presents presentation information obtained by comparing the product information of products with an interest level greater than a predetermined interest level with the recommendation target information of the recommendation target products that the user was initially not interested in, and presents the recommendation target information after guiding the user 21 to a state where it is easy to accept the recommendation target information, thereby facilitating acceptance.

[0086] More specifically, Figure 3 the information processing system 11 in < > includes an information processing device 31, a depth sensor 32, an eye tracker 33, a display 34, and a product shelf 35.

[0087] The information processing device 31 includes a personal computer or the like, and obtains the individual interest level of the user 21 in the product based on the distance image of the user 21 or the product captured by the depth sensor 32 or the information on the line-of-sight direction of the user 21 detected by the eye tracker 33, and determines the product of interest, that is, the product that becomes the object of interest.

[0088] The information processing device 31 uses the product information of the product of interest and the product information of the recommendation target product to generate a guiding presentation for comparing the two, and presents the guiding presentation on the display 34, thereby guiding the user to be interested in the recommendation target product, guiding the user 21 to a state where it is easy to accept the recommendation target information, and then presenting the recommendation target information.

[0089] The depth sensor 32 is provided in the store, generates a distance image of the user 21 in the store or the product displayed on the product shelf 35, and outputs the distance image to the information processing device 31.

[0090] The eye tracker 33 is provided near the display 34 or the like, detects the position of the pupil of the user 21, determines the line-of-sight direction, and outputs the line-of-sight direction to the information processing device 31.

[0091] The display 34 presents the guiding presentation and the recommendation target information generated by the information processing device 31 based on the product information of the product as the object of interest or the product information of the product as the recommendation target, in order to guide the user 21 to a state where the recommendation target information can be accepted.

[0092] In addition, the display 34 includes a touch panel, presents an inquiry from the information processing device 31 to the user 21 as needed, receives an operation input as a response to the inquiry, and outputs an operation signal corresponding to the received operation input to the information processing device 31.

[0093] <Configuration Example of Information Processing Device>

[0094] Next, refer to Figure 4 for Figure 2A configuration example of the information processing device 31 in the information processing system 11 will be described.

[0095] The information processing device 31 is a terminal device including a computer or the like, and includes a control unit 51, an input unit 52, an output unit 53, a storage unit 54, a communication unit 55, a driver 56, and a removable storage medium 57, which are interconnected via a bus 58 and capable of sending and receiving data and programs.

[0096] In addition, a depth sensor 32, an eye tracker 33, and a display 34 are connected via the bus 58 via an interface (not shown).

[0097] The control unit 51 includes a processor and a memory, and controls the overall operation of the information processing device 31. In addition, the control unit 51 includes an object detection unit 71, an interest estimation unit 72, a presentation processing unit 73, an acceptance estimation unit 74, an acceptance difficulty estimation unit 75, and an acceptability determination unit 76.

[0098] The object detection unit 71 detects the presence or absence of an object visitor to the store near the merchandise shelf 35 based on the distance image provided by the depth sensor 32.

[0099] The interest estimation unit 72 estimates the interest of the user 21 in the merchandise or presentation based on the distance images provided by the depth sensor 32 to the user 21 as a visitor to the store and each merchandise displayed on the merchandise shelf 35, and the information on the line-of-sight direction of the user 21 provided by the eye tracker 33. Note that details of the estimation of the interest will be described later.

[0100] The presentation processing unit 73 generates presentation information to be presented to the user 21 and presents the presentation information on the display 34. The presentation information includes the above-described guidance presentation, summary information, detailed information, and recommended object information of the merchandise that is the object of interest of the user 21.

[0101] Based on the acceptance degree, which is an index of the ease of acceptance of the presentation information estimated according to the behavior of the user 21, and the acceptance difficulty, which is an index indicating the acceptance difficulty of the user 21 for each piece of presentation information, the presentation processing unit 73 generates presentation information for guiding the user 21 to a ready state where the user 21 can accept the recommended object information and presents it on the display 34.

[0102] Here, the acceptance degree is set by the user 21, and is set according to the interest degree of the user 21 in the merchandise and the interest degree in each information category of the merchandise, and is an index indicating the ease of acceptance of the presentation information by the user 21.

[0103] In addition, the acceptance difficulty is set for each piece of information and is an index of the acceptance difficulty preset according to the amount of information and the expected demand value of each information category. More specifically, while presenting specific information while changing the amount of information (number of characters), after preliminarily confirming how the acceptance changes according to the amount of information, the acceptance difficulty is set. That is, when the amount of information is less than the predetermined amount and the presentation is simple, the number of characters presented is small, so the reading burden on the user is reduced and the presentation becomes easy, so the acceptance difficulty is set to a low value. On the other hand, when the amount of information exceeds the predetermined amount, the number of characters to be presented increases, the reading burden on the user increases, and it is difficult to accept the information, so the acceptance difficulty is set to a high value.

[0104] Note that the information category is, for example, a type or classification of information such as a product name, a packaging image, a taste description, calories, and salt content. In addition, the amount of information presented is the number of strings, characters, etc. related to the information to be presented. In addition, the expected demand value for each information category is an expected value indicating how much demand is usually set for each information category. More specifically, for example, regarding the expected demand value, it is also possible to collect the degree of interest in each information category for a product with a specific degree of interest through a questionnaire or the like, and use the average value of the collected degrees of interest as the initial value of the expected demand value of the information category. Then, in actual operation, it is also possible to record whether the presentation is actually accepted, that is, the change in the degree of interest, and based on the recorded results, increase the expected demand value according to the actual operation.

[0105] In addition, although the acceptance degree is a variable value because it is based on the degree of interest that changes when the user 21 accepts the presented information, the acceptance difficulty is a fixed value preset in the presented information.

[0106] Therefore, when the degree of interest in the product to be recommended changes with respect to the predetermined presented information, for example, when a relationship is established in which the acceptance degree is greater than the set acceptance difficulty by a predetermined ratio, it can be determined that the user 21 is ready to accept the predetermined presented information. Note that the acceptance degree and the acceptance difficulty will be described in detail later.

[0107] The acceptance degree estimation unit 74 estimates the acceptance degree, which is an index indicating the ease of acceptance of the presented information set according to the degree of interest of the user 21 in the product estimated by the degree of interest estimation unit 72 and the degree of interest of the user 21 in the information category of the product.

[0108] The acceptance difficulty estimation unit 75 estimates the acceptance difficulty, which is an index of the acceptance difficulty of the presented information and is preset according to the amount of information of the presented information and the acceptance expectation value of each information category. Since the acceptance difficulty is a value preset according to the amount of information of the presented information and the demand expectation value of each information category, the acceptance difficulty estimation unit 75 can estimate the acceptance difficulty in advance and store the estimated difficulty in the storage unit 54 as a table.

[0109] The acceptability determination unit 76 determines whether the user 21 can accept the presented information when presenting the presented information on the display 34 for each presented information based on the acceptance degree and the acceptance difficulty.

[0110] The input unit 52 includes input devices such as a keyboard, a mouse, and a touch panel to which the user inputs, and provides various input signals corresponding to the input operations to the control unit 51.

[0111] The output unit 53 is controlled by the control unit 51, includes a display unit and a sound output unit (both not shown), and displays various processing results as images or outputs various processing results as sounds.

[0112] The storage unit 54 includes a hard disk drive (HDD), a solid state drive (SSD), a semiconductor memory, etc., is controlled by the control unit 51, and performs writing or reading of various data and programs. The storage unit 54 includes a product information storage unit 91, which is read when generating the presented information. The product information storage unit 91 stores, for example, the product name of each product displayed on the product shelf 35, summary information such as a package image, and detailed information such as ingredient information.

[0113] The communication unit 55 is controlled by the control unit 51 to implement communication represented by a local area network (LAN), Bluetooth (registered trademark), etc. in a wired or wireless manner, and sends various data and programs to other information processing devices, etc. or receives various data and programs from other information processing devices, etc. via a network (not shown) as needed.

[0114] The drive 56 reads data from and writes data to a removable storage medium 57 such as a magnetic disk (including a floppy disk), an optical disk (including a compact disc read-only memory (CD-ROM) and a digital versatile disc (DVD)), a magneto-optical disk (including a mini disc (MD)), or a semiconductor memory.

[0115] <Acceptance Degree and Acceptance Difficulty>

[0116] Next, refer to Figure 5 A description will be given of the acceptance degree and the acceptance difficulty.

[0117] As described above, the acceptance is an index indicating the ease of acceptance of the presented information to the user, which is set according to the degree of interest of User 21 in the product and the degree of interest of User 21 in the information category of the product.

[0118] In addition, the acceptance difficulty is an index of the acceptance difficulty of the information, which is preset according to the amount of information presented and the acceptance expectation value of each information category.

[0119] Figure 5 The relationship between the acceptance of the predetermined information and the acceptance difficulty is shown. The upper part represents the acceptance difficulty of the predetermined information, and the lower part represents the acceptance of the user with respect to the predetermined information.

[0120] Both the acceptance, which is an index of the ease of acceptance set for the user, and the acceptance difficulty, which is an index of the acceptance difficulty set for the user in the information, are represented by continuous values from 0 to 1. Note that in this specification, both the acceptance and the acceptance difficulty are continuous values from 0 to 1, but they can also be discrete values at predetermined intervals.

[0121] Here, the fact that the acceptance is 0 indicates that the user's acceptance is the lowest, and the user is in the state of being most difficult to accept information. In addition, the fact that the acceptance is 1 indicates that the user's acceptance is the highest, and the information is most easily accepted.

[0122] In addition, the fact that the acceptance difficulty is 0 indicates that the acceptance difficulty for the user is the lowest, and the information is most easily accepted by the user. In addition, the fact that the acceptance difficulty is 1 indicates that the acceptance difficulty for the user is the highest, and the information is most difficult to be accepted by the user.

[0123] Therefore, the higher the user's acceptance of the information, the easier it is for the user to accept information with a low acceptance difficulty to information with a high acceptance difficulty. On the contrary, the lower the user's acceptance of the information, the more difficult it is for the user to accept the information, unless the acceptance difficulty of the information is low.

[0124] Based on such a relationship, it can be considered that there is a qualitative correlation between the acceptance and the acceptance difficulty in terms of the magnitude relationship. Therefore, in the following description, it is assumed that the relationship between the values of the acceptance and the acceptance difficulty corresponds quantitatively to each other.

[0125] That is, for example, if the user's acceptance is 1, it is assumed that the user can accept information with an acceptance difficulty from 0 to 1. In addition, if the user's acceptance is 0.5, it is assumed that the user can accept information with an acceptance difficulty from 0 to 0.5. Additionally, if the user's acceptance is 0, it is assumed that the user cannot even accept information with the lowest acceptance difficulty of 0.

[0126] Note that since acceptance and acceptance difficulty are not the same metric, it is considered difficult to strictly compare their magnitudes numerically. That is, based on the above assumptions, if the user's acceptance is 1.0, then all information with an acceptance difficulty from 0 to 1.0 can be accepted. However, in reality, since the two are not the same metric, information with an acceptance difficulty of 1.0 can also be accepted, even if the user's acceptance is 0.8, while information with an acceptance difficulty of 0.9 cannot be accepted, even if the user's acceptance is 1.0.

[0127] Therefore, the comparison of the actual magnitudes between the two is qualitative, and in order to quantitatively handle the magnitude relationship, it is considered necessary to adjust the magnitude relationship using at least a correction factor, etc. However, here for the sake of simplicity of explanation, it is assumed that the correlation of the magnitude relationship between acceptance and acceptance difficulty exactly corresponds to the numerical value for description.

[0128] Based on the above assumptions, as Figure 5 shown, for example, information with an acceptance difficulty greater than or equal to 0 and less than 0.3 is defined as information with low acceptance difficulty, information with an acceptance difficulty greater than or equal to 0.3 and less than 0.6 is defined as information with medium acceptance difficulty, and information with an acceptance difficulty greater than or equal to 0.6 and less than or equal to 1.0 is defined as information with high acceptance difficulty.

[0129] At this time, the user changes the acceptable information according to the acceptance. For example, if the acceptance is 0.3, the user can only accept information with low acceptance difficulty. However, when the user's acceptance is increased to 0.6 by presenting some information, not only information with low acceptance difficulty can be accepted, but also information with medium acceptance difficulty can be accepted. In addition, when the user's acceptance is increased to 1.0, all information from low acceptance difficulty to high acceptance difficulty can be accepted.

[0130] In the present disclosure, the user's acceptance is increased by gradually guiding the presentation, and the recommended object information is presented after the acceptance becomes greater than the acceptance difficulty set in the recommended object information that the user was originally not interested in, so that the user can easily accept the recommended object information.

[0131] <Interest Degree>

[0132] Next, the interest degree required for calculating the acceptance will be described.

[0133] The interest degree is an index indicating the intensity of the user's interest in the goods or information categories that are the objects of interest. That is, the interest degree includes the goods interest degree as the interest degree in the goods that are the objects of interest, and the information category interest degree as the interest degree in the information categories.

[0134] The object of interest is the object being gazed at, grasped, or the object of the user's touch operation on the presented information. When the object being gazed at cannot be uniquely determined based on the detection results such as the user's line-of-sight information and facial orientation, scores can be calculated for a group of objects to select the highest score. In addition, when the group of objects is narrowed down to a certain number, the object group can also be selected through user input such as a touch operation.

[0135] As Figure 6 shown, the degree of interest in the object of interest can be obtained by setting scores for each of the three types of object gazing, object contact, and presentation response, weighting them considering the action sequence, and adding the scores. The weights can also be changed according to the configuration of the merchandise shelf 35, etc. Hereinafter, the scores for object gazing, object contact, and presentation response are also referred to as the object gazing score, the object contact score, and the presentation response score, respectively.

[0136] More specifically, the object being gazed at is determined by the line-of-sight direction, facial direction, etc., and the object gazing score is calculated based on the gazing time and the shift of the line of sight. For example, the object gazing score can be set to be higher for a gaze from a short distance than for a gaze from a long distance, or can be set to be higher for a longer gazing time.

[0137] In addition, the object in contact is determined by touching with the hand, grasping (luggage), etc., and the object contact score is set to a score higher than that of gazing. In addition, the object contact score can be set to be higher in the case of grasping than in the case of touching.

[0138] In addition, the presentation response score can be set such that the object of the presentation response is determined by gazing at, touching, etc. the presented information, and the score becomes higher when the gazing time of the presented content is longer than a predetermined time or when a touch operation is performed.

[0139] As described above, since the degree of interest is a value set based on the three scores of object gazing, object contact, and presentation response, when the degree of interest is greater than a predetermined value, it can be determined that the user is interested in the object commodity.

[0140] However, when an action with an extremely large score added is observed for at least one of the three types of object gazing, object contact, and presentation response, even if the degree of interest calculated based on the scores of these three types does not exceed the predetermined value, it can be considered that the user has a particularly strong interest.

[0141] When the degree of interest is higher than the predetermined threshold and the gazing time is longer than the predetermined time, for example, when the user gazes at the commodity while approaching the commodity, when the user grasps the commodity without touching it, etc., it can be considered that the user has a strong interest in the object.

[0142] In a guided presentation, if it is possible to pre-consider that the user has a strong interest in an object, it can be considered that the possibility of accepting detailed information about the object commodity is high.

[0143] Therefore, for an object with an interest level higher than a predetermined value, especially an object with a high level of interest, a guided presentation can be made on the premise of accepting detailed information.

[0144] In addition, an object with an interest level higher than the predetermined value but without a strong interest can be regarded as having a weak interest.

[0145] In the case of weak interest, it is necessary to start the guided presentation from presenting summary information to lead to a state where detailed information can be accepted.

[0146] Regarding the presentation of summary information about an object with weak interest, for example, in the case where the fixation time is longer than a predetermined time and the body orientation is directly facing the presented information not only in the facial orientation, it can be considered that the interest in the object commodity changes from weak interest to strong interest.

[0147] Note that, as Figure 6 shown, the interest level calculated based on the object fixation score and the object contact score can be obtained as the true interest level, that is, the interest level of the true object. In addition, the interest level calculated based on the presentation response score as a response to non-true presented information can be obtained as the presentation interest level. That is, the sum of the true interest level and the presentation interest level is expressed as the interest level (commodity interest level and information category interest level).

[0148] In this case, since the true interest level is the interest in the true target and it can be considered that the interest in commodities, etc. is higher than the interest in the presented information, the weight can be made greater than the presentation interest level.

[0149] In addition, after presenting the summary information about an object with weak interest, when the presentation interest level becomes higher than the predetermined value, it can be considered that the user's interest has changed from weak to strong.

[0150] Note that the above strong interest and weak interest are only examples using the interest level, but other information can also be used for setting.

[0151] For example, according to the relationship between the acceptance level and the acceptance difficulty described later, it can also be configured such that, among multiple information categories set for an object commodity, etc., for a commodity, etc. that can accept more than a predetermined number of information in an information category with a higher acceptance difficulty than the predetermined acceptance difficulty, it has a strong interest, and for a commodity, etc. with less than the predetermined number, it has a weak interest.

[0152] <Specific calculation method of acceptance level>

[0153] Next, referring toFigure 7 and Figure 8 Describe specific calculation examples of acceptance.

[0154] As described above, acceptance is calculated based on product interest and information category interest. For example, in the case where there are products A, B, and C and information categories α, β, and γ, as Figure 7 shown, product interest, information category interest, and acceptance are defined. Note that in the attached drawings, information categories α, β, and γ are abbreviated as information α, information β, and information γ respectively, and the same applies to the following descriptions.

[0155] At Figure 7 the upper left part, the product interests I prod (U, p) of products A, B, and C are defined in sequence from the left as product interests I prod (U, A), I prod (U, B), and I prod (U, C). Here, U is an identifier used to identify the behavior that the user is interested in, such as identifying approaching, gazing, touching, grasping, etc. of the target product. In addition, p is an identifier used to identify the product, which is each of products A, B, and C.

[0156] At Figure 7 the lower left part, the information category interests I cat (U, c) of information categories α, β, and γ are defined in sequence from the left as information category interests I cat (U, α), I cat (U, β), and I cat (U, γ). Here, c is an identifier used to identify the information category, which is each of information categories α, β, and γ.

[0157] At Figure 7 the right part, the acceptance R(U, I prod , I cat ) of each information category of each product is defined. More specifically, the acceptance of each information category in information categories α, β, and γ of product A is defined as R(U, I prod (U, A), I cat (U, α)), R(U, I prod (U, A), I cat (U, β)), and R(U, I prod (U, A), I cat (U, γ)). In addition, the acceptance of each information category in information categories α, β, and γ of product B is defined as R(U, I prod (U, B), I cat (U, α)), R(U, I prod (U, B), Icat (U, β)) and R(U, I prod (U, B), I cat (U, γ)). Additionally, the acceptance of each information category α, β, and γ of product C is defined as R(U, I prod (U, C), I cat (U, α)), R(U, I prod (U, C), I cat (U, β)) and R(U, I prod (U, C), I cat (U, γ)).

[0158] For example, in the case of R(U, I prod , I cat ) = (I prod (U, p) + I cat (U, c)) / 2, as shown in the left - hand part of Figure 8 , when the product interest degrees I prod (U, A), I prod (U, B) and I prod (U, C) are 1, 0.3, and 0.2 respectively, and the information - category interest degrees I cat (U, α), I cat (U, β) and I cat (U, γ) are 1, 0.8, and 0.1 respectively, the acceptance of each information category of the product R(U, I prod , I cat ) is calculated as the value shown in the right - hand part of Figure 8 .

[0159] That is to say, the acceptances of information categories α, β, and γ of product A, R(U, I prod (U, A), I cat (U, α)), R(U, I prod (U, A), I cat (U, β)) and R(U, I prod (U, A), I cat (U, γ)) are calculated as 1 (=(1 + 1) / 2), 0.9 (=(1 + 0.8) / 2), and 0.55 (=(1 + 0.1) / 2) respectively.

[0160] In addition, the acceptances of information categories α, β, and γ of product B, R(U, I prod (U, B), I cat (U, α)), R(U, I prod (U, B), I cat (U, β)) and R(U, I prod (U, B), Icat (U, γ)) are calculated to be 0.65 (= (0.3 + 1) / 2), 0.55 (= (0.3 + 0.8) / 2), and 0.2 (= (0.3 + 0.1) / 2), respectively.

[0161] In addition, the acceptance degrees R(U, I prod (U, C), I cat (U, α)), R(U, I prod (U, C), I cat (U, β)), and R(U, I prod (U, C), I cat (U, γ)) are calculated to be 0.6 (= (0.2 + 1) / 2), 0.5 (= (0.2 + 0.8) / 2), and 0.15 (= (0.2 + 0.1) / 2), respectively.

[0162] Note that although examples in which the item interest degree and the information category interest degree are combined in the calculation of the acceptance degree have been described above, the information category interest degree is not necessary, and the item interest degree can be directly used as the acceptance degree because it is basically sufficient to obtain the acceptance degree of the entire information related to the item.

[0163] <Specific calculation method of acceptance difficulty>

[0164] Next, with reference to Figure 9 and Figure 10 a specific calculation example of the acceptance difficulty will be described.

[0165] As described above, the acceptance difficulty is calculated based on the expected demand values of the information amount and the information category. For example, in the presence of items A, B, and C and information categories α, β, and γ, as Figure 9 shown, the expected demand values of the information amount and each information category are defined.

[0166] In the Figure 9 upper left part, the information amounts Q(i(p, c)) of the information categories α to γ of item A, the information categories α to γ of item B, and the information categories α to γ of item C are defined in order from the left. Here, i(p, c) is the information of the information category c of item p.

[0167] More specifically, the information amounts of the information categories α to γ of item A are defined as the information amounts Q(i(A, α)), Q(i(A, β)), and Q(i(A, γ)). In addition, the information amounts of the information categories α to γ of item B are defined as Q(i(B, α)), Q(i(B, β)), and Q(i(B, γ)). Further, the information amounts of the information categories α to γ of item C are defined as Q(i(C, α)), Q(i(C, β)), and Q(i(C, γ)).

[0168] At Figure 9 the lower left part of, the expected demand values E(c) of the corresponding information categories among information categories α, β, and γ are defined as the expected demand values E(α), E(β), and E(γ) of the information categories in sequence from the left.

[0169] At Figure 9 the right part of, the acceptance difficulty D(Q, E) of each information category of each commodity is defined. More specifically, the acceptance difficulties of information categories α, β, and γ of commodity A are defined as D(Q(i(A, α)), E(α)), D(Q(i(A, β)), E(β)), and D(Q(i(A, γ)), E(γ)), respectively. In addition, the acceptance difficulties of information categories α, β, and γ of commodity B are defined as D(Q(i(B, α)), E(α)), D(Q(i(B, β)), E(β)), and D(Q(i(B, γ)), E(γ)), respectively. Further, the acceptance difficulties of information categories α, β, and γ of commodity C are defined as D(Q(i(C, α)), E(α)), D(Q(i(C, β)), E(β)), and D(Q(i(C, γ)), E(γ)), respectively.

[0170] The smaller the amount of information Q(i(p, c)), the lower the acceptance difficulty D(Q, E), and the higher the expected demand value E(c) of the information category, the lower the acceptance difficulty.

[0171] For example, in the case where the acceptance difficulty D(Q, E) = min(1, |1 - E(c)| + Q(i(p, c)) / 100), as Figure 10 shown in the left part of, when the amounts of information Q(i(A, α)), Q(i(A, β)), and Q(i(A, γ)) are 11, 20, and 18 respectively, the amounts of information Q(i(B, α)), Q(i(B, β)), and Q(i(B, γ)) are 7, 18, and 25 respectively, the amounts of information Q(i(C, α)), Q(i(C, β)), and Q(i(C, γ)) are 10, 11, and 27 respectively, and the expected demand values E(α), E(β), and E(γ) are 1, 0.8, and 0.2 respectively, the acceptance difficulty D(Q, E) is calculated as the values shown in Figure 10 the right part of.

[0172] That is to say, the acceptance difficulties D(Q(i(A, α)), E(α)), D(Q(i(A, β)), E(β)), and D(Q(i(A, γ)), E(γ)) of information categories α, β, and γ of commodity A are calculated as 0.11 (= min(1, 0 + 0.11)), 0.4 (= min(1, 0.2 + 0.2)), and 0.98 (= min(1, 0.8 + 0.18)), respectively.

[0173] In addition, the acceptance difficulties D(Q(i(B, α)), E(α)), D(Q(i(B, β)), E(β)), and D(Q(i(B, γ)), E(γ)) for information categories α, β, and γ of product B are calculated as 0.07 (=min(1, 0 + 0.07)), 0.38 (=min(1, 0.2 + 0.18)), and 1 (=min(1, 0.8 + 0.25)), respectively.

[0174] In addition, the acceptance difficulties D(Q(i(C, α)), E(α)), D(Q(i(C, β)), E(β)), and D(Q(i(C, γ)), E(γ)) for information categories α, β, and γ of product C are calculated as 0.1 (=min(1, 0 + 0.1)), 0.31 (=min(1, 0.2 + 0.11)), and 1 (=min(1, 0.8 + 0.27)), respectively.

[0175] Note that although an example of using both the expected demand values of the information quantity and the information category for calculating the acceptance difficulty is described, since at least one of the expected demand values of the information quantity and the information category can also be used, the acceptance difficulty can also be obtained only by the information quantity or only by the expected demand value of the information category.

[0176] Here, in the case of only the expected demand value of the information category, for example, the acceptance difficulty D = |1 - E(c)| can be set. In addition, in the case of only the information quantity, the expected demand value E can be a constant such as 0.5, for example.

[0177] In addition, the acceptance difficulty can be determined by an operation. That is, initially, the expected demand value of the information category can be uniformly set to 0.5, and only the information quantity is used as a parameter to determine the acceptance difficulty. In addition, thereafter, the expected demand value can change according to whether it is actually presented and accepted.

[0178] <Process of guiding presentation>

[0179] Next, refer to Figure 11 Describe the process of guiding presentation.

[0180] Figure 11 The information i(p, c) of information categories α, β, γ, and Δ is shown as a matrix for each of products A, B, and C. In addition, in Figure 11 it is assumed that among information categories α, β, γ, and Δ, those with the lowest acceptance difficulty are arranged in the upper part of the drawing, and information categories with higher acceptance difficulty are arranged towards the lower part of the drawing.

[0181] Therefore, in Figure 11Among information categories α, β, γ, and Δ, the information in information category α has the lowest acceptance difficulty and is easily accepted by users. In contrast, the information in information category Δ has the highest acceptance difficulty and is difficult to be accepted by users.

[0182] The information with low acceptance difficulty and easily accepted by users is information with a small amount of information and a high expected demand value, such as corresponding to product names, packaging images, etc. Therefore, here, it is assumed that the information in information category α is the product name, and the information in information category β is the packaging image.

[0183] In addition, the information with high acceptance difficulty and difficult to be accepted by users is information with a large amount of information and a low expected demand value. For example, the display of ingredients such as the amount of salt and the amount of dietary fiber corresponds to this information. Therefore, here, it is assumed that the information in information category γ is the amount of dietary fiber, and the information in information category Δ is the amount of salt.

[0184] Here, the process of guided presentation will be described in the case where the user is in a state of having a weak interest in product A, and the information i(C, Δ) in information category Δ with the highest acceptance difficulty for the uninteresting product C is set as the recommended target information. Therefore, here, the process of guiding and presenting the uninteresting information of the uninteresting product will be described.

[0185] In the first presentation, it is assumed that based on the distance image captured by the depth sensor 32 and the information on the line-of-sight direction detected by the eye tracker 33, etc., the user 21 is in a state of having a weak interest in product A. Therefore, first, the product overview of the information i(A, α) in information category α with the lowest acceptance difficulty for product A indicated by the solid-line frame Z1 in the attached figure is presented.

[0186] Through the first presentation, the information i(A, α) as the product name is presented, increasing the user's interest in product A and improving the acceptance of information related to product A. In addition, by using the first guided presentation, the user's degree of interest in the product can be regarded as changing from weak interest to strong interest.

[0187] Next, in the second presentation, for product A indicated by the dashed-line frame Z2 in the attached figure, presentation information including the information i(A, β), i(A, γ), and i(A, Δ) in information categories β to Δ with a higher acceptance difficulty than the product name of the information i(A, α) in information category α is presented.

[0188] Through this second presentation, the acceptance of information categories with high acceptance difficulty is improved.

[0189] In the third presentation, for example, presentation information for comparison with other products is generated and presented based on information in an information category that includes information indicating that Product C, which is the product to be recommended, has an advantage over Product A, which was initially of weak interest, or information with characteristics, in an information category with relatively low acceptance difficulty.

[0190] Figure 11 An example is shown where the information in information category β includes information indicating that Product C, which is the product to be recommended, has an advantage over Product A, which was initially of weak interest. In this case, assuming that the information i(A, β), i(B, β), and i(B, β) in information category β for each of Products A to C surrounded by the dashed line box Z3 is used as a reference, presentation information for comparing Products A to C is generated and presented.

[0191] Through the third presentation, the user, based on the comparison information in information category β, identifies that Product C, which the user was not initially interested in, has an advantage or characteristics over Product A, which the user was weakly interested in. As a result, the user's interest in Product C is higher, and the acceptance of information related to Product C is higher.

[0192] Therefore, through the fourth presentation, the recommended object information i(C, Δ) surrounded by the broken line box Z4 is presented. The recommended object information i(C, Δ) is presented in a state where the acceptance of information related to Product C, which the user was initially not interested in, has been increased through the processing up to the third presentation. Thus, the recommended object information i(C, Δ) is presented to the user in a state that is easy to accept.

[0193] That is, through the above series of guiding presentations, even information that the user was not interested in during the selection action can be easily accepted by the user.

[0194] Note that in the above description, it is assumed that the acceptance is effectively increased through each presentation, but the acceptance of the presentation is not necessarily increased. Therefore, it is also possible to calculate the interest degree and acceptance degree each time information is presented, and in the case where the acceptance does not increase, repeatedly perform the process of generating and presenting presentation information in sequence using information in different information categories until the acceptance increases.

[0195] For example, in the case where there are multiple products showing weak interest, it is also possible to switch the product used as a reference in the first presentation and repeatedly perform the above guiding presentation until the recommended object information has an acceptable acceptance.

[0196] In addition, in the case where there are multiple information categories used as references in the third presentation, it is also possible to switch the information category used as a reference in the third presentation until the recommended object information has an acceptable acceptance, generate presentation information including the above comparison information, and repeatedly perform the guiding presentation.

[0197] Note that in the case where there is a strong interest in Product A from the beginning, the first presentation can also be omitted, and the guiding presentation can start from the second presentation.

[0198] In addition, in the third presentation, information related to the product that was only weakly interested in initially but later became strongly interested and information related to the recommended product that the user is not interested in are presented simultaneously. Through this presentation, it is necessary to make the user interested in the recommended product that the user is not interested in, and ultimately increase the acceptance of the recommended information.

[0199] Therefore, in the third presentation, it is desirable to present presentation information including such comparison information that enables the user to recognize that the recommended product has more advantages or characteristics compared to the product that was only weakly interested in initially but later became strongly interested.

[0200] <Specific examples of guiding presentation>

[0201] Next, specific examples of the guiding presentation will be described.

[0202] For example, as Figure 12 shown, consider the case where the depth sensor 32 and the eye tracker 33 recognize that the user 21, who is a visitor to the store, directs his / her line of sight to the range VE on the product shelf 35 where Products A to C surrounded by a dotted line are displayed.

[0203] Here, a specific example of the guiding presentation will be described when guiding to the state of presenting the product information of Product E in the dotted line box from the state where the product interest level of Product A in the solid line box in Figure 12 is confirmed to be weakly interested by the user.

[0204] At this time, for example, as Figure 13 shown, it is assumed that for Products A to E, the acceptance difficulty is obtained for each information category in the information categories of "product name", "packaging image", "dietary fiber content", and "salt content".

[0205] Figure 13 The figure shows an example of the acceptance difficulty of each of Products A to E in the case where the information categories are arranged in the order of "product name", "packaging image", "dietary fiber content", and "salt content" from left to right in the figure in such a way that the acceptance difficulty increases from the upper row to the lower row.

[0206] More specifically, the acceptance difficulties of the corresponding information categories of "product name", "packaging image", "dietary fiber content", and "salt content" of Products A to E are 0.5, 0.5, 0.7, and 0.9 respectively.

[0207] That is, the acceptance difficulty of "product name" and "packaging image", which are information categories of easy-to-accept information with little information content and high demand, is 0.5 for any of the products A to E.

[0208] On the other hand, the acceptance difficulties of "dietary fiber content" and "salt content", which are information categories of difficult-to-accept information with large information content and low demand, are 0.7 and 0.9 respectively for any of the products A to E. That is, the demand for the information category of "salt content" is particularly low, so the acceptance difficulty is the highest, at 0.9.

[0209] On the other hand, for example, as Figure 14 shown, similar to the case of acceptance difficulty, it is assumed that for products A to E, the acceptance degrees are obtained for each of the information categories "product name", "packaging image", "dietary fiber content", and "salt content".

[0210] More specifically, the acceptance degrees of the corresponding information categories of "product name", "packaging image", "dietary fiber content", and "salt content" of product A are set to 1, 1, 0.5, and 0.3 respectively.

[0211] In addition, the acceptance degrees of the corresponding information categories of "product name", "packaging image", "dietary fiber content", and "salt content" of product B are set to 0.4, 0.4, 0.2, and 0.1 respectively.

[0212] Furthermore, the acceptance degrees of the corresponding information categories of "product name", "packaging image", "dietary fiber content", and "salt content" of product C are set to 0.3, 0.3, 0.15, and 0.1 respectively.

[0213] In addition, the acceptance degrees of the corresponding information categories of "product name", "packaging image", "dietary fiber content", and "salt content" of products D and E are uniformly set to 0.

[0214] That is, in product A with weak interest, in the order of easy-to-accept information categories, the acceptance degrees of "product name", "packaging image", "dietary fiber content", and "salt content" are set to the highest 1, 1, 0.5, and 0.5 in each information category.

[0215] In addition, in the identified range VE of the line of sight, in the order of proximity to product A with weak interest in the same information category, the acceptance degrees are set in the order of products B and C. However, for products B and C, the acceptance degree of "salt content", which is the information category with the lowest acceptance degree, is set to the same 0.1.

[0216] In addition, for products D and E outside the identified range VE of the line of sight, since the line of sight is not directed, the acceptance degree is set to 0 in any information category.

[0217] That is to say, in any information category, within the range close to product A which the user has a weak interest in, the acceptance is the highest. As the distance from product A increases, the acceptance decreases, and outside the range VE, the acceptance is 0.

[0218] Here, as Figure 15 shown, the recommended object information is the product information of product E surrounded by a broken line box in the figure where the acceptance is currently set to 0.

[0219] On the other hand, the information with an acceptance higher than the acceptance difficulty that can be accepted by user 21 who is a visitor to the store is, as Figure 15 shown, the information of product A surrounded by a solid line box and shaded, and the information categories are "product name" and "packaging image".

[0220] That is to say, as Figure 15 shown, the acceptance degrees of the information categories "product name" and "packaging image" of product A are both 1, but as Figure 13 shown, the acceptance difficulties of the information categories "product name" and "packaging image" of product A are both 0.5, and the acceptance is higher than the acceptance difficulty. Therefore, the information where the information categories of product A are "product name" and "packaging image" can be considered to be acceptable to the user.

[0221] Here, for example, as Figure 16 shown, such presentation information is presented on the display 34, and the presentation information includes the information of product A where the information categories are "product name" and "packaging image" that can be accepted by user 21, and the information of product B and C where the information categories are "product name" and "packaging image" which are not acceptable to user 21 but the line of sight is recognized as pointing to and exist in the range VE.

[0222] In Figure 16 , as shown in the upper right part of the figure, the following state is shown: The image indicating the range VE on the product shelf 35 where the line of sight is pointed to and the information of the information categories of products A to C including "product name" and "packaging image" are displayed on the display 34 as presentation information, and this information includes the information category of product A that contains the information of "product name" and "packaging image" acceptable to user 21 existing in this range VE.

[0223] Assume that user 21 views the presentation information as Figure 16 shown, thereby increasing the interest in product A and increasing the acceptance. Thus, for example, as Figure 17 indicated by the dotted text in the left part of, assume that the acceptance degrees of the information of the information categories "dietary fiber content" and "salt content" of product A are respectively from Figure 150.5 and 0.3 are updated to 0.7 and 0.7. Note that, as described above, since the acceptance is obtained based on the product interest and the information category interest, increasing the acceptance means increasing the interest. In other words, it can be said that the higher the interest, the higher the acceptance.

[0224] Then, the acceptances of the information categories "dietary fiber content" and "salt content" of product A are 0.7 and 0.7 respectively, and the corresponding acceptance difficulties are as Figure 17 shown in the right part of 0.7 and 0.9.

[0225] Therefore, the information with the information category of "dietary fiber content" of product A has the same acceptance and acceptance difficulty, so it is information that user 21 can almost accept.

[0226] Therefore, as Figure 18 shown, presentation information is generated by adding information Info1 related to the dietary fiber content, and the presentation information is presented on the display 34.

[0227] In Figure 18 , in addition to presenting the information of the information category where the range VE where the line of sight is directed is recognized, and referring to Figure 16 the information of "product name" and "product packaging" of products A to C in the range VE in the product shelf 35 described, information Info1 related to dietary fiber is also added.

[0228] In the information Info1 related to dietary fiber, the packaging of product A is shown as the information of the information category of dietary fiber on the left side of the figure, and from above the center of the figure, it is recorded in sequence as the product name "product A", "crispy and fresh, slightly salty taste", "energy", "253 kcal", and "carbohydrates = lipids + dietary fiber". In addition, the amount of carbohydrates is recorded as 22.5 g, the amount of lipids is 20.8 g, and the amount of dietary fiber is 1.7 g below the packaging. In addition, 1.7 g of dietary fiber is underlined to emphasize that the information Info1 is related to dietary fiber information.

[0229] Assume that by user 21 viewing the information Info1 about dietary fiber in the presentation information especially as Figure 18 shown, the interest in the information of the information categories "dietary fiber content" and "salt content" increases, and the acceptance improves.

[0230] Therefore, for example, the acceptances of the information of the information categories "dietary fiber content" and "salt content" of product A are updated from Figure 17 0.7 and 0.7 to 0.9 and 0.9 respectively, as indicated by the dotted text in the left part of Figure 19 .

[0231] In addition, it is also assumed that the acceptance degrees of the information of "dietary fiber content" and "salt content" of products B to E, which are other products, are all updated to 0.5.

[0232] Therefore, for product A, the acceptance degree of the information of "dietary fiber content" is 0.9, which is higher than the acceptance difficulty of 0.7, so it becomes information acceptable to user 21. In addition, the acceptance degree of the information of "salt content" of product A is 0.9, which is the same as the acceptance difficulty of 0.9, so it indicates that this information becomes information acceptable to user 21.

[0233] Note that in the case where the change in the degree of interest with respect to the newly presented information exceeds a predetermined value, it is assumed that the user is looking at the presented information with interest. Therefore, in addition to the relationship between the acceptance degree and the acceptance difficulty, it can also be determined that the user has a strong interest.

[0234] Therefore, as Figure 20 shown, detailed information Info2 related to dietary fiber is added to generate the presented information, and this presented information is presented on the display 34.

[0235] In Figure 20 , in addition to the range VE where the line of sight is identified on the product shelf 35, the information of the information categories of "product name" and "product packaging" of products A to C in the range VE, and the information Info1 related to dietary fiber described with reference to Figure 16 , information Info2 including detailed information related to dietary fiber is added.

[0236] In the information Info2 including detailed information related to dietary fiber, as the detailed information related to dietary fiber, "nutritional components of interest", "dietary fiber content", and "carbohydrates = lipids + dietary fiber" are sequentially displayed from the top of the figure. In addition, it is recorded below the table that "for people in their 20s, the daily dietary fiber is about 4g short", and the target value of dietary fiber is shown as 20g, while 16g is ingested but still 4g is lacking.

[0237] In addition, "advantages of dietary fiber" is also recorded below. Hereinafter, as the advantages of dietary fiber, "intestinal regulatory effects such as preventing constipation", "inhibiting the rise of blood sugar levels", "lowering the cholesterol concentration in the blood", and "increasing the proportion of beneficial bacteria in the intestine" are recorded item by item from the top.

[0238] In addition, by adding a display indicated by the dotted ellipse Ev1 to the information Info2 including detailed information about dietary fiber, the added information Info2 emphasizes the detailed information about the amount of dietary fiber that has been added and makes a presentation that leaves a strong impression on user 21.

[0239] At this time, it is assumed that user 21 views information Info2 regarding the amount of dietary fiber in the presented image as shown in Figure 20 thereby increasing the interest in information of the information category "amount of dietary fiber" and increasing the acceptance rate.

[0240] Therefore, for example, it is assumed that the acceptance rate of information of the information category "amount of dietary fiber" for each of products B to E is updated from Figure 1 0.5 to Figure 21 the value indicated by the dotted text in the left part of

[0241] Therefore, since the acceptance rate of information of the information category "amount of dietary fiber" for product A is 0.9 and the acceptance rate of information of the information category "amount of dietary fiber" for products B to E is 0.7, the acceptance rates of products A to E are all greater than or equal to 0.7 of the acceptance difficulty. Therefore, for user 21, the information of the information category "amount of dietary fiber" becomes acceptable information in all of products A to E.

[0242] Therefore, using the information of the information categories of products A to C and product E of "amount of dietary fiber" shown in the thick-line frame in Figure 22 , a presented image of "comparing products by carbohydrate (lipid + dietary fiber)" as shown in Figure 23 is generated. At this time, for products B and C, for comparison, the information of the information categories "product name" and "package image" is also used as indicated by the thick-line frame.

[0243] Note that in Figure 22 , the information of the information categories "product name", "package image", "amount of dietary fiber" of products A to C in the thick-line frame and the information of the information category "amount of dietary fiber" of product E are shown for generating the presented information of "comparing products by carbohydrate (lipid + dietary fiber)" as shown in Figure 23

[0244] More specifically, as shown in Figure 23 , presented information indicating "comparing products by carbohydrate (lipid + dietary fiber)" in the upper right part of the figure is generated and presented on the display 34.

[0245] In Figure 23 , the image indicating the range VE of the line of sight identified on the product shelf 35 is described as "product being viewed". In this range VE, user 21 and the information of products A to C of the information categories "product name" and "package image" are reduced and presented below this image. "Comparing products by carbohydrate (lipid + dietary fiber)" is recorded in the upper right part, and the information Info3 "comparing products by carbohydrate (lipid + dietary fiber)" is presented in the lower left part.​

[0246] In Information Info3, in the upper part, a line graph showing Products A to C and Product E with the vertical axis representing lipids and the horizontal axis representing dietary fiber is presented, and in the lower part, a pie chart showing the ratio of dietary fiber to the daily deficiency amount for each of Products A to C and a bar graph indicating the amount (g) of lipids are shown.

[0247] The four line graphs in the upper part of Information Info3 with the vertical axis being lipids and the horizontal axis being dietary fiber are the line graphs of Product C, A, B, and E from the left in the figure.

[0248] Thus, based on Figure 23 the presented image shown, in the information category of "dietary fiber amount" instead of the information of Product A with weak interest, Product E which has an advantage over Product A is emphasized and presented to User 21.

[0249] Therefore, it is expected that as User 21's interest in Product E increases, the acceptance level will increase. For example, as Figure 24 shown, for all information categories of Product E, the acceptance level is updated to 0.7.

[0250] In this case, for User 21, since the acceptance levels of the information categories of "product name", "packaging image", and "dietary fiber amount" related to Product E become greater than the acceptance difficulty, the information becomes in an acceptable state.

[0251] Therefore, by using the information of the information categories of "product name", "packaging image", and "dietary fiber amount" of Products A to C and Product E indicated by the thick line frame in Figure 25 , the presented information shown in Figure 26 is generated and presented.

[0252] More specifically, as Figure 26 shown, on the right side of Information Info3 "Comparing Products by Carbohydrates (Lipids + Dietary Fiber)", Information Info4 of the information categories of "product name", "packaging image", and "dietary fiber amount" of Product E is presented.

[0253] In Information Info4, a pie chart showing the ratio of dietary fiber of Product E to the deficiency amount in a day and a bar graph indicating the amount (g) of lipids are shown. "Dietary Fiber Amount No. 1!" and "Low Fat No. 1!" are both recorded below the pie chart, and "Please Select and Purchase the Product" is recorded below the bar graph.

[0254] In addition, "Rich in Dietary Fiber" surrounded by an ellipse Ev11 indicated by a single dotted line is recorded below the product name of Product E.

[0255] That is to say, the information categories of product E, which is presented as the recommended object information, are "product name", "packaging image", and "dietary fiber content". It emphasizes that product E is a superior product among any of products A to E in terms of dietary fiber content, and presents information prompting user 21 to purchase product E.

[0256] Thus, since the product information of product E, which was initially not of interest, is presented after becoming acceptable through the above-mentioned guided presentation, it is presented in a state that is easily acceptable to user 21.

[0257] That is to say, first, by presenting the "product name" and "packaging image", which have relatively low acceptance difficulty, in the information categories of product A that user 21 has a weak interest in, the acceptance degree of the information on "dietary fiber content" and "salt content", which are information categories with relatively high acceptance difficulty, is guided to increase relative to product A.

[0258] Next, for the "dietary fiber content", which is the superior information of product E as the recommended object information among the information on "dietary fiber content" and "salt content" in the information categories with increased acceptance degree, present the presentation information including the comparison information of multiple products including products A and E, thereby guiding the interest in product E as the recommended object information, increasing the acceptance degree, and guiding it to a state where the recommended object information is acceptable.

[0259] Then, when the recommended object information becomes acceptable, present product E as the recommended object information. Therefore, it is possible to present the recommended object information of the recommended object product that was initially not of interest in a state that is easily acceptable to user 21. Thus, user 21 can easily accept the recommended object information.

[0260] Note that as described above, in the case where user 21 cannot be interested and the acceptance degree cannot be increased by presenting the image presentation, the presentation content can also be changed and presented repeatedly until the acceptance degree increases relative to the acceptance difficulty.

[0261] For example, in the case where there are multiple information categories in which the recommended object information has advantages, first present the presentation information including the comparison information of the most advantageous information category, and in the case where the acceptance degree cannot be increased, present the presentation information including the comparison information of the second most advantageous information category, etc., and repeat the above process until the recommended object information becomes acceptable.

[0262] In addition, even when the acceptance is presented through step-by-step guidance and is not sufficiently improved relative to the acceptance difficulty and it is not possible to determine that the information is in an acceptable state, when the presentation interest level based on the presentation response to the presented information is higher than a predetermined value, it can be considered that the user has a strong interest in the presented information. Therefore, even if the acceptance difficulty relative to the acceptance is not large enough, it is possible to determine that the information is in an acceptable state and the next guided presentation can be carried out.

[0263] In addition, in the above description, the following examples have been described: presenting the summary information and detailed information of the products within a predetermined range of the line-of-sight direction and the products to be recommended, and determining whether the products are in an acceptable state based on the acceptance and acceptance difficulty of all information categories.

[0264] However, if the number of products or the number of information categories used for presentation or for determining whether they are in an acceptable state is too large, it may not be possible to perform an appropriate narrowing. Therefore, the number of products and the number of information categories used for presentation or for determining whether the information is in an acceptable state can be restricted by providing predetermined conditions.

[0265] For example, the number of products or the number of information categories can be restricted and presented in such a way that the sum of the acceptance and the acceptance difficulty is less than or equal to a threshold value, and it can also be determined whether it is acceptable based on the acceptance and the acceptance difficulty.

[0266] In addition, in addition to the basic information (product name, product packaging, etc.), the number of information categories can generally be about two to three. In addition, the number of products can be about three to five or less.

[0267] In addition, a threshold value for determining the balance between the number of products and the number of information categories (such as reducing the number of information categories when the number of products is large) can be set for limitation.

[0268] In addition, when the estimation accuracy of the interest level is low and when the number of products or the number of information categories is large, it may not be possible to appropriately compare the acceptance and the acceptance difficulty. Therefore, the number of products or the number of information categories can be reduced.

[0269] In addition, as needed, it is also possible to ask user 21 for suggestions on increasing or decreasing the number of categories of specific products, and increase or decrease the number of categories according to the response. For example, an inquiry such as "Are you also interested in this product?" can be made to user 21 regarding a specific product, and the product can be increased or decreased according to the response.

[0270] In addition, for products other than the products with strong interest or the products to be recommended in the information category, presentation information for selecting and comparing the products with the maximum or minimum value in the information category can be generated and presented.

[0271] In addition, although an example has been described in which an information category including the most advantageous information in the recommended object information is presented as the information category to be presented, conversely, an information category including information with the worst recommended object information may be presented.

[0272] Furthermore, the switching timing of the presented information can be switched at a predetermined fixed time, but it can also be switched at an appropriate timing to maintain the user 21's interest for a longer time and enable the user to understand the content more deeply.

[0273] For example, it is also possible to switch and present the presented information when the user's degree of interest changes significantly and exceeds a threshold, or when a specific action is detected in which the user's degree of interest is expected to change significantly and exceed the threshold.

[0274] Here, specific actions in which the user's degree of interest is expected to change significantly and exceed the threshold are, for example, a long gaze retention time (when the user continuously gazes at a product, information, presented information, etc. on the display 34 for a predetermined time or longer), the user touching the display 34, the user touching a product, the user holding a product, the user not moving the body for a predetermined time or longer while facing a specific product, or the user taking a crossed-arm posture for a predetermined time or longer.

[0275] In addition, if the presented content is changed frequently, the user 21 may not be able to read the content or may feel discomfort during the presentation. Therefore, it can be set not to switch the presented information until according to the length of the amount of information to be presented.

[0276] Summarizing the above series of guided presentations, by presenting information of an information category with relatively low acceptance difficulty among products with weak interest, the interest in information of an information category with higher acceptance difficulty is guided, and strong interest is given.

[0277] Moreover, by expanding the acceptable information categories in the products whose interest becomes strong interest, and presenting presentation information that can be compared with multiple products for information categories including advantageous information or characteristic information in the recommended object information in the acceptable information categories, the degree of interest in the recommended object can be increased, and the acceptance degree can be increased.

[0278] Therefore, the acceptance degree of the recommended object information is gradually increased, and according to the comparison with the acceptance difficulty, the acceptance degree is increased relative to the acceptance difficulty. After determining that the recommended object information is acceptable, the recommended object information is presented.

[0279] Accordingly, during the selection operation, the acceptance level is gradually increased by presenting step-by-step guidance, and the recommended object information is presented when it becomes acceptable. Therefore, even if the recommended object information is information with high acceptance difficulty that the user is not initially interested in, the recommended object information can be easily accepted.

[0280] In addition, even if the recommended object information is information with relatively high acceptance difficulty, by repeatedly presenting guidance and gradually increasing the acceptance level until the recommended object information becomes acceptable, the recommended object information can be easily accepted.

[0281] <Recommended Object Information Guided Presentation Process>

[0282] Next, with reference to Figure 27 the flowchart of Figure 4 the information processing system 11 performs the recommended object information guided presentation process.

[0283] In step S31, the object detection unit 71 in the control unit 51 of the information processing device 31 detects the visitors to the store based on the distance image provided by the depth sensor 32.

[0284] In step S32, based on the detection result of the visitors to the store, the object detection unit 71 determines whether there are object visitors to the store within a predetermined distance from the product shelf 35.

[0285] The processes of steps S31 and S32 are repeated until it is determined in step S32 that there are object visitors to the store.

[0286] Then, when it is determined in step S32 that there are visitors to the store, the process proceeds to step S33.

[0287] In step S33, the object detection unit 71 sets the detected object visitors to the store as the object visitors to the store.

[0288] In step S34, the guided presentation process is executed. Note that the guided presentation process will be described in detail with reference to Figure 28 the flowchart later.

[0289] In step S35, it is determined whether the end of the process is indicated. If the end of the process is not indicated, the process returns to step S31 and the subsequent processes are repeated.

[0290] Then, in step S35, when the end of the process is indicated, the process ends.

[0291] Through the above process, the object visitors to the store are detected, the visitors to the store within a predetermined distance from the product shelf 35 are set as the object visitors to the store, and the recommended object information presentation process is executed.

[0292] <Guided Presentation Processing>

[0293] Next, with reference to Figure 28 the flowchart of

[0294] In step S51, the interest degree estimation unit 72 estimates the merchandise interest degree of the merchandise displayed on the merchandise shelf 35 for the object visitor of the store based on the distance image provided by the depth sensor 32, the line-of-sight information of the object visitor of the store provided by the eye tracker 33, and so on.

[0295] In step S52, the interest degree estimation unit 72 determines whether there is a merchandise with a merchandise interest degree greater than or equal to a predetermined value, that is, at least a merchandise with a weak interest among the merchandise with a strong interest and the merchandise with a weak interest.

[0296] In the case where it is determined in step S52 that there is no merchandise with a merchandise interest degree greater than or equal to a predetermined value, the process proceeds to step S64.

[0297] In step S64, the object detection unit 71 determines whether the object visitor of the store continues to exist.

[0298] In the case where it is determined in step S64 that the object visitor of the store continues to exist, the process proceeds to step S51.

[0299] That is, as long as the object visitor of the store continues to exist, in the case where there is no merchandise with a merchandise interest degree greater than or equal to a predetermined value, the processes of steps S51, S52, and S64 are repeated.

[0300] In the case where it is determined in step S52 that there is a merchandise with a merchandise interest degree greater than or equal to a predetermined value, the process proceeds to step S53.

[0301] In step S53, the acceptance degree estimation unit 74 and the acceptance difficulty estimation unit 75 calculate and store the acceptance degree and acceptance difficulty of each information category of the merchandise corresponding to the merchandise group and the recommendation object information within a predetermined range (for example, a predetermined range set with respect to the line-of-sight direction of the object visitor of the store) based on the merchandise with a merchandise interest degree greater than or equal to a predetermined value.

[0302] Note that hereinafter, the merchandise group including the recommended object merchandise set based on the merchandise with a predetermined interest degree for which the acceptance degree and acceptance difficulty are calculated by each of the acceptance degree estimation unit 74 and the acceptance difficulty estimation unit 75 is referred to as the object merchandise group. In the object merchandise group, the acceptance degree and acceptance difficulty of each information category of each merchandise are calculated.

[0303] In step S54, the interest degree estimation unit 72 determines whether there is a product with strong interest among the products whose product interest degree is greater than or equal to a predetermined value.

[0304] In the case where there is no product with strong interest among the products whose product interest degree is determined to be greater than or equal to the predetermined value in step S54, the process proceeds to step S55.

[0305] In step S55, the presentation processing unit 73 generates presentation information including summary information of the products with weak interest, and presents the presentation information on the display 34.

[0306] In step S56, the interest degree estimation unit 72 estimates the product interest degree of the products displayed on the product shelf 35 based on the distance image provided by the depth sensor 32, the line-of-sight information of the object visitors to the store provided by the eye tracker 33, etc. That is, here, by presenting the presentation information including the summary information of the products with weak interest through the process of step S55, the product interest degree of the object visitors to the store that may change is estimated.

[0307] In step S57, the interest degree estimation unit 72 determines whether the product interest degree of the product with weak interest becomes greater than the predetermined value and becomes a product with strong interest.

[0308] In step S57, in the case where it is determined that the product interest degree of the product with weak interest does not become greater than the predetermined value and does not become a product with strong interest, the process proceeds to step S58.

[0309] In step S58, the interest degree estimation unit 72 estimates the presentation interest degree of the presentation information including the summary information of the products with weak interest presented on the display 34 in the process of step S55.

[0310] In step S59, the interest degree estimation unit 72 determines whether the presentation interest degree of the presentation information including the summary information of the products with weak interest is greater than the predetermined value, and judges whether it can be considered that the product becomes a product with strong interest.

[0311] In step S59, in the case where it is determined that the presentation interest degree of the presentation information including the product summary of the products with weak interest is greater than the predetermined value, and it can be considered that the product becomes a product with strong interest, the process proceeds to step S60.

[0312] In step S60, the presentation processing unit 73 generates presentation information including detailed information about the products with strong interest, and presents the presentation information on the display 34.

[0313] In step S61, the interest degree estimation unit 72 estimates the presentation interest degree of the presentation information regarding the detailed information of the product with strong interest presented on the display 34 in the process of step S59.

[0314] In step S62, the interest degree estimation unit 72 determines whether the presentation interest degree of the presentation information including the detailed information of the product with strong interest is greater than a predetermined value, and whether the presentation information based on each information category constituting the detailed information of the product with strong interest is acceptable.

[0315] In step S62, when the presentation interest degree of the presentation information including the detailed information of the product with strong interest is greater than the predetermined value and the presentation information based on each information category constituting the detailed information of the product with strong interest is determined to be acceptable, the process proceeds to step S63.

[0316] In step S63, the recommended object presentation process is executed, and the process of presenting the recommended object information is performed.

[0317] Note that the recommended object presentation process will be described in detail with reference to Figure 29 the flowchart.

[0318] In addition, when it is determined in step S54 that there is a product with strong interest among the products whose product interest degree is greater than or equal to the predetermined value, and when it is determined in step S57 that the product interest degree of the product with weak interest becomes greater than the predetermined value and becomes a product with strong interest, the process proceeds to step S60.

[0319] In addition, when it is determined in step S59 that the presentation interest degree of the presentation information including the product outline of the product with weak interest is less than the predetermined value and it cannot be considered that the product becomes a product with strong interest, and when it is determined in step S62 that the presentation interest degree of the presentation information including the detailed information of the product with strong interest is less than the predetermined value and the presentation information based on the information of the information category of the product with strong interest is unacceptable, the process proceeds to step S64.

[0320] In addition, when the process of step S63 ends, and when it is determined in step S64 that the target visitor of the store does not continue to exist, the process ends.

[0321] That is to say, through the above processing, it is possible to determine the products with strong interest and guide the presentation information based on any information category of the products with strong interest to an acceptable state.

[0322] Note that in the above description, it has been described that based on the presentation interest degree, it is determined whether the presentation information of each information category in the products of strong interest is finally acceptable. However, it is also possible to determine whether the presentation information is acceptable based on whether the acceptance degree of each information category in the products of strong interest is greater than the acceptance difficulty.

[0323] <Recommendation Object Presentation Processing>

[0324] Next, with reference to Figure 29 the flowchart, the recommendation object presentation processing will be described.

[0325] In step S81, the presentation processing unit 73 generates presentation information including information of information categories in which the recommended object information has an advantage over the products of strong interest, and presents the presentation information on the display 34.

[0326] In step S82, the acceptance degree estimation unit 74 estimates the acceptance degree of the object product group.

[0327] In step S83, the acceptability determination unit 78 determines, based on the comparison between the calculated acceptance degree and the initially calculated acceptance difficulty, whether the acceptance degree of the information in the information categories of the presentation information presented in the processing of step S81 is greater than or equal to the acceptance difficulty and whether it is in a state acceptable to the target visitors of the store.

[0328] If it is determined in step S83 that the information in the information categories of the presentation information presented in the processing of step S82 is not in a state acceptable to the target visitors of the store, the process proceeds to step S84.

[0329] In step S84, the interest degree estimation unit 72 estimates the presentation interest degree for the information of the information categories of the presentation information presented in the processing of step S82.

[0330] In step S85, the interest degree estimation unit 72 determines whether the presentation interest degree for the information of the information categories of the presentation information presented in the processing of step S82 is greater than a predetermined value and whether the information of the information categories of the presentation information presented in the processing of step S82 is considered to be in a state acceptable to the target visitors of the store.

[0331] In step S85, if it is determined that the presentation interest degree for the information of the information categories of the presentation information presented in the processing of step S82 is greater than the predetermined value and is considered to be in a state acceptable to the target visitors of the store, the process proceeds to step S86.

[0332] Note that, when it is determined in step S83 that the information on the information category of the presentation information presented in the process of step S82 is in a state acceptable to the target visitors of the store, the processes of steps S84 and S85 are skipped.

[0333] In step S86, the presentation processing unit 73 generates presentation information capable of comparing a product with strong interest with the recommended object information on the information category of the information in which the recommended object information has an advantage over the product with strong interest, and presents the presentation information on the display 34.

[0334] In step S87, the acceptance estimation unit 74 estimates the acceptance of the target product group.

[0335] In step S88, based on the comparison between the calculated acceptance and the initially calculated acceptance difficulty, the acceptability determination unit 78 determines whether the acceptance of the recommended object information is greater than or equal to the reception difficulty, and whether it becomes a state where the recommended object information is acceptable to the target visitors of the store.

[0336] That is, since the presentation information presented in the process of step S86 is viewed by the target visitors of the store, the interest in the product of the recommended object is increased, and it is determined whether the information on the information category of the recommended object information is in an acceptable state.

[0337] In step S88, when it is determined based on the comparison between the calculated acceptance and the initially calculated acceptance difficulty that the acceptance of the recommended object information is greater than or equal to the acceptance difficulty and is not in a state acceptable to the target visitors of the store, the process proceeds to step S89.

[0338] In step S89, the interest estimation unit 72 estimates the presentation interest degree for the presentation information presented in the process of step S86.

[0339] Note that, when it is determined in step S88 that the acceptance of the recommended object information is in a state acceptable to the target visitors of the store, the processes of steps S89 and S90 are skipped.

[0340] In step S90, the interest estimation unit 72 determines whether the presentation interest degree for the presentation information presented in the process of step S86 is greater than a predetermined value, and whether the presentation information presented in the process of step S86 can be considered to be in a state acceptable to the target visitors of the store.

[0341] In step S90, when it is determined that the presentation interest degree for the presentation information presented in the process of step S86 is greater than the predetermined value and can be considered to be in a state acceptable to the target visitors of the store, the process proceeds to step S91.

[0342] In step S91, the presentation processing unit 73 generates presentation information including the recommended object information and presents the presentation information on the display 34.

[0343] Note that in the case where it is determined in step S85 that the presentation interest level of the information in the information category of the presentation information presented in the processing in step S82 is not greater than a predetermined value and cannot be considered to be in a state acceptable to the target visitors of the store, and in the case where it is determined in step S90 that the presentation interest level of the presentation information presented in the processing in step S86 is not greater than a predetermined value and cannot be considered to be in a state acceptable to the target visitors of the store, the process returns to Figure 28 step S51 of the flowchart of

[0344] According to the above processing, information in the information category including information having an advantage over the products with strong interest is presented in the recommended object information, and after making the information in the information category including information having an advantage over the products with strong interest into an acceptable state, presentation information capable of comparing the information in the information category including information having an advantage in the recommended object information with the products with strong interest is generated and presented.

[0345] Therefore, the information having an advantage in the recommended object information compared with the products with strong interest is presented by the information in the information category capable of being compared with the products with strong interest, thereby improving the acceptance of the recommended object information. Then, after the acceptance of the recommended object information becomes higher than the acceptance difficulty and it is confirmed that the recommended object information is acceptable to the target visitors of the store, the recommended object information is presented.

[0346] Thereby, even if initially not interested in the recommended object information, the recommended object information can be presented after the acceptance is sufficiently improved, so that the recommended object information can be easily accepted.

[0347] Note that Figure 29 shows an example where in the case where the improvement of the acceptance is insufficient and the presentation information is determined to be unacceptable, and in the case where the presentation interest level is higher than a predetermined value, the presentation information is considered acceptable. However, presentation information for comparing information in other information categories or information having an advantage over the products with strong interest in other information categories with the recommended object information can also be presented.

[0348] That is, for example, in the case where the recommended object information includes a plurality of information categories each including information having an advantage over the products with strong interest, the presentation information can be repeatedly presented while switching the information categories for the plurality of information categories until the presentation information becomes acceptable.

[0349] <<3. Application Example>>

[0350] According to this method, the selection result or action can be influenced by making user 21 interested in things that the user is not interested in.

[0351] For example, it can be used not only for purchase behaviors in the real world, but also for various scenarios of selection behaviors that accompany user 21 and are not limited to purchases, such as the metaverse and online shopping.

[0352] In other words, in the above example, it starts to be presented when user 21 arrives in front of the product shelf 35, but it can also start to be presented when the user arrives at a scenario where the user performs a selection action in a certain way in the online shopping or metaverse space.

[0353] In addition, the technology of the present disclosure can be applied to, for example, digital out-of-home (DOOH). That is, for example, this technology can be applied to a technology where not only products but also general promotions of events, companies, music groups, sports professional teams, etc. and selection actions of information for public welfare (such as health-related items and etiquette) are carried out at digital signage (advertisements, vending machines, product shelves with displays, etc.) in stations, facilities, towns, etc.

[0354] When applied to DOOH, the object gaze of the present disclosure is replaced with the line-of-sight / facial direction estimation result estimated from the image of the imaging device. In addition, the object contact is replaced with an action such as touching the object estimated from the imaging device image of the camera or reaching for the object with a hand. Further, the presentation reaction is replaced with a gaze at the presented content or a touch.

[0355] In addition, this technology can be applied to scenarios in the cyberspace, such as online shopping, advertisements or stores in the cyberspace, or the metaverse accompanied by other selection actions. In particular, in the cyberspace such as the metaverse, it is considered effective to be able to obtain more various actions of user 21 compared to the real space.

[0356] When applied to online shopping, the object gaze is replaced with the line of sight or facial direction estimated from the image inside the imaging device of the device. In addition, the object contact is replaced with an action of clicking or tapping on the object through an input to a personal computer (PC), zooming through screen conversion, or moving the cursor. Further, the presentation reaction is replaced with a click, tap, etc. on the object by gazing at the presented content or an input to the PC.

[0357] In the case of applying object gaze to a scene in a cyberspace such as the metaverse, the object gaze is replaced with the gaze detection result of a gaze sensor in a head-mounted display (HMD), the face direction detection result of the HMD, the image capture result of an intercom of the device, etc. In addition, object contact is replaced with an operation of extending, selecting, or grasping an object by a virtual reality (VR) controller. Further, the detection results of gaze, selection, expression, etc. on the presented content by a sensor in the HMD or the intercom of the device are used to replace the presentation reaction.

[0358] In addition, in the case of applying the present technology to the above-mentioned DOOH or metaverse space, multiple users 21 can be accommodated.

[0359] That is, in the case where there are multiple people in the presentation area, the area where people gather is set as a popular area, and the information presented in that area is emphasized, thereby enabling the guidance of interest in the popular area.

[0360] On the other hand, even when multiple users 21 view an advertisement, it can be presented independently to each user in the metaverse space. In this case, the degree of interest of each person can be estimated individually, separate content can be presented, and the advertisement can be directed to a specific advertisement.

[0361] In addition, regarding the recommended object information, after purchase, data can be sent to the user's device (such as a smartphone) via NFC, QR code (registered trademark), email, SNS, etc. Therefore, even after leaving the store, it is possible to prompt the user to confirm the information again.

[0362] Furthermore, by managing the history of information obtained at the second or subsequent entry into the store or at the last entry into the store by a cloud server or the like, the store side can obtain information that is easily acceptable by referring to the sending history to the user.

[0363] In addition, in the case where a high degree of interest in a product is not detected, the process can start with presenting the presentation information about the product that the user was previously interested in.

[0364] For example, it is also possible not to present information that has not been accepted in the past, and to preferentially display information that was actively obtained in the past. Before presenting the recommended object information, the order and content of the information to be presented can be optimized according to the detected interested products.

[0365] In addition, the product information in the shopping cart can be used for DOOH, online shopping, the metaverse space, etc. In other words, when it is possible to purchase products through a touch panel or the like, when user 21 uses the function of putting products into the shopping cart, the products put into the shopping cart can also be regarded as the products with the highest degree of interest, the interest degree of user 21 can be estimated, and a presentation with a stronger interest degree can be carried out. For example, comparison information between the products placed in the shopping cart and the products of current interest can be presented.

[0366] In addition, in DOOH, online shopping, the metaverse space, etc., presentation information can be presented at the destination of the line of sight or near the product, so as to reduce the amount of movement of the line of sight and more easily guide the user to the presentation information. In particular, it is expected to play a useful function in outdoor large-screen advertising displays and the like.

[0367] In addition, in the metaverse space, grasping can be detected similarly to the situation of a real store. Therefore, for example, the object of interest of the user can be estimated by using the actions (grasping of objects in the world or objects of attention) until the user reaches the advertisement / store as interest information, or the attributes of user 21 can be estimated to estimate the products or information that the user may be interested in.

[0368] In addition, in the metaverse space, even when the distance from the rooftop advertisement of a building to user 21 is long, or when a large number of users 21 see the advertisement, optimized presentation can be carried out for each user 21.

[0369] Therefore, the interest degree of the user does not increase as the user approaches the advertisement, and it can be estimated that the larger the size of the advertisement occupying the screen / the larger the advertisement viewed from the front / the longer the fixation time, the higher the interest degree.

[0370] In addition, in DOOH, online shopping, and the metaverse space, interest can be guided by changing the configuration of the product shelves themselves.

[0371] For example, the products that user 21 is interested in and the products that are estimated to be more likely to be interested in by user 21 compared with the previous data can also be arranged side by side. More specifically, in the presence of previous information indicating that user 21 likes sweet products, presentation information in which sweet products and the products to be recommended are arranged side by side can be generated and presented.

[0372] In addition, if there may be competition with the products for which interest is to be aroused, that product may not be displayed on the shelf. More specifically, in the presence of previous information that user 21 always purchases a specific beverage, that specific beverage may not be displayed on the shelf so that the user purchases the products to be recommended.

[0373] In addition, when user 21 can estimate information on a product of strong interest, for example, as a product comparison axis, comparison can also be made easier by rearranging the displayed products based on the product of strong interest. More specifically, when user 21 selects products based on the information category of calories, the products can be arranged in descending order of calories starting from the right.

[0374] In addition, when changing the configuration of the product shelf, at the timing before displaying the product shelf, estimate the attributes and objects of interest of user 21 based on the behavior of user 21 before arriving at the presentation area, the information of user 21 obtained upon arrival, the reaction to the pre-presentation upon arrival, etc., and make changes according to the estimation result. In addition, as long as it is at the timing after the display of the sample shelf, it can also be updated sequentially according to the purchase status and the interest status.

[0375] <<Example Executed by Software>>

[0376] Incidentally, the above series of processes can be executed by hardware, but can also be executed by software. When executing a series of processes by software, install the program forming the software from a recording medium into, for example, a computer built into dedicated hardware or a general-purpose computer capable of executing various functions by installing various programs.

[0377] Figure 30 Shows a configuration example of a general-purpose computer. This computer includes a central processing unit (CPU) 1001. The input / output interface 1005 is connected to the CPU 1001 via a bus 1004. A read-only memory (ROM) 1002 and a random access memory (RAM) 1003 are connected to the bus 1004.

[0378] The input / output interface 1005 is connected to the following units: an input unit 1006, which includes input devices such as a keyboard and a mouse through which the user inputs operation commands; an output unit 1007, which outputs images of the processing operation screen and the processing result to a display device; a storage unit 1008, which includes a hard disk drive or the like that stores programs and various types of data; a communication unit 1009, which includes a local area network (LAN) adapter or the like and performs communication processing via a network represented by the Internet. In addition, a drive 1010 for reading data from and writing data to a removable storage medium 1011 is connected, and the removable storage medium 1011 is such as a magnetic disk (including a floppy disk), an optical disk (including a compact disk-read only memory (CD-ROM) and a digital versatile disk (DVD)), a magneto-optical disk (including a mini disk (MD)), or a semiconductor memory.

[0379] The CPU 1001 executes various types of processing according to a program stored in the ROM 1002 or a program read from a removable storage medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory and installed in the storage unit 1008 and loaded from the storage unit 1008 into the RAM 1003. The RAM 1003 also appropriately stores data and the like required for the CPU 1001 to execute various types of processing.

[0380] In the computer configured as described above, for example, the CPU 1001 loads a program stored in the storage unit 1008 into the RAM 1003 via the input / output interface 1005 and the bus 1004 and executes the program to thereby execute the above-described series of processes.

[0381] A program executed by a computer (CPU 1001) can be provided, for example, by being recorded on a removable storage medium 1011 such as a packaging medium. In addition, the program can be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

[0382] In the computer, by attaching the removable storage medium 1011 to the drive 1010, the program can be installed in the storage unit 1008 via the input / output interface 1005. In addition, the program can be received by the communication unit 1009 via a wired or wireless transmission medium and installed on the storage unit 1008. In addition, the program can be pre-installed in the ROM 1002 or the storage unit 1008.

[0383] Note that the program executed by the computer can be a program that executes processing in the chronological order described in this specification, a program that executes processing in parallel, or a program that executes processing at a necessary timing such as when making a call.

[0384] Note, Figure 30 the CPU 1001 in Figure 4 implements the function of the control unit 51 of the information processing apparatus 31 in

[0385] Note that in this specification, a system refers to a collection of a plurality of configured elements (devices, modules (parts), etc.), and it does not matter whether all the configured elements are in the same housing. Therefore, both a plurality of devices housed in separate housings and connected to each other via a network and a single device including a plurality of modules housed in a single housing are systems.

[0386] In addition, the embodiments of the present disclosure are not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present disclosure.

[0387] For example, the present disclosure may have a configuration of cloud computing, in which multiple devices share a function via a network and collaboratively perform processing.

[0388] In addition, each step described in the above flowchart may be executed by one device, or may be executed by multiple devices in a shared manner.

[0389] In addition, in the case where a single step includes multiple processes, the multiple processes included in the single step may be executed by a single device or by multiple devices in a shared manner.

[0390] Note that the present disclosure may also have the following configuration.

[0391] <1> An information processing apparatus, comprising:

[0392] An interest degree estimation unit that estimates an index of the intensity of a user's interest in a predetermined object as an interest degree;

[0393] A presentation processing unit that generates presentation information for comparing interest object information, which is information related to an interest object, with recommended object information, which is information related to a recommended object to be recommended to the user, and presents the presentation information to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree; and

[0394] An acceptance degree calculation unit that calculates an acceptance degree, which is an index of the ease of acceptance of the recommended object information by the user, based on the interest degree of the user in the presentation information,

[0395] wherein the presentation processing unit presents the recommended object information when the acceptance degree of the user in the recommended object information is higher than a predetermined value.

[0396] <2> The information processing apparatus according to <1>, wherein

[0397] the presentation processing unit presents detailed information of the interest object information, and when the interest degree in the detailed information is higher than a predetermined value, generates presentation information of a predetermined information category for comparing the interest object information with the recommended object information and presents the presentation information to the user.

[0398] <3> The information processing apparatus according to <2>, wherein

[0399] the presentation processing unit generates presentation information of the predetermined information category for comparing the interest object information with the recommended object information, where the recommended object information includes an advantage with respect to the interest object information, and presents the presentation information to the user.

[0400] <4>The information processing apparatus according to <3>, wherein,

[0401] the presentation processing unit

[0402] after generating other presentation information of the predetermined information category that is different from the presentation information, is composed of the interest object information and the recommended object information, and in which the recommended object information includes an advantage with respect to the interest object information, and presenting the other presentation information to the user,

[0403] when the acceptance degree of the other presentation information is higher than a predetermined value, generate presentation information of the predetermined information category that compares the interest object information with the recommended object information and in which the recommended object information includes an advantage, and present the presentation information to the user.

[0404] <5>The information processing apparatus according to <3>, wherein,

[0405] the presentation processing unit

[0406] after generating other presentation information of the predetermined information category that is different from the presentation information, is composed of the interest object information and the recommended object information, and in which the recommended object information includes an advantage with respect to the interest object information, and presenting the other presentation information to the user,

[0407] when the acceptance degree of the other presentation information is lower than a predetermined value and the interest degree in the other presentation information is higher than a predetermined value, generate presentation information of the predetermined information category that compares the interest object information with the recommended object information and in which the recommended object information includes an advantage, and present the presentation information to the user.

[0408] <6>The information processing apparatus according to <3>, wherein,

[0409] when the acceptance degree of the user for the recommended object information is lower than the predetermined value, the presentation processing unit generates presentation information of another information category that is different from the predetermined information category, compares the interest object information with the recommended object information, and in which the recommended object information includes an advantage, and presents the presentation information to the user.

[0410] <7>The information processing apparatus according to <6>, wherein,

[0411] The presentation processing unit repeatedly performs the following processing until the user's acceptance of the recommended object information is higher than the predetermined value: generating presentation information of different information categories in sequence that compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presenting it to the user.

[0412] <8>The information processing apparatus according to <2>, wherein,

[0413] When the degree of interest in the interest object information is higher than a predetermined value, the presentation processing unit presents the detailed information of the interest object information, and,

[0414] When the degree of interest in the presentation of the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of a predetermined information category that compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

[0415] <9>The information processing apparatus according to <2>, wherein,

[0416] When the degree of interest in the interest object information is lower than a predetermined value, the presentation processing unit presents the summary information of the interest object information, and when the degree of interest in the interest object is higher than a predetermined value, presents the detailed information of the interest object information, and,

[0417] When the degree of interest in the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of a predetermined information category that compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

[0418] <10>The information processing apparatus according to <2>, wherein,

[0419] When the degree of interest in the interest object information is lower than a predetermined value, the presentation processing unit presents the summary information of the interest object information, and when the degree of interest in the interest object is not higher than a predetermined value and the degree of interest in the summary information is higher than a predetermined value, presents the detailed information of the interest object information, and

[0420] When the degree of interest in the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of a predetermined information category that compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

[0421] <11>The information processing apparatus according to <1>, wherein,

[0422] When the acceptance degree of the user for the recommended object information is not higher than the predetermined value, the presentation processing unit presents the recommended object information when the interest degree for the presentation information is higher than the predetermined value.

[0423] <12>The information processing apparatus according to any one of <1> to <11>, wherein,

[0424] The acceptance degree is calculated based on the interest degree for the recommended object and the interest degree for the information category of the recommended object information.

[0425] <13>The information processing apparatus according to any one of <1> to <12>, wherein,

[0426] The interest degree is set based on the following: an object gaze score based on the user's gaze at the object, a contact score based on contact or grasping of the object, and a presentation response score based on gaze or touch of the presentation information related to the object.

[0427] <14>The information processing apparatus according to any one of <1> to <13>, wherein,

[0428] The presentation processing unit presents the recommended object information when the acceptance degree of the user for the recommended object information is higher than the acceptance difficulty that is an index of the difficulty of acceptance of the recommended object information by the user.

[0429] <15>The information processing apparatus according to <14>, wherein,

[0430] The acceptance difficulty is calculated based on the amount of information of the recommended object information and the demand expectation value.

[0431] <16>The information processing apparatus according to any one of <1> to <15>, wherein,

[0432] The object of interest and the recommended object are products displayed on a product shelf.

[0433] <17>An information processing method, comprising the following steps:

[0434] Estimating an index of the interest intensity of the user for a predetermined object as the interest degree;

[0435] Generating presentation information that compares interest object information that is information related to an object of interest and recommended object information that is information related to a recommended object to be recommended to the user, and presenting it to the user, where the object of interest is an object for which the user shows an interest higher than a predetermined interest degree; and

[0436] Calculate an acceptance degree as an index of the ease of acceptance of the recommended object information by the user based on the degree of interest of the user in the presented information.

[0437] Among them, when the acceptance degree of the recommended object information by the user is higher than a predetermined value, the recommended object information is presented.

[0438] <18>A program for causing a computer to function as:

[0439] An interest degree estimation unit that estimates an index of the intensity of the user's interest in a predetermined object as the interest degree;

[0440] A presentation processing unit that generates presentation information for comparing interest object information, which is information related to an interest object, with recommended object information, which is information related to a recommended object to be recommended to the user, and presents it to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree; and

[0441] An acceptance degree calculation unit that calculates an acceptance degree as an index of the ease of acceptance of the recommended object information by the user based on the degree of interest of the user in the presented information.

[0442] Among them, the presentation processing unit presents the recommended object information when the acceptance degree of the recommended object information by the user is higher than a predetermined value.

[0443] List of reference numerals

[0444] 11 Information processing system, 31 Information processing device, 32 Depth sensor, 33 Eye tracker, 34 Display, 71 Object detection unit, 72 Interest degree estimation unit, 73 Presentation processing unit, 74 Acceptance degree estimation unit, 75 Acceptance difficulty estimation unit, 76 Acceptability determination unit

Claims

1. An information processing apparatus, comprising: an interest degree estimation unit that estimates an index of the intensity of a user's interest in a predetermined object as an interest degree; a presentation processing unit that generates presentation information for comparing interest object information, which is information related to an interest object, with recommendation object information, which is information related to a recommendation object to be recommended to the user, and presents the presentation information to the user, where the interest object is an object in which the user shows an interest higher than a predetermined interest degree; and an acceptance degree calculation unit that calculates an acceptance degree, which is an index of the ease of acceptance of the recommendation object information by the user, based on the interest degree of the user in the presentation information, wherein the presentation processing unit presents the recommendation object information when the acceptance degree of the user in the recommendation object information is higher than a predetermined value.

2. The information processing apparatus according to claim 1, wherein the presentation processing unit presents detailed information of the interest object information, and when the interest degree in the detailed information is higher than a predetermined value, generates presentation information of a predetermined information category for comparing the interest object information with the recommendation object information and presents the presentation information to the user.

3. The information processing apparatus according to claim 2, wherein the presentation processing unit generates presentation information of the predetermined information category for comparing the interest object information with the recommendation object information, where the recommendation object information includes an advantage with respect to the interest object information, and presents the presentation information to the user.

4. The information processing apparatus according to claim 3, wherein the presentation processing unit after generating other presentation information of the predetermined information category, which is different from the presentation information and is composed of the interest object information and the recommendation object information and in which the recommendation object information includes an advantage with respect to the interest object information, and presenting the other presentation information to the user, when the acceptance degree in the other presentation information is higher than a predetermined value, generates presentation information of the predetermined information category for comparing the interest object information with the recommendation object information, where the recommendation object information includes an advantage, and presents the presentation information to the user.

5. The information processing apparatus according to claim 3, wherein the presentation processing unit after generating other presentation information of the predetermined information category, which is different from the presentation information and is composed of the interest object information and the recommendation object information and in which the recommendation object information includes an advantage with respect to the interest object information, and presenting the other presentation information to the user, when the acceptance degree in the other presentation information is lower than a predetermined value and the interest degree in the other presentation information is higher than a predetermined value, generates presentation information of the predetermined information category for comparing the interest object information with the recommendation object information, where the recommendation object information includes an advantage, and presents the presentation information to the user.

6. The information processing apparatus according to claim 3, wherein In a case where the acceptance degree of the user for the recommended object information is lower than the predetermined value, the presentation processing unit generates presentation information of another information category different from the predetermined information category, which compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

7. The information processing apparatus according to claim 6, wherein, the presentation processing unit repeatedly performs the following processing until the acceptance degree of the user for the recommended object information is higher than the predetermined value: generating presentation information of different information categories in sequence, which compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presenting it to the user.

8. The information processing apparatus according to claim 2, wherein, in a case where the degree of interest in the interest object information is higher than a predetermined value, the presentation processing unit presents detailed information of the interest object information, and when the degree of interest in the presentation of the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of the predetermined information category, which compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

9. The information processing apparatus according to claim 2, wherein, in a case where the degree of interest in the interest object information is lower than a predetermined value, the presentation processing unit presents summary information of the interest object information, and when the degree of interest in the interest object is higher than a predetermined value, presents detailed information of the interest object information, and when the degree of interest in the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of the predetermined information category, which compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

10. The information processing apparatus according to claim 2, wherein, in a case where the degree of interest in the interest object information is lower than a predetermined value, the presentation processing unit presents summary information of the interest object information, and when the degree of interest in the interest object is not higher than a predetermined value and the degree of interest in the summary information is higher than a predetermined value, presents detailed information of the interest object information, and when the degree of interest in the detailed information is higher than a predetermined value, the presentation processing unit generates presentation information of the predetermined information category, which compares the interest object information with the recommended object information and includes information on the advantages in the recommended object information, and presents it to the user.

11. The information processing apparatus according to claim 1, wherein, in a case where the acceptance degree of the user for the recommended object information is not higher than the predetermined value, the presentation processing unit presents the recommended object information when the degree of interest in the presentation information is higher than a predetermined value.

12. The information processing apparatus according to claim 1, wherein, Calculate the acceptance degree based on the degree of interest in the recommended object and the degree of interest in the information category of the information of the recommended object.

13. The information processing apparatus according to claim 1, wherein, The degree of interest is set based on the following: an object gaze score based on the user's gaze at the object, a contact score based on contact or grasping of the object, and a presentation response score based on gaze or touch of presentation information related to the object.

14. The information processing apparatus according to claim 1, wherein, When the acceptance degree of the user for the recommended object information is higher than the acceptance difficulty which is an index of the difficulty of acceptance of the recommended object information by the user, the presentation processing unit presents the recommended object information.

15. The information processing apparatus according to claim 14, wherein, Calculate the acceptance difficulty based on the amount of information of the recommended object information and the expected demand value.

16. The information processing apparatus according to claim 1, wherein, The object of interest and the recommended object are products displayed on a product shelf.

17. An information processing method, comprising the following steps: Estimate an index of the intensity of the user's interest in a predetermined object as the degree of interest; Generate presentation information that compares the interest object information, which is information related to the object of interest, with the recommended object information, which is information related to the recommended object to be recommended to the user, and present it to the user, where the object of interest is an object in which the user shows an interest higher than a predetermined degree of interest; and Calculate the acceptance degree, which is an index of the ease of acceptance of the recommended object information by the user, based on the degree of interest of the user in the presentation information, wherein, when the acceptance degree of the user for the recommended object information is higher than a predetermined value, the recommended object information is presented.

18. A program for causing a computer to function as: An interest degree estimation unit that estimates an index of the intensity of the user's interest in a predetermined object as the degree of interest; A presentation processing unit that generates presentation information that compares the interest object information, which is information related to the object of interest, with the recommended object information, which is information related to the recommended object to be recommended to the user, and presents it to the user, where the object of interest is an object in which the user shows an interest higher than a predetermined degree of interest; and An acceptance degree calculation unit that calculates the acceptance degree, which is an index of the ease of acceptance of the recommended object information by the user, based on the degree of interest of the user in the presentation information, wherein, the presentation processing unit presents the recommended object information when the acceptance degree of the user for the recommended object information is higher than a predetermined value.

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