Advertisement position determination method, product placement method, device, equipment and medium

Abstract

The present disclosure provides a method for determining an advertisement position, a product placement method, a device, equipment and a medium, which relates to the technical field of artificial intelligence, and the main technical scheme comprises the following steps: first, collecting a visual focus point according to the visual cone information; second, forming a visual focus point area according to the visual focus point; third, determining a hot visual focus point area from the visual focus point area, wherein the visual focus point area has the most visual focus points; and finally, determining a target advertisement position from the hot visual focus point area. By determining the hot visual focus point area, the hot visual focus point area is used as a candidate area of the advertisement position, and the advertisement position can be quickly determined without relying on historical data and changing the shopping layout, thereby enhancing the timeliness of selecting the advertisement position.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of artificial intelligence, and in particular, to a method for determining an advertising position, a product placement method, device, equipment and medium. BACKGROUND

[0002] In an offline shopping environment, the position of an advertisement is required to be in a place with large traffic, but cannot affect product display. Currently, when determining the position of a supermarket advertising position, a method of predicting or determining the best advertising position under the current period theme through historical data is often used. Although the above method can confirm the advertising position, when determining the position, it depends on historical data, and when the shopping environment changes, it will affect the timeliness of determining the supermarket advertising position. SUMMARY

[0003] The present disclosure aims to at least partially solve one of the technical problems in the related art.

[0004] The present disclosure proposes a method for determining an advertising position, a product placement method, device, equipment and medium, by determining a thermal line of sight focus area, taking the thermal line of sight focus area as a candidate area of the advertising position, and on the basis of not relying on historical data and changes in shopping layout, the advertising position can be quickly determined, and the timeliness of selecting the advertising position is enhanced.

[0005] The first aspect embodiment of the present disclosure proposes a method for determining an advertising position, comprising:

[0006] Collecting a line of sight focus according to the cone information;

[0007] Forming a line of sight focus area according to the line of sight focus, and determining a thermal line of sight focus area from the line of sight focus area, the line of sight focus in the thermal line of sight focus area being the most;

[0008] Determining a target advertising position from the thermal line of sight focus area.

[0009] The second aspect embodiment of the present disclosure proposes a method for determining an advertising position based on a virtual environment, comprising:

[0010] Inputting a simulated person into a virtual shopping scene;

[0011] Tracking the cone information of the simulated person, and collecting a line of sight focus in the virtual shopping scene;

[0012] Confirming a thermal line of sight focus area according to the line of sight focus, the line of sight focus in the thermal line of sight focus area being the most;

[0013] Determining a target advertising position from the thermal line of sight focus area.

[0014] The third aspect of the present disclosure provides a product placing method based on heat vision line, comprising:

[0015] acquiring a target advertising position determined from a heat vision line focus area, wherein the heat vision line focus area has the most vision line focus points;

[0016] confirming a target placing position in a preset shelf layout corresponding to the target advertising position;

[0017] placing products of a corresponding category in the target placing position.

[0018] The fourth aspect of the present disclosure provides a device for determining an advertising position, comprising:

[0019] a first acquisition module configured to acquire a vision line focus point according to a vision cone information;

[0020] a first determination module configured to form a vision line focus area according to the vision line focus point, and determine a heat vision line focus area from the vision line focus area, wherein the heat vision line focus area has the most vision line focus points;

[0021] a second determination module configured to determine a target advertising position from the heat vision line focus area.

[0022] The fifth aspect of the present disclosure provides a device for determining an advertising position based on a virtual environment, comprising:

[0023] a first input module configured to input a simulation person into a virtual shopping scene;

[0024] an acquisition module configured to track vision cone information of the simulation person, and acquire a vision line focus point in the virtual shopping scene;

[0025] a first determination module configured to confirm a heat vision line focus area according to the vision line focus point, wherein the heat vision line focus area has the most vision line focus points;

[0026] a second determination module configured to determine a target advertising position from the heat vision line focus area.

[0027] The sixth aspect of the present disclosure provides a product placing device based on heat vision line, comprising:

[0028] an acquisition module configured to acquire a target advertising position determined from a heat vision line focus area, wherein the heat vision line focus area has the most vision line focus points;

[0029] a first determination module configured to confirm a target placing position in a preset shelf layout corresponding to the target advertising position;

[0030] a placing module configured to place products of a corresponding category in the target placing position.

[0031] The seventh aspect of the present disclosure provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the advertisement position determination method of any one of the first aspect, or implement the advertisement position determination method of any one of the second aspect, or implement the product placement method of any one of the third aspect.

[0032] The eighth aspect of the present disclosure provides a non-transitory computer readable storage medium, which stores a computer program executable by a processor to implement the advertisement position determination method of any one of the first aspect, or implement the advertisement position determination method of any one of the second aspect, or implement the product placement method of any one of the third aspect.

[0033] The ninth aspect of the present disclosure provides a computer program product, which, when instructions in the computer program product are executed by a processor, executes the advertisement position determination method of any one of the first aspect, or implements the advertisement position determination method of any one of the second aspect, or implements the product placement method of any one of the third aspect.

[0034] The above-mentioned embodiment of the present disclosure has at least the following advantages or beneficial effects:

[0035] Firstly, the line-of-sight focus is collected according to the view frustum information, secondly, the line-of-sight focus area is formed according to the line-of-sight focus, the line-of-sight focus area is determined from the line-of-sight focus area, the line-of-sight focus in the line-of-sight focus area is the most, and finally the target advertisement position is determined from the line-of-sight focus area. By determining the line-of-sight focus area, the line-of-sight focus area is used as a candidate area of the advertisement position, and the advertisement position can be quickly determined on the basis of not relying on historical data and the change of shopping layout, thereby enhancing the timeliness of selecting the advertisement position. BRIEF DESCRIPTION OF DRAWINGS

[0036] The above-mentioned and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0037] Figure 1 A flowchart of the advertisement position determination method provided by the embodiment of the present disclosure is shown in the figure;

[0038] Figure 2 A schematic diagram of the product display layer in the shelf provided by the embodiment of the present disclosure is shown in the figure;

[0039] Figure 3 A flowchart of the advertisement position determination method provided by the embodiment of the present disclosure is shown in the figure;

[0040] Figure 4A flowchart of a method for determining an advertising position according to an embodiment of the present disclosure is shown.

[0041] Figure 5 A flowchart of a method for determining an advertising position according to an embodiment of the present disclosure is shown.

[0042] Figure 6 A flowchart of a method for constructing a plurality of simulated persons imitating customer behaviors according to an embodiment of the present disclosure is shown.

[0043] Figure 7 A flowchart of a product placement method based on heat vision according to an embodiment of the present disclosure is shown.

[0044] Figure 8 A structural diagram of a device for determining an advertising position according to an embodiment of the present disclosure is shown.

[0045] Figure 9 A structural diagram of another device for determining an advertising position according to an embodiment of the present disclosure is shown.

[0046] Figure 10 A structural diagram of a product placement device based on heat vision according to an embodiment of the present disclosure is shown.

[0047] Figure 11 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0048] Embodiments of the present disclosure are described in detail below with reference to the accompanying drawings, in which like or similar elements are denoted by the same or similar reference numerals, and various examples of the embodiments are shown. The embodiments described below are examples and are intended to explain the present disclosure, and should not be understood as limiting the present disclosure.

[0049] A method for determining an advertising position, a product placement method, a device, an apparatus, and a medium according to embodiments of the present disclosure are described below with reference to the accompanying drawings.

[0050] Figure 1 A flowchart of a method for determining an advertising position according to an embodiment of the present disclosure is shown.

[0051] The method for determining an advertising position in the embodiments of the present disclosure, as shown in Figure 1 may include the following steps:

[0052] In step 101, a vision focus point is collected according to cone information.

[0053] This application provides an advertising space selection system in a virtual environment. The virtual environment refers to a virtual shopping scene and a virtual simulated person. Based on the simulated person, the system simulates the customer flow in the shopping scene, calculates the focal point area of ​​the customer's line of sight, and selects advertising spaces within the focal point area.

[0054] In practical applications, customer traffic in a virtual shopping scenario can be simulated using a Poisson distribution. Simulated individuals are then input into the virtual shopping scenario to form a digital twin system of the shopping scene. Within this digital twin system, the focal point of the gaze is collected based on the frustum information of multiple simulated individuals.

[0055] As one feasible approach in this application embodiment, the gaze focus can be collected by simulating the lifting angle of a human face. Since the gaze is a straight line, the gaze focus can be determined based on the lifting angle of the human face. As another feasible approach in this application embodiment, any implementation method in related technologies can also be used to determine the gaze focus. This application embodiment does not limit the specific implementation method for collecting the gaze focus.

[0056] Step 102: Form a visual focus area based on the visual focus, and determine a thermal visual focus area from the visual focus area, wherein the thermal visual focus area has the most visual focus.

[0057] In practical applications, a focal zone can be formed based on the gaze focus of each simulated person. For ease of understanding, as shown below... Figure 2 As shown, assuming, Figure 2 The illustrated shelf contains eight product display layers. The circles within each layer represent the focal points of a simulated person's gaze on that layer. Multiple focal points form a focal point area, the formation of which is based on an empirical value. In the specific division of focal point areas, as a first feasible method in this embodiment, the entire shelf can be considered as a single focal point area. As a second feasible method, the entire shelf can be divided into two focal point areas, such as the top four layers forming the first focal point area and the bottom four layers forming the second. As a third feasible method, the focal point area can be directly defined by the composition of the elements that create the focal point. This embodiment does not limit the method of dividing focal point areas.

[0058] In practical applications, the following embodiments will be illustrated by dividing the entire shelf into two visual focus areas, such as the upper four shelves being the first visual focus area and the lower four shelves being the second visual focus area. Figure 2 It can be clearly seen that the number of focal points in the second focal point area is greater than that in the first focal point area. Therefore, the second focal point area is designated as the thermal focal point area.

[0059] Step 103, determining a target advertisement position from the thermodynamic visual line focus area.

[0060] The thermodynamic visual line focus area determined in step 102 is a candidate area of the advertisement position, and the target advertisement position suitable for placing an advertisement can be screened from the thermodynamic visual line focus area.

[0061] In the specific implementation process, when the target advertisement position in the thermodynamic visual line focus area is confirmed, the target advertisement position can be an advertisement position originally existing in the thermodynamic visual line focus area, or a newly set advertisement position at an arbitrary position or a specified position in the thermodynamic visual line focus area, and the specific position of the target advertisement position is not limited.

[0062] The method for determining an advertisement position provided by the embodiment of the present application first collects a visual line focus according to the cone information, then forms a visual line focus area according to the visual line focus, determines a thermodynamic visual line focus area from the visual line focus area, the visual line focus in the thermodynamic visual line focus area is the most, and finally determines a target advertisement position from the thermodynamic visual line focus area. Through the determination of the thermodynamic visual line focus area, the thermodynamic visual line focus area is taken as a candidate area of the advertisement position, and on the basis of not relying on historical data and the change of the shopping layout, the advertisement position can be quickly determined, and the timeliness of selecting the advertisement position is enhanced.

[0063] In order to clearly illustrate how the target advertisement position is determined from the thermodynamic visual line focus area in the present disclosure, the embodiment provides another method for determining an advertisement position. Figure 3 The flowchart of the method for determining an advertisement position provided by the second embodiment of the present disclosure is shown in Figure 3 The method for determining an advertisement position can include the following steps:

[0064] Step 201, acquiring a first product category in the thermodynamic visual line focus area.

[0065] The method described in the embodiment of the present application is applied to a simulated shopping scene, please continue to refer to Figure 2 , Figure 2 The vertical shelf shown in the figure, as well as the horizontal shelf, the rotating shelf and the like, no matter how the style of the shelf is, the products placed thereon have different first product categories, for example: vegetable category, fruit category, daily product category, grain and oil category and the like, in order to facilitate selection and purchase, the product categories placed on the same shelf are usually the same category, or different categories with a correlation relationship are placed.

[0066] It should be noted that in actual application, there can be a case where the same first product category is placed in different thermal line-of-sight focal point areas, a case where different first product categories are placed in the same thermal line-of-sight focal point area, and a case where one first product category is placed in one thermal line-of-sight focal point area. For the convenience of description, the subsequent embodiments take the case where one first product category is placed in one thermal line-of-sight focal point area as an example for description.

[0067] The method described in the embodiments of the present application is applied to a simulated shopping scene, which is obtained by 3D modeling of the overall layout of a supermarket. The simulated shopping scene contains N shelves (N is greater than 1) for placing products, and the first product category corresponding to the products is displayed in the simulated shopping scene.

[0068] In step 202, the target ad position is determined according to the first product category.

[0069] In the embodiments of the present application, in order to make the advertising bring more benefits, when determining the target ad position, the first ad category is consistent with the first product category according to the first product category. For the convenience of understanding, when the first product category is baby products, the first ad category of the advertising is also baby products when determining the target ad position. When the first product category is a snack of a certain brand, the first ad category of the advertising is also a snack category ad when determining the target ad position, and so on. So that the advertising brings the maximum benefit.

[0070] From a technical point of view, when determining the target ad position, first, the corresponding first ad category in the ad library is determined according to the first product category, and the target ad position is determined according to the first ad category. The ad library stores various categories of ads, and after determining the first product category, the ads of the same type can be matched according to the first product category.

[0071] As an extension of the embodiments of the present application, when determining the target ad position, in addition to referring to the first product category, the preset screening condition can also be referred to. The preset screening condition includes but is not limited to at least one of the following contents: 1) the selected target ad position makes the overall layout of the simulated shopping scene more beautiful; 2) the target ad position retains the interaction ability with the customer, such as selecting the height that is level with the customer's line of sight; 3) the area of the target ad position is reasonable, and does not excessively occupy the position of the product, and the number of advertising is regulated.

[0072] Figure 3The embodiment shown details the application scenario of matching the first advertisement category in the advertisement library to the first product category. In actual application, there can also be a case where the first advertisement category in the advertisement library does not match the first product category, or, in order to chain marketing, the second product category of the associated product of the first product category can be used for placement when determining the target advertisement position.

[0073] Figure 4 The flowchart of the advertisement position determination method provided in Embodiment Three of the present disclosure is shown in FIG. 3. Figure 4 The advertisement position determination method can include the following steps:

[0074] In step 301, the second product category associated with the first product category is determined according to historical orders.

[0075] In the specific implementation process, the Apriori association algorithm is used to determine the second product category associated with the first product category. However, it should be noted that this description is not intended to limit the use of the Apriori association algorithm to determine the association relationship. Any association algorithm can be used, and the present embodiment will not be described one by one.

[0076] The target advertisement position and the product are placed in the position of the second product category by using the Apriori association algorithm. The specific process of the Apriori association algorithm for generating associated products is as follows:

[0077] a) Access the historical orders to generate the data of the products contained in each order. Determine the number K of product categories around the target advertisement according to the shelf layout, and set the minimum support threshold;

[0078] b) Input the current product and calculate the support of each frequent 2-item set S = {current product, candidate associated product} (support = P(S));

[0079] c) Only keep the frequent item sets that meet the minimum support threshold at the same time;

[0080] d) Add one associated product to the retained frequent item set and repeat steps b and c;

[0081] e) Obtain the highest support set containing K+1 items as the associated second product category placed around the target advertisement position. For detailed calculation process of the Apriori association algorithm, please refer to the detailed description in the related art, which will not be described one by one in the present embodiment.

[0082] For the convenience of understanding, the first product category and the second product category are exemplified, for example, from historical orders, when the first product category is biscuits, the item set often purchased together in the frequent item set contains milk (60%) and bread (20%), thus it can be determined that when the first product category is biscuits, the associated second product category is milk; when the first product category is toothpaste, the item set often purchased together in the frequent item set contains toothbrush (55%) and soap (30%), thus it can be determined that when the first product category is toothpaste, the associated second product category is toothbrush, and the like.

[0083] Step 302, determining a second advertisement category in the advertisement library according to the second product category.

[0084] The advertisement library stores various categories of advertisements, and after determining the second product category, the advertisements of the same type can be matched according to the second product category.

[0085] Step 303, determining the target advertisement position according to the second advertisement category.

[0086] As an extension of the embodiment of the present application, in addition to referring to the second product category, the preset screening condition can also be referred to in determining the target advertisement position, the preset screening condition includes but is not limited to at least one of the following contents: 1) the selected target advertisement position makes the overall layout in the simulated shopping scene more beautiful; 2) the target advertisement position retains the interaction ability with the customer, for example, the height of the target advertisement position is selected to be in line with the customer's eyesight; 3) the area of the target advertisement position is reasonable, and the position of the product is not excessively occupied, and the number of advertisement placements is regulated.

[0087] The embodiment of the present application also provides a method for determining an advertisement position based on a virtual environment, as shown in the figure, the method comprises the steps of: Figure 5

[0088] Step 401, inputting a simulated person into a virtual shopping scene.

[0089] The embodiment of the present application provides an advertisement position determination system in a virtual environment, the virtual environment refers to the virtual of the shopping scene and the virtual of the simulated person, and the customer flow in the simulated shopping scene is simulated based on the simulated person.

[0090] Step 402, tracking the view cone information of the simulated person, and collecting the line of sight focus in the virtual shopping scene.

[0091] ​The gaze focus area is calculated by simulating the gaze of the customer shopping, and the advertisement position is screened in the gaze focus area. In actual application, the customer flow in the virtual shopping scene can be simulated by Poisson distribution, and the simulated person is input into the virtual shopping scene to form a digital twin system of the shopping scene. In the digital twin system, the gaze focus is collected based on the cone information of the plurality of simulated persons.

[0092] As a feasible manner of the embodiment of the present application, the gaze focus can be collected by simulating the lifting angle of the face. Since the gaze is a straight line, the gaze focus can be determined according to the lifting angle of the face. As another feasible manner of the embodiment of the present application, the gaze focus can also be determined by any implementation manner in the related art, and the embodiment of the present application does not limit the specific implementation manner of collecting the gaze focus.

[0093] Step 403: confirming a heat gaze focus area according to the gaze focus, in which the gaze focus is the most.

[0094] In actual application, the focus area can be formed according to the gaze focus of each simulated person. In the specific division of the gaze focus area, as a first feasible manner of the embodiment of the present application, the entire shelf can be taken as a gaze focus area as a whole. As a second feasible manner of the embodiment of the present application, the entire shelf can be divided into two gaze focus areas, for example, the upper preset layer is a first gaze focus area, and the lower preset layer is a gaze focus area. As a third feasible manner of the embodiment of the present application, the composition of the realized focus is directly taken as the gaze focus area. The division manner of the gaze focus area is not limited by the embodiment of the present application.

[0095] For examples of confirming the heat gaze focus area, refer to Figure 2 and the related description, which will not be repeated here.

[0096] Step 404: determining a target advertisement position from the heat gaze focus area.

[0097] The heat gaze focus area determined in step 403 is taken as a candidate area of the advertisement position, and the target advertisement position suitable for placing the advertisement can be screened in the heat gaze focus area.

[0098] In the specific implementation process, when the target advertisement position in the heat gaze focus area is confirmed, the target advertisement position can be an advertisement position originally existing in the heat gaze focus area, or a newly set advertisement position at any position or a specified position in the heat gaze focus area, and the specific position of the target advertisement position is not limited.

[0099] The method for determining an advertising position provided by the embodiments of the present application inputs a simulation person into a virtual shopping scene, tracks the view cone information of the simulation person, collects the line-of-sight focus in the virtual shopping scene, confirms a hot line-of-sight focus area according to the line-of-sight focus, the line-of-sight focus in the hot line-of-sight focus area is the most, and determines a target advertising position from the hot line-of-sight focus area. Through the determination of the hot line-of-sight focus area in the constructed virtual environment, the hot line-of-sight focus area is taken as a candidate area of the advertising position, and the advertising position can be quickly determined on the basis of not relying on historical data and the change of the shopping layout, thereby enhancing the timeliness of selecting the advertising position.

[0100] Figure 6 The flowchart of the method for constructing a plurality of simulation persons imitating customer behaviors provided by the embodiments of the present application is shown in FIG. 1. Figure 6 The simulation method can include the following steps:

[0101] In step 501, sample information is parsed to determine feature classification and action trajectory, and the feature classification is classified according to whether payment is generated.

[0102] The sample information described in the embodiments of the present application includes but is not limited to preset video information and historical shopping lists. Taking the preset video information as the sample information as an example, the preset video information is the shopping video of the customer collected in the real shopping scene, the customer data in the shopping video can be classified according to the features, and the feature classification is classified according to whether the final purchase (i.e., payment settlement) is made, including but not limited to directly settling after selecting products in the real shopping scene, finally settling after selecting products and wandering in the real shopping scene, and only wandering in the real shopping scene without finally settling.

[0103] When the preset video information is parsed, it can be parsed based on the above-mentioned feature classification, and the corresponding action trajectory under each feature classification is determined. The action trajectory at least includes the behavior trajectory of the same customer from the supermarket entrance to the supermarket exit, the line-of-sight focus of selecting products, and the posture of selecting products.

[0104] For the scene where the sample information is a historical shopping list, the feature classification can be directly determined from the historical shopping list, and the corresponding action trajectory is determined in combination with the preset video information. As another feasible way of the embodiments of the present application, in the scene where the sample information is a historical shopping list, in addition to being able to determine the feature classification from the historical shopping list, a plurality of action trajectories can also be constructed based on the feature classification, the product categories in the historical shopping list, and the real shopping scene layout. The embodiments of the present application are not limited to the specific implementation of determining the feature classification and the action trajectory.

[0105] In step 502, the corresponding relationship between the feature classification and the action trajectory is established.

[0106] The sample information is parsed, all features are classified and action trajectories are extracted as feature-action pairs, and a feature-action pair set is constructed. The action in this step is different from the action trajectory in step 501. The action in this step includes actions related to the visual focus of selecting products, the posture of selecting products, etc., while the action trajectory in step 501 is generally the behavior trajectory of the same customer from the supermarket entrance to the supermarket exit.

[0107] Step 503, learning the correspondence between the feature classification and the action trajectory, and constructing a preset shopping strategy.

[0108] The action abstracted in step 502 is classified or regressed as a label for learning, thereby obtaining a preset shopping strategy model. The training target of the model is to make the feature-action distribution generated by the model match the input trajectory distribution.

[0109] Step 504, inputting the preset shopping strategy into the simulation person, so that the simulation person imitates the feature classification and action trajectory in the preset shopping strategy according to the simulation person.

[0110] The preset shopping strategy is input into the simulation person, and a plurality of simulation persons imitating the behavior of customers are constructed.

[0111] Step 505, inputting the simulation person into a virtual shopping scene to simulate the passenger flow in the shopping scene.

[0112] In the specific application process, the passenger flow in the virtual shopping scene is simulated by using the Poisson distribution, the virtual person passenger flow is placed in the virtual shopping scene, and a digital twin is formed.

[0113] As a refinement of the above embodiment, when forming a visual focus area according to the visual focus, it includes: tracking the visual cone information of the simulation person, collecting the visual focus and the stagnation time in the shopping scene, and confirming the visual focus area according to the visual focus and the stagnation time. In the digital twin system of the simulation shopping scene, the visual cone information of the plurality of simulation persons is used to track the eye information of the simulation person, collect the sum of the visual focus and the stagnation time of the visual cone information on the shelf, and recall the visual focus area according to the visual focus. The hot visual focus area is selected as the candidate area of the advertising position.

[0114] The embodiment of the present disclosure also provides a product placement method based on hot visual lines, as shown in Figure 7 The method comprises the following steps:

[0115] Step 601, obtaining a target advertising position determined from a hot visual focus area, wherein the hot visual focus area has the most visual focus.

[0116] For the implementation of determining the target advertisement position based on the heat vision focus area, refer to the method described in any of the above embodiments, which will not be repeated here.

[0117] In step 602, a target placement position in a preset shelf layout corresponding to the target advertisement position is determined.

[0118] In actual application, the preset shelf layout can be a shelf layout preset in advance. In order to facilitate product placement, a placement position is arranged on each shelf, which is used to indicate the product placement position. The placement positions corresponding to different preset shelf layouts are different, and the embodiments of the present application do not limit the placement positions.

[0119] In step 603, a product of a corresponding category is placed at the target placement position.

[0120] Under the premise of determining the target placement position, a product of a product category corresponding to the target advertisement position is placed at the target placement position.

[0121] The product placement method based on heat vision provided by the present disclosure obtains a target advertisement position determined from a heat vision focus area, wherein the heat vision focus area has the most vision focus points, determines a target placement position in a preset shelf layout corresponding to the target advertisement position, and places a product of a corresponding category at the target placement position. By obtaining the heat vision focus area and determining the target placement position from the heat vision focus area, and placing the corresponding product at the target placement position, even if the shopping layout changes, the advertisement position can be quickly determined, and the timeliness of selecting the advertisement position and placing the corresponding product is enhanced.

[0122] The method described in the embodiments of the present application is applied to a simulated product placement scene. For example, the simulated product placement scene is obtained by 3D modeling of the overall layout of a supermarket. The simulated placement scene includes N shelves (N is greater than 1) for product placement, and products of various categories are displayed in the scene.

[0123] As a refinement of the above embodiments, when determining the target advertisement position from the heat vision focus area in step 601, the following methods can be used, but are not limited to them. The first product category in the heat vision focus area is obtained, and the target advertisement position is determined according to the first product category.

[0124] In the embodiments of the present application, in order to make the advertising consistent with the placement of products, the first target placement position corresponding to the first product category is searched in the preset shelf layout, and the product corresponding to the first product category is placed at the first target placement position. For ease of understanding, when the first product category is mother and baby products, the first target placement position is also for mother and baby products; when the first product category is a certain brand of snacks, the first target placement position is also for snack category advertising, and so on.

[0125] It should be noted that in actual application, there may be a case that the target placement position in the preset shelf layout does not match the position consistent with the first product category, or in order to chain marketing, the second product category of the associated product of the first product category can be placed when the position is consistent with the first product category. Specifically, the second product category associated with the first product category is determined according to historical orders, the second target placement position corresponding to the second product category in the preset shelf layout is determined according to the second product category, and the product corresponding to the second product category is placed at the second target placement position.

[0126] In the specific implementation process, the Apriori association algorithm is used when the second product category associated with the first product category is determined, but it should be noted that this kind of description is not intended to limit that only the Apriori association algorithm can be used to determine the association relationship, but any association algorithm can also be used, and the association algorithm is not described one by one in the embodiments of the present application.

[0127] For ease of understanding, an example of the first product category and the second product category is given, for example, from the historical orders, when the first product category is biscuits, the item set often purchased together contains milk (accounting for 60%) and bread (accounting for 20%), therefore, it can be determined that when the first product category is biscuits, the second product category associated with it is milk; when the first product category is toothpaste, the item set often purchased together contains toothbrush (accounting for 55%) and soap (accounting for 30%), therefore, it can be determined that when the first product category is toothpaste, the second product category associated with it is toothbrush, and so on.

[0128] As an extension of the embodiments of the present application, in addition to referring to the second product category, the preset screening condition can also be referred to when determining the placement product, the preset screening condition includes but is not limited to at least one of the following contents: 1) the selected placement product makes the overall layout more beautiful; 2) the interaction ability of the placement product with the customer, for example, the height of the placement product is selected to be level with the customer's line of sight; 3) the area of the placement product is reasonable, and the position of the product is not excessively occupied, and the number of placement products is regulated.

[0129] In summary, the embodiment of the present application provides an advertisement position selection system in a virtual environment, which can fully consider various environmental factors, does not require historical data, and can easily update the shopping environment in real time when the overall layout of the real shopping scene changes, quickly determine new advertisement positions, enhance timeliness, and find the best advertisement position under the digital twin, with almost no trial and error cost.

[0130] The advertisement position determination method provided in the embodiment of the present application corresponds to the advertisement position determination method provided in the above Figures 1 to 6 The advertisement position determination method provided in the embodiment of the present application corresponds to the advertisement position determination method provided in the above Figures 1 to 6 The advertisement position determination method provided in the embodiment of the present application corresponds to the advertisement position determination method provided in the above

[0131] Figure 8 The structure diagram of the advertisement position determination device provided in the fifth embodiment of the present application.

[0132] As Figure 8 shown, the advertisement position determination device 700 includes:

[0133] The first acquisition module 701 is configured to acquire a line-of-sight focus point according to the cone information.

[0134] The first determination module 702 is configured to form a line-of-sight focus point area according to the line-of-sight focus point, and determine a heat line-of-sight focus point area from the line-of-sight focus point area, in which the line-of-sight focus points are the most.

[0135] The second determination module 703 is configured to determine a target advertisement position from the heat line-of-sight focus point area.

[0136] The advertisement position determination device provided in the embodiment of the present application first acquires a line-of-sight focus point according to the cone information, then forms a line-of-sight focus point area according to the line-of-sight focus point, determines a heat line-of-sight focus point area from the line-of-sight focus point area, in which the line-of-sight focus points are the most, and finally determines a target advertisement position from the heat line-of-sight focus point area. By determining the heat line-of-sight focus point area as a candidate area of the advertisement position, the advertisement position can be quickly determined without relying on historical data and when the shopping layout changes, and the timeliness of selecting the advertisement position is enhanced.

[0137] In a possible implementation manner of the embodiment of the present application, as Figure 8 shown, the second determination module is further configured to:

[0138] acquire a first product category in the heat line-of-sight focus point area;

[0139] determine the target ad position according to the first product category.

[0140] In a possible implementation of the embodiments of the present disclosure, the second determining module is further configured to:

[0141] determine a first ad category in the ad library according to the first product category;

[0142] determine the target ad position according to the first ad category.

[0143] In a possible implementation of the embodiments of the present disclosure, as shown in Figure 8 if the target ad position is not determined according to the first product category, the apparatus further includes:

[0144] a third determining module 704 configured to determine a second product category associated with the first product category according to historical orders;

[0145] a fourth determining module 705 configured to determine a second ad category in the ad library according to the second product category;

[0146] a fifth determining module 706 configured to determine the target ad position according to the second ad category.

[0147] The embodiments of the present disclosure further provide an apparatus 800 for determining an ad position based on a virtual environment, as shown in Figure 9 the apparatus includes:

[0148] a first input module 801 configured to input a simulated person into a virtual shopping scene;

[0149] a collection module 802 configured to track cone information of the simulated person and collect a line-of-sight focus point in the virtual shopping scene;

[0150] a first determining module 803 configured to determine a heat line-of-sight focus area according to the line-of-sight focus point, the heat line-of-sight focus area having the most line-of-sight focus points;

[0151] a second determining module 804 configured to determine a target ad position from the heat line-of-sight focus area.

[0152] The advertisement position determination apparatus provided in the embodiments of the present application inputs a simulation person into a virtual shopping scene, tracks the view cone information of the simulation person, collects a sight focus point in the virtual shopping scene, confirms a hot sight focus point area according to the sight focus point, the hot sight focus point area has the most sight focus points, and determines a target advertisement position from the hot sight focus point area. Through the determination of the hot sight focus point area in the constructed virtual environment, the hot sight focus point area is taken as a candidate area of the advertisement position, and the advertisement position can be quickly determined on the basis of the shopping layout change without relying on historical data, thereby enhancing the timeliness of selecting the advertisement position.

[0153] In a possible implementation manner of the embodiments of the present application, as shown in Figure 9 The apparatus further includes:

[0154] The analysis module 805 is configured to analyze sample information before the simulation person is input into the virtual shopping scene, to determine feature classification and action trajectory, and the feature classification is classified according to whether payment is generated.

[0155] The establishment module 806 is configured to establish a corresponding relationship between the feature classification and the action trajectory.

[0156] The construction module 807 is configured to learn the corresponding relationship between the feature classification and the action trajectory, and construct a preset shopping strategy.

[0157] The second input module 808 is configured to input the preset shopping strategy into the simulation person, so that the simulation person imitates the feature classification and the action trajectory in the preset shopping strategy.

[0158] In a possible implementation manner of the embodiments of the present application, the collection module 802 is further configured to:

[0159] Collect a sight focus point and a stagnation duration in the virtual shopping scene.

[0160] The hot sight focus point area is confirmed according to the sight focus point, and the hot sight focus point area is confirmed according to the sight focus point and the stagnation duration.

[0161] The hot sight focus point area is confirmed according to the sight focus point and the stagnation duration.

[0162] The embodiments of the present application further provide a product placement apparatus 900 based on hot sight, as shown in Figure 10 The apparatus includes:

[0163] The acquisition module 901 is configured to acquire a target advertisement position determined from a hot sight focus point area, wherein the hot sight focus point area has the most sight focus points.

[0164] The first determination module 902 is configured to determine a target placement position in a preset shelf layout according to the target advertising position.

[0165] The placement module 903 is configured to place a product of a corresponding category at the target placement position.

[0166] The product placement device based on heat vision line provided by the present disclosure determines a target advertising position from a heat vision focus area in which the number of vision focus points is the largest, determines a target placement position in a preset shelf layout according to the target advertising position, and places a product of a corresponding category at the target placement position. By obtaining the heat vision focus area and determining the target placement position from the heat vision focus area and placing a corresponding product at the target placement position, even if the shopping layout changes, the advertising position can be quickly determined, and the timeliness of selecting an advertising position and placing a corresponding product is enhanced.

[0167] In a possible implementation of the embodiment of the present disclosure, the obtaining module 901 is further configured to:

[0168] obtain a first product category in the heat vision focus area;

[0169] determine the target advertising position according to the first product category.

[0170] In a possible implementation of the embodiment of the present disclosure, the first determination module 902 is further configured to:

[0171] find a first target placement position corresponding to the first product category in the preset shelf layout;

[0172] The placing a product of a corresponding category at the target placement position includes:

[0173] placing a product corresponding to the first product category at the first target placement position.

[0174] In a possible implementation of the embodiment of the present disclosure, as shown in Figure 10 If the target placement position in the preset shelf layout cannot be determined according to the target advertising position, the device further includes:

[0175] The second determination module 904 is configured to determine a second product category associated with the first product category according to historical orders.

[0176] The third determination module 904 is configured to determine a second target placement position in the preset shelf layout according to the second product category.

[0177] In a possible implementation of the embodiments of the present disclosure, the placing module 903 is further configured to place the product corresponding to the second product category at the second target placing position.

[0178] To achieve the above-mentioned embodiments, the present disclosure further provides a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining an advertising position or the product placing method according to any one of the preceding embodiments of the present disclosure is implemented.

[0179] To achieve the above-mentioned embodiments, the present disclosure further provides a non-transitory computer readable storage medium, which stores a computer program, wherein when the program is executed by a processor, the method for determining an advertising position or the product placing method according to any one of the preceding embodiments of the present disclosure is implemented.

[0180] To achieve the above-mentioned embodiments, the present disclosure further provides a computer program product, wherein when instructions in the computer program product are executed by a processor, the method for determining an advertising position or the product placing method according to any one of the preceding embodiments of the present disclosure is executed.

[0181] Figure 11 A block diagram of an exemplary computer device suitable for implementing embodiments of the present disclosure is shown. Figure 11 The computer device 12 shown is merely one example and should not be taken as limiting the functionality or use of embodiments of the present disclosure.

[0182] As shown in Figure 11 The computer device 12 is shown in the form of a general-purpose computing device. The components of the computer device 12 can include, but are not limited to, one or more processors or processing modules 16, a system memory 28, and a bus 18 that connects the various system components, including the system memory 28 and the processing module 16.

[0183] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0184] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0185] Memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 11 Not shown; usually referred to as a "hard drive"). Although Figure 11 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disc drive for reading and writing to a removable non-volatile optical disc (e.g., a compact disc read-only memory (CD-ROM), a digital video disc read-only memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of this disclosure.

[0186] Program / utility 40 having a set of program modules 42 can be stored in memory 28 by way of example, such program modules 42 include an operating system, one or more application programs, other program modules, and program data, each or some combination thereof, which can include implementation of the network environment in each or some combination thereof. Program modules 42 generally carry out the functions and / or methodologies described in embodiments of the disclosure.

[0187] Computer device 12 can also communicate with one or more external devices 14 such as a keyboard or pointing device, a display 24, etc. one or more devices that enable a user to interact with computer device 12 and / or one or more devices that enable computer device 12 to communicate with one or more other computing devices. Such communication can be via input / output (I / O) interfaces 22. Further, computer device 12 can communicate with one or more networks such as a local area network (LAN), a wide area network (WAN), and / or the Internet through network adapter 20. As depicted, network adapter 20 communicates with the other components of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and / or software modules could be used in conjunction with computer device 12. Examples, include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0188] Processing module 16 performs various function applications and data processing by running programs stored in system memory 28, such as implementing the methods mentioned in the foregoing embodiments.

[0189] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0190] Moreover, the terms "first", "second", "third", etc. are used herein only to describe different instances, and do not imply or suggest relative importance or a number of indicated technical features. Thus, features defined with "first", "second" can include at least one of such features, either explicitly or implicitly. In the description of the disclosure, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly and specifically limited.

[0191] Any process or method descriptions or blocks in flow charts herein, and elsewhere, can be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of the preferred embodiments of this disclosure in which additional functionality can be added or further orders of execution may be implemented without departing from the spirit of the disclosure. Embodiments of the disclosure can be used in varied applications, and are not limited to applications in which various features are used.

[0192] Logic and / or steps represented in flow charts herein, and elsewhere, can be considered as a sequence of executable instructions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch instructions from a instruction execution system, apparatus, or device and execute instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can specifically include a transmission line, a wired or wireless access network, or in other wired or wireless communication over the Internet as examples of apparatuses that can also include multiple networks together or separately. The computer-readable medium can also be specifically a medium that can store such a program and that can be accessed by an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium can include the following: an electrical connection (electronic device), a portable computer diskette (magnetic device), a RAM (random access memory), a ROM (read only memory), an EPROM (erasable programmable ROM) or a flash memory (EPROM), an optical fiber, and a portable CD-ROM (compact disk ROM). Additionally, the computer-readable medium can even be paper or another suitable medium upon which the program can be printed, as the program can be electronically captured, for example, by optically scanning the paper or other suitable medium, then electronically converted into a form that can be edited, compiled, or interpreted, or otherwise processed in electronic form into an executable form suitable for use by the instruction execution system, apparatus, or device.

[0193] It should be understood that various parts of this disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0194] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0195] Furthermore, the functional modules in the various embodiments of this disclosure can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0196] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for determining advertising space based on a virtual environment, characterized in that, include: Introduce a simulated human into a virtual shopping scenario; Track the visual cone information of the simulated human and collect the focal point of the gaze in the virtual shopping scene; The thermal focal point area is identified based on the focal point of the line of sight, and the thermal focal point area contains the most focal points of the line of sight. Determine the target advertising space from the aforementioned thermal focal zone; The method further includes, before inputting the simulated human into the virtual shopping scenario: The sample information is analyzed to determine the feature classification and action trajectory, wherein the feature classification is based on whether a payment has been made; Establish the correspondence between the feature classifications and the action trajectories; The correspondence between the feature classification and the action trajectory is learned to construct a preset shopping strategy; The preset shopping strategy is input into the simulator so that the simulator can imitate the feature classification and action trajectory in the preset shopping strategy.

2. The determination method according to claim 1, characterized in that, The focus of gaze collected in the virtual shopping scenario includes: Collect the focus of eye movement and the duration of eye contact in the virtual shopping scenario; The step of confirming the thermal visual focus area based on the visual focus includes: The thermal visual focus area is determined based on the focal point and duration of stagnation.

3. A device for determining advertising space based on a virtual environment, characterized in that, include: The first input module is used to input simulated humans into the virtual shopping scenario; The acquisition module is used to track the visual cone information of the simulated human and acquire the focal point of the gaze in the virtual shopping scene; The first determining module is used to identify the thermal visual focus area based on the visual focus, wherein the thermal visual focus area has the most visual focuses; The second determining module is used to determine the target advertising position from the thermal line of sight focal area; The device further includes: The parsing module is used to parse sample information before inputting the simulated person into the virtual shopping scenario to determine feature classification and action trajectory. The feature classification is based on whether a payment is generated. A module is established to establish the correspondence between the feature classifications and the action trajectories; A construction module is used to learn the correspondence between the feature classification and the action trajectory to construct a preset shopping strategy; The second input module is used to input the preset shopping strategy into the simulated person, so that the simulated person can imitate the feature classification and action trajectory in the preset shopping strategy.

4. The determining device according to claim 3, characterized in that, The acquisition module is also used for: Collect the focus of eye movement and the duration of eye contact in the virtual shopping scenario; The step of confirming the thermal visual focus area based on the visual focus includes: The thermal visual focus area is determined based on the focal point and duration of stagnation.

5. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the method for determining an advertising space as described in any one of claims 1-2.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for determining the ad placement as described in any one of claims 1-2.

7. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor, the method for determining the advertising space as described in any one of claims 1-2 is performed.

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