Information processing apparatus, information processing method, and program

Abstract

To grasp a relationship between a degree of complexity of a space and an influence of the degree of complexity.SOLUTION: The information processing apparatus 1 includes the acquisition unit 131 that acquires line-of-sight information indicating a motion of a line of sight of a user in a case in which the user has an experience of viewing a predetermined space and acquires evaluation information for evaluating the predetermined space, the calculation unit 132 that calculates a degree of dispersion of the line of sight of the user indicated by the acquired line-of-sight information and calculates a degree of complexity indicating complexity of the predetermined space on the basis of the calculated degree of dispersion of the line of sight, and the output unit 133 that outputs the degree of complexity calculated by the calculation unit 132 and the evaluation information in association with each other.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Conventionally, there are known devices that support the layout design of spaces such as buildings. For example, Patent Document 1 discloses a device that allows a user to view a virtual reality space, analyzes trends in layout changes based on layout change operations received from the user, and identifies recommended layout aspects. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2011-145979 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, when laying out a space, it is necessary to consider not only the user's requests but also the influence of the complexity of the space.

[0005] The present invention has been made in consideration of these points, and aims to make it possible to grasp the relationship between the degree of complexity of a space and the influence that the degree of complexity has. [Means for solving the problem]

[0006] An information processing device according to a first aspect of the present invention has an acquisition unit that acquires gaze information indicating the movement of the user's gaze when the user has the experience of visually recognizing a specified space and acquires evaluation information that evaluates the specified space, a calculation unit that calculates the degree of dispersion of the user's gaze indicated by the gaze information and calculates a complexity that indicates the complexity of the specified space based on the calculated degree of dispersion of the gaze, and an output unit that associates the complexity calculated by the calculation unit with the evaluation information and outputs it.

[0007] The acquisition unit acquires the gaze information corresponding to each of one or more images when the user views one or more images each showing one or more landscapes that the user can see when the user performs the experience, and the calculation unit may calculate the complexity corresponding to each of the one or more images based on the degree of dispersion of the user's gaze indicated by the gaze information corresponding to each of the one or more images.

[0008] The acquisition unit may acquire gaze information indicating the movement of the user's gaze during each of a plurality of time periods when the user performs the experience, the calculation unit may calculate the complexity corresponding to each of the plurality of time periods based on the degree of dispersion of the user's gaze during each of the plurality of time periods indicated by the gaze information, and the output unit may output information indicating the change in complexity corresponding to each of the plurality of time periods in association with the evaluation information.

[0009] The acquisition unit acquires gaze information indicating the movement of the user's gaze along each of a plurality of routes when the user has the experience of visually viewing a space corresponding to each of the plurality of routes in the specified space, the calculation unit calculates the complexity corresponding to each of the plurality of routes based on the degree of dispersion of the user's gaze along each of the plurality of routes indicated by the gaze information, and the output unit may output the information indicating the complexity corresponding to each of the plurality of routes in association with the evaluation information.

[0010] The acquisition unit may acquire a plurality of pieces of gaze information indicating the gaze movements of each of a plurality of users who have performed the experience, the calculation unit may calculate the complexity corresponding to each of the plurality of users based on the degree of dispersion of the gaze of the user indicated by the gaze information of each of the plurality of users, and calculate a statistical value of the complexity corresponding to each of the plurality of users, and the output unit may output the complexity calculated by the calculation unit in association with the evaluation information.

[0011] The predetermined space may be a real space, a virtual reality space, or an augmented reality space. The acquisition unit may acquire, as the evaluation information, sales information indicating sales at a facility located in the predetermined space or visitor number information indicating the number of visitors to the facility. The acquisition unit may acquire, as the evaluation information, an index value indicating the degree to which the user perceives the predetermined space positively.

[0012] An information processing method according to a second aspect of the present invention is executed by a computer and includes the steps of acquiring gaze information indicating the movement of a user's gaze when the user has the experience of visually viewing a specified space, and acquiring evaluation information evaluating the specified space; calculating the degree of dispersion of the user's gaze indicated by the gaze information, and calculating a complexity indicating the complexity of the specified space based on the calculated degree of dispersion of the gaze; and outputting the calculated complexity in association with the evaluation information.

[0013] A program according to a third aspect of the present invention causes a computer to function as an acquisition unit that acquires gaze information indicating the movement of the user's gaze when the user has the experience of visually viewing a specified space and acquires evaluation information that evaluates the specified space, a calculation unit that calculates the degree of dispersion of the user's gaze indicated by the gaze information and calculates a complexity that indicates the complexity of the specified space based on the calculated degree of dispersion of the gaze, and an output unit that associates the complexity calculated by the calculation unit with the evaluation information and outputs it. [Effects of the Invention]

[0014] The present invention provides an advantage in that it is possible to grasp the relationship between the degree of complexity of a space and the influence of the degree of complexity. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram illustrating an overview of an information processing device. [Figure 2] FIG. 2 is a diagram illustrating a functional configuration of an information processing device. [Figure 3] FIG. 10 is a diagram showing an example of a gaze amount distribution diagram. [Figure 4] FIG. 10 is a diagram illustrating an example of an analysis result screen. [Figure 5] FIG. 10 is a diagram (part 1) showing another example of the analysis result screen. [Figure 6] FIG. 10 is a diagram (part 2) showing another example of the analysis result screen. [Figure 7] FIG. 10 is a diagram (part 3) showing another example of the analysis result screen. DETAILED DESCRIPTION OF THE INVENTION

[0016] [Overview of information processing device 1] FIG. 1 illustrates an overview of an information processing device 1. The information processing device 1 is a computer that supports analysis of the relationship between spatial evaluation and spatial complexity. The information processing device 1 is communicably connected to an analyst terminal 2 used by an analyst A who analyzes the relationship between spatial complexity and the impact of the spatial complexity. The information processing device 1 acquires evaluation information for evaluating a predetermined space from the analyst terminal 2 ((1) in FIG. 1). The spatial complexity is the degree to which a user perceives the space as complex when visually recognizing it, and is calculated, for example, based on the degree of dispersion of the user's line of sight. The predetermined space may be, for example, an actual space, a virtual reality (VR) space, or an augmented reality space. The VR space or the augmented reality space may be, for example, a space to be designed, such as a space in a facility to be constructed, or a space used for a predetermined purpose, such as a game. The evaluation information is information related to the impact of the spatial complexity on a user, such as the number of visitors to the predetermined space or a facility located in the predetermined space, or information indicating sales at the facility located in the predetermined space.

[0017] A user U wears a display device 3, which is a wearable device such as an eye tracker, VR goggles, or a VR headset, and is capable of detecting the user's gaze, and experiences visual recognition of a predetermined space. The VR goggles or VR headset may be an assembly-type VR goggles or VR headset that allows a smartphone or the like to function as VR goggles. Furthermore, if a wearable device such as a VR goggles or a VR headset cannot detect the user's gaze, a gaze detection device that detects the user's gaze may be provided separately from the display device 3.

[0018] The experience of visually perceiving a predetermined space includes the experience of the user U viewing multiple images or videos captured of an actual space or a VR space as the predetermined space, the experience of visually perceiving the actual space while actually moving or staying in the space, and the experience of visually perceiving a VR space representing the predetermined space while moving or staying in the VR space. Furthermore, the multiple images representing the predetermined space are, for example, images captured by an imaging device when the predetermined space is an actual space, and images captured by a virtual imaging device installed in the VR space when the predetermined space is a VR space.

[0019] If the predetermined space is an actual space, the video showing the predetermined space is a video captured by an imaging device, or a video with a 360-degree panoramic view or a 180-degree panoramic view captured by an imaging device capable of capturing a video with a 360-degree panoramic view. If the predetermined space is a VR space, the video showing the predetermined space is a video related to VR content that allows you to experience freely panning around while standing still or moving within the VR space, or a video with a 360-degree panoramic view or a 180-degree panoramic view that allows you to have an experience similar to that experience.

[0020] The display device 3 generates gaze information indicating the movement of the gaze of the user U when the user U has the experience of visually recognizing a predetermined space. The information processing device 1 acquires the gaze information generated by the display device 3 ((2) in FIG. 1).

[0021] When the information processing device 1 acquires the gaze information, it calculates the degree of dispersion of the user's gaze indicated by the acquired gaze information, and calculates a complexity indicating the complexity of a predetermined space based on the calculated degree of dispersion of the gaze ((3) in FIG. 1). The information processing device 1 associates the calculated complexity with the acquired evaluation information and outputs them to the analyst terminal 2 ((4) in FIG. 1). In this way, the analyst using the analyst terminal 2 can grasp the relationship between the spatial complexity and the evaluation information indicating the impact of the spatial complexity.

[0022] [Functional configuration of information processing device 1] Next, a description will be given of the functional configuration of the information processing device 1. FIG. The information processing device 1 includes a communication unit 11, a storage unit 12, and a control unit 13. The communication unit 11 is a communication interface for transmitting and receiving data to and from the analyst terminal 2 and the display device 3 via a network such as the Internet or a wireless LAN, or short-range wireless communication such as Bluetooth (registered trademark).

[0023] The storage unit 12 is, for example, a read-only memory (ROM) and a random access memory (RAM), etc. The storage unit 12 stores various programs for causing the information processing device 1 to function. For example, the storage unit 12 stores a program for causing the control unit 13 of the information processing device 1 to function as an acquisition unit 131, a calculation unit 132, and an output unit 133.

[0024] The control unit 13 is, for example, a CPU (Central Processing Unit). The control unit 13 controls functions related to the information processing device 1 by executing various programs stored in the storage unit 12. The control unit 13 executes the programs stored in the storage unit 12, thereby functioning as an acquisition unit 131, a calculation unit 132, and an output unit 133.

[0025] The acquisition unit 131 acquires gaze information indicating the movement of the user's gaze when the user performs a spatial experience, which is an experience of visually recognizing a predetermined space, and also acquires evaluation information evaluating the predetermined space. For example, the acquisition unit 131 acquires, from the analyst terminal 2, sales information indicating sales at a facility located in the predetermined space or visitor number information indicating the number of visitors to the predetermined space or the facility, as evaluation information evaluating the predetermined space.

[0026] Note that the acquiring unit 131 acquires sales information or visitor number information as evaluation information, but is not limited to this. The acquiring unit 131 may acquire, as evaluation information, an index value indicating the degree to which the user perceives the predetermined space positively. The index value indicating the degree to which the user perceives the predetermined space positively is, for example, the traffic volume indicating the number of people passing through the predetermined space measured in the predetermined space, the number of SNS posts which is the number of posts including comments evaluating the predetermined space on an SNS (Social Networking Service), or the proportion of brain waves detected in a user who has experienced the space that include alpha waves or other brain waves detected when the user's mind and body are relaxed.

[0027] The index value indicating the degree to which the user positively perceives the specified space may be the proportion of heart rates per hour detected for the user who has experienced the space that include heart rates lower than a predetermined threshold, which are detected when the user is mentally and physically relaxed. Alternatively, it may be the proportion of heart rate variability that includes heart rate variability higher than a predetermined threshold, which is detected when the user is mentally and physically relaxed. Note that, although the index value indicating the degree to which the user is relaxed is used as the index value indicating the degree to which the user positively perceives the specified space, it is not limited to this, and an index value indicating the degree to which the user is excited may also be used.

[0028] Furthermore, the acquisition unit 131 acquires gaze information indicating the movement of the gaze of a user when the user has the experience of visually recognizing a predetermined space, for example, via a communication network such as the Internet or short-range wireless communication such as Bluetooth, from the display device 3. There are multiple users who have the experience of visually recognizing a predetermined space, and the acquisition unit 131 acquires multiple pieces of gaze information indicating the movement of the gaze of each of the multiple users.

[0029] The gaze information is, for example, information indicating the movement of the user's gaze corresponding to each of one or more slide images when the user views one or more slide images each showing one or more landscapes corresponding to the predetermined space that the user can view when the user has a spatial experience of viewing the predetermined space. The gaze information is, for example, information that associates a time with the user's gaze position corresponding to the time in a coordinate system set for the slide image.

[0030] For example, the display device 3 allows the user to have a spatial experience of visually recognizing a predetermined space by displaying one or more slide images on the display unit for a predetermined time (e.g., 10 seconds) each. The display device 3 then generates gaze information indicating the movement of the user's gaze when visually recognizing each of the one or more slide images. The acquisition unit 131 acquires the gaze information corresponding to each of the one or more slide images from the display device 3.

[0031] The calculation unit 132 calculates the degree of dispersion of the user's gaze indicated by the gaze information acquired by the acquisition unit 131, and calculates a complexity indicating the complexity of a predetermined space based on the calculated degree of dispersion of the gaze. For example, the calculation unit 132 calculates the complexity corresponding to each of one or more images based on the degree of dispersion of the user's gaze indicated by the gaze information corresponding to each of one or more slide images indicating the predetermined space.

[0032] For example, first, based on the gaze information, the calculation unit 132 identifies a point where the user's gaze stays for a predetermined first time or more during a predetermined time period during which the user is allowed to view one slide image as the user's gaze point. Furthermore, the calculation unit 132 identifies the position of the gaze point by identifying which of a plurality of grid-like regions obtained by dividing the display region of the slide image includes the gaze point. Note that the shape of the region is assumed to be a square, but is not limited thereto and may be another shape such as an equilateral triangle or a regular hexagon.

[0033] Then, the calculation unit 132 generates a gaze amount distribution diagram showing the gaze amount, which is the total number of times each of a plurality of regions is identified as a gaze point during a predetermined time period in which a user views one slide image. Fig. 3 is a diagram showing an example of the gaze amount distribution diagram. Fig. 3 shows a gaze amount distribution diagram when the slide image is divided into 18 horizontal sections and 10 vertical sections. Note that regions without numbers in Fig. 3 are regions where the number of gazes is 0.

[0034] Although the gaze amount distribution diagram indicates the gaze amount, which is the total number of times a gaze point is identified as a gaze point, this is not limited to this. For example, the look area may be an area that the user gazes at from the time when a short-time dwell point where the user's gaze stayed for a second time shorter than a predetermined first time is identified to the time when a dwell point where the user's gaze stayed for the first time or more is identified. Then, the calculation unit 132 may generate a gaze amount distribution diagram that indicates the total number of times each area is identified as a gaze point and the total number of times each area is identified as a look area for each of the multiple areas. In this way, the information processing device 1 can calculate the complexity of a predetermined space taking into account the user's look around behavior.

[0035] The calculation unit 132 calculates the degree of gaze dispersion based on the gaze amounts corresponding to the respective regions when the slide image is divided, which are shown in the gaze amount distribution diagram, and the sum of the gaze amounts. First, the calculation unit 132 calculates the sum of the gaze amounts in one slide image as a sum , the amount of gaze in one area i (where 1≦i≦n) of n areas is a i , the occurrence probability of gaze amount in region i, p i a i / a sum In this case, the information entropy H indicates how much gaze was detected in n regions, and the maximum value of the information entropy H is max and are calculated based on the following formulas (1) and (2).

[0036]

number

[0037] Then, the calculation unit 132 calculates the information entropy H as the maximum value H of the information entropy, as shown in the following equation (3): max The value obtained by dividing by is calculated as a line-of-sight variance value R indicating the degree of line-of-sight variance, and this line-of-sight variance value R is used as the complexity C indicating the complexity of the predetermined space. For example, the calculation unit 132 calculates the complexity C for each of one or more slide images indicating the predetermined space, and calculates the average value of the complexities C of one or more slide images as the complexity C of the predetermined space. s It is calculated as follows.

[0038]

number

[0039] The calculation unit 132 calculates the degree of dispersion R of the gazes of each of the multiple users based on the gaze information of each of the multiple users, and calculates the complexity C for each of the multiple users. Then, the calculation unit 132 calculates a statistical value of the complexity C for each of the multiple users. For example, the calculation unit 132 calculates the average value of the complexity C for each of one or more slide images of the multiple users and the complexity C of a predetermined space of the multiple users. s The average value of the complexity C is calculated as a statistical value of the complexity C.

[0040] Note that the calculation unit 132 calculated the average value of the complexity C corresponding to each of one or more slide images of multiple users, but this is not limited to this, and the minimum value, maximum value, intermediate value, etc. of the complexity C may also be calculated as a statistical value of the complexity C.

[0041] Furthermore, the calculation unit 132 calculates multiple complexity levels C corresponding to the multiple users, but is not limited to this. Alternatively, the calculation unit 132 may calculate one complexity level C corresponding to the multiple users. In this case, for example, for one user u among N users, k (where 1≦k≦N) the amount of gaze in region i in one slide image is a ki , the total amount of gaze is a ksum In this case, the total amount of gaze of N users is asum is expressed as equation (4), and p i is calculated as shown in the following formula (5).

[0042]

number

[0043] Then, the calculation unit 132 adds p , which is the occurrence probability of the gaze amount in the area i calculated by the formula (5), to the above formula (1). i The information entropy H is calculated by applying the above formula (2), and the sum of the gaze amounts of N users calculated by formula (4) a sum Applying the maximum value of information entropy H max Calculate the calculated information entropy H and the maximum value of the information entropy H max and are applied to equation (3) to calculate one complexity C corresponding to multiple users.

[0044] The output unit 133 outputs the complexity calculated by the calculation unit 132 in association with the evaluation information. For example, the output unit 133 outputs to the analyst terminal 2 an analysis result screen in which one or more slide images, a graph showing multiple complexities calculated by the calculation unit 132 for each of the one or more slide images, and the evaluation information are associated with each other.

[0045] 4 is a diagram showing an example of an analysis result screen. For example, when a user selects two spaces X and Y as predetermined spaces, the analysis result screen shown in FIG. 4 displays a plurality of slide images XA to XE corresponding to the space X, the complexity C calculated for each of the plurality of slide images XA to XE, and the average value of the complexity C calculated for each of the plurality of slide images XA to XE, i.e., the complexity C corresponding to the entire space X. s It can be seen that the number of visitors to space X as evaluation information is associated with the number of visitors to space X. Similarly, on the analysis result screen, the plurality of slide images YA to YE corresponding to space Y, the complexity C calculated for each of the plurality of slide images YA to YE, and the complexity C corresponding to the entire space Y are displayed. sIt can be confirmed that the relationship between the complexity of each of the two spaces and the number of visitors to space Y is associated with the evaluation information. In this way, the analyst can understand what level of complexity is appropriate for adjusting the number of visitors while checking the relationship between the complexity of each of the two spaces and the number of visitors.

[0046] [Variations] In the above-described embodiment, the acquisition unit 131 acquired gaze information when the user viewed one or more slide images each showing one or more landscapes that the user can view when the user had the experience of viewing a specified space, but this is not limited to this.

[0047] The acquisition unit 131 may acquire gaze information indicating the movement of the user's gaze in each of a plurality of time periods when the user has the experience of visually recognizing a predetermined space. For example, the playback time of an experience video, which is a video that is shot while moving around a predetermined space and allows the user to have the experience of visually recognizing the predetermined space, may be divided into a plurality of time periods, and the acquisition unit 131 may acquire gaze information indicating the movement of the user's gaze in each of the plurality of time periods when the user views the video.

[0048] The calculation unit 132 may calculate a complexity indicating the complexity of the predetermined space corresponding to each of the multiple time periods based on the degree of dispersion of the user's gaze in each of the multiple time periods indicated by the gaze information. The output unit 133 then associates information indicating the change in complexity corresponding to each of the multiple time periods with the evaluation information and outputs the information to the analyst terminal 2.

[0049] For example, the output unit 133 outputs to the analyst terminal 2 an analysis result screen that associates the trial video with a graph showing the change in complexity corresponding to each of the multiple time periods calculated by the calculation unit 132, a graph showing the playback position of the trial video, and evaluation information.

[0050] FIG. 5 is a diagram (part 1) showing another example of the analysis result screen. The analysis result screen shown in FIG. 5 shows that the experience video M, a graph G showing the complexity of each of multiple time periods obtained by dividing the playback time of the video, and the number of visitors to a predetermined space as evaluation information are associated with each other. In response to a complexity level being selected in the graph G, the analysis result screen may display an image corresponding to a position corresponding to the playback time corresponding to the selected complexity level. Furthermore, a numerical value indicating the selected complexity level may be displayed on the analysis result screen. For example, the numerical value indicating the selected complexity level may be displayed near a bar indicating the playback time in the graph G. This allows the analyst to easily check, for example, the type of space corresponding to the evaluation value selected by the analyst in the graph for multiple evaluation values, and to easily grasp the types of spaces with relatively high spatial complexity and spaces with relatively low spatial complexity.

[0051] Furthermore, the output unit 133 may display, on the analysis result screen, information indicating the distribution of gazes and glances based on the user's gaze information acquired by the acquisition unit 131. For example, the output unit 133 may display, superimposed on the experience video M displayed on the analysis result screen, a heat map image indicating the distribution of gazes and glances based on the user's gaze information corresponding to a predetermined period from the playback time. FIG. 6 is a diagram showing another example (part 2) of the analysis result screen. On the analysis result screen shown in FIG. 6, it can be seen that a heat map image indicating the distribution of user gazes and glances is superimposed on the experience video M. In this way, the analyst can check the heat map image superimposed on the experience video M and confirm what kind of space the gazes and glances are occurring in.

[0052] Furthermore, the acquiring unit 131 may acquire gaze information indicating the movement of the user's gaze along each of a plurality of routes in a predetermined space when the user has the experience of visually recognizing each of the plurality of routes. For example, the acquiring unit 131 may acquire gaze information corresponding to each of the plurality of routes in a predetermined space when the user views each of a plurality of slide images corresponding to each of the plurality of routes.

[0053] The calculation unit 132 may calculate a complexity indicating the complexity of a predetermined space corresponding to each of the multiple routes based on the degree of dispersion of the user's gaze along each of the multiple routes indicated by the gaze information. The output unit 133 then associates information indicating the change in complexity corresponding to each of the multiple routes with the evaluation information and outputs the information to the analyst terminal 2.

[0054] For example, the calculation unit 132 outputs to the analyst terminal 2 an analysis result screen showing slide images corresponding to each of the multiple routes and the complexity indicating the complexity of the predetermined space, as well as associating the analysis result screen with evaluation information of the predetermined space. FIG. 7 is a diagram showing another example (part 3) of the analysis result screen. The analysis result screen shown in FIG. 7 shows multiple slide images corresponding to each of the multiple routes, the complexity I calculated for each of the multiple slide images, and the average value of the complexity I calculated for each of the multiple slide images, i.e., the complexity I corresponding to the route. s It can be confirmed that the spatial complexity of a route is correlated with the number of pedestrians for that route as evaluation information. In this way, the analyst can confirm which of multiple routes corresponds to the most complex space, and evaluate the multiple routes.

[0055] Furthermore, although the acquiring unit 131 acquires gaze information indicating the movement of the user's gaze from the display device 3, the acquisition unit 131 is not limited to this. The acquiring unit 131 may acquire gaze information generated by a gaze estimation tool that estimates the user's gaze. The gaze estimation tool may be, for example, a program that generates gaze information by analyzing the shading of brightness in an image, or a program that learns images and the movement of the user's gaze in the image as training data and outputs gaze information indicating the movement of the gaze in response to an input image. The acquiring unit 131 may then input images that constitute a slide image or a video showing a predetermined space to the gaze estimation tool, causing the gaze estimation tool to generate gaze information, and acquire the gaze information.

[0056] [Effects of this embodiment] As described above, the information processing device 1 according to the present embodiment calculates the complexity of a predetermined space based on the degree of dispersion of the user's gaze based on gaze information indicating the movement of the user's gaze when the user experiences visual recognition of the predetermined space, and outputs the calculated complexity in association with evaluation information evaluating the predetermined space. In this way, the information processing device 1 allows the analyst to grasp the relationship between the complexity of the space and the evaluation information indicating the influence of the complexity.

[0057] The present invention has been described above using embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist of the present invention. For example, all or part of the device can be configured by functionally or physically distributing or integrating any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combination also have the effects of the original embodiments. [Explanation of symbols]

[0058] 1. Information processing equipment 2. Analyst terminal 3 Display device 11 Communications Department 12 Storage section 13 Control Unit 131 Acquisition Department 132 Calculation Unit 133 Output section

Claims

1. an acquisition unit that acquires gaze information indicating a movement of the user's gaze when the user has an experience of visually recognizing a predetermined space, and acquires evaluation information that evaluates the predetermined space; a calculation unit that calculates a degree of dispersion of the user's line of sight indicated by the line of sight information, and calculates a complexity that indicates complexity of the predetermined space based on the calculated degree of dispersion of the line of sight; an output unit that outputs the complexity calculated by the calculation unit and the evaluation information in association with each other; An information processing device having the above.

2. the acquisition unit acquires the line of sight information corresponding to each of one or more images when the user views one or more images each showing one or more landscapes that the user can view when the user performs the experience, and the calculation unit calculates the complexity corresponding to each of the one or more images based on a degree of dispersion of the user's gaze indicated by the gaze information corresponding to each of the one or more images. The information processing device according to claim 1 .

3. the acquisition unit acquires gaze information indicating a movement of the user's gaze in each of a plurality of time periods when the user has performed the experience; the calculation unit calculates the complexity corresponding to each of the plurality of time periods based on a degree of dispersion of the user's gaze in each of the plurality of time periods indicated by the gaze information; the output unit outputs information indicating a change in the complexity corresponding to each of the plurality of time periods and the evaluation information in association with each other. The information processing device according to claim 1 .

4. the acquisition unit acquires gaze information indicating a movement of the user's gaze along each of a plurality of routes when the user has the experience of visually recognizing a space corresponding to each of the plurality of routes in the predetermined space, and the calculation unit calculates the complexity corresponding to each of the plurality of routes based on a degree of dispersion of the user's gaze on each of the plurality of routes indicated by the gaze information; the output unit outputs information indicating the complexity corresponding to each of the plurality of paths and the evaluation information in association with each other. The information processing device according to claim 1 .

5. the acquisition unit acquires a plurality of pieces of gaze information indicating gaze movements of each of a plurality of users who have performed the experience, the calculation unit calculates the complexity for each of the plurality of users based on a degree of dispersion of the gazes of the users indicated by the gaze information of each of the plurality of users, and calculates a statistical value of the complexity for each of the plurality of users; the output unit outputs the complexity calculated by the calculation unit in association with the evaluation information. The information processing device according to claim 1 .

6. The predetermined space is a real space, a virtual reality space, or an augmented reality space. The information processing device according to claim 1 .

7. The acquisition unit acquires, as the evaluation information, sales information indicating sales at a facility located in the predetermined space or visitor number information indicating the number of visitors to the facility. The information processing device according to claim 1 .

8. the acquiring unit acquires, as the evaluation information, an index value indicating a degree to which the user positively perceives the predetermined space; The information processing device according to claim 1 .

9. The computer executes acquiring gaze information indicating a movement of the user's gaze when the user visually recognizes a predetermined space, and acquiring evaluation information evaluating the predetermined space; calculating a degree of dispersion of the user's gaze indicated by the gaze information, and calculating a complexity indicating the complexity of the predetermined space based on the calculated degree of dispersion of the gaze; a step of outputting the calculated complexity and the evaluation information in association with each other; An information processing method comprising:

10. Computer, an acquisition unit that acquires gaze information indicating a movement of the user's gaze when the user has an experience of visually recognizing a predetermined space, and acquires evaluation information that evaluates the predetermined space; a calculation unit that calculates a degree of dispersion of the user's line of sight indicated by the line of sight information, and calculates a complexity that indicates the complexity of the predetermined space based on the calculated degree of dispersion of the line of sight; and an output unit that outputs the complexity calculated by the calculation unit and the evaluation information in association with each other; A program that functions as a

Images