JP2024011853A - Commodity arrangement evaluation program, commodity arrangement evaluation method, commodity arrangement evaluation apparatus, and commodity arrangement evaluation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a commodity arrangement evaluation program for evaluating arrangement of commodities that a user shows interest in.

SOLUTION: A commodity arrangement evaluation program to be executed by a computer includes the steps of: acquiring interest information indicating that a user has shown interest in a commodity group composed of a plurality of commodities, the commodities each having location information where the commodities are arranged; generating association information between commodities that the user has shown interest in, in the commodity group, on the basis of the acquired interest information; and outputting the association information. The association information includes distance information between the commodities.

SELECTED DRAWING: Figure 4

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present disclosure relates to a device and the like that evaluates the arrangement of products that a customer (user) is interested in.

When operating a store, it is important to analyze customer preferences. In this regard, conventional methods have been proposed for analyzing the purchasing behavior of customers for products in a store. Specifically, a method has been proposed in which purchasing behavior is analyzed based on the number of times a customer contacts a product, etc. (see Patent Document 1).

Japanese Patent Application Publication No. 2011-253344

On the other hand, conventional methods analyze purchasing behavior based on whether a customer has come into contact with a product, and do not evaluate the placement of products that the user is interested in.

An object of the present disclosure is to provide a product placement evaluation program, a product placement evaluation method, a product placement evaluation device, and a product placement evaluation system that are capable of evaluating the placement of products that a user is interested in.

A product placement evaluation program executed by a computer according to the present disclosure obtains interest information indicating that a user is interested in a product group consisting of a plurality of products, each of which has location information where it is placed. a step of generating related information between the products in which the user has shown interest among the product groups based on the acquired interest information; and a step of outputting the related information, where the related information is based on the distance between the products. Contains information.

Preferably, the step of generating the related information includes the step of calculating the degree of correlation between products in which the user has shown interest among the product group based on the acquired interest information.

Preferably, in the step of calculating the degree of correlation between products, the degree of correlation between products is calculated based on the number of times of interest between the products included in the interest information and the distance between the products.

Preferably, the number of interests is the number of users who have contacted one set of products.

Preferably, the step of outputting the related information includes a step of displaying a line segment indicating a relationship between products, and a step of changing the display form of the line segment based on the calculated degree of correlation between the products.

Preferably, the step of generating related information includes the step of calculating the sum of degrees of correlation between products.

Preferably, the step of outputting the related information includes a step of displaying a plurality of nodes corresponding to a plurality of products, and a step of changing the display form of each node based on the calculated sum of correlations between the products. including.

Preferably, in the step of outputting the related information, the related information is output in a superimposed manner on an image of a product group made up of a plurality of products.

The product placement evaluation method of the present disclosure includes the steps of acquiring interest information indicating that a user has expressed interest in a product group consisting of a plurality of products, each of which has location information. The present invention includes a step of generating related information between products in which a user has shown interest among a group of products based on interest information, and a step of outputting the related information. The related information includes distance information between products.

The product placement evaluation device of the present disclosure includes a storage unit that stores interest information indicating that a user has expressed interest in a product group consisting of a plurality of products, each of which has location information, and a storage unit. The present invention includes a related information generating section that generates related information between a plurality of products in which a user has shown interest among a group of products based on interest information stored in the section, and an output section that outputs the related information. The related information includes distance information between products.

The product placement evaluation system of the present disclosure includes a storage unit that stores interest information indicating that a user is interested in a product group consisting of a plurality of products, each of which has location information, and a storage unit. A related information generation section that generates related information between a plurality of products in which a user has shown an interest among product groups based on interest information stored in the section, and an output section that outputs the related information. , including distance information between products.

These and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention, taken in conjunction with the accompanying drawings.

FIG. 1 is a diagram illustrating an overview of a product placement evaluation system based on an embodiment. FIG. 2 is a diagram illustrating a display example of one frame of moving image data stored in the memory of the product placement evaluation device 1 based on the embodiment. FIG. 2 is a diagram illustrating the hardware of the product placement evaluation device 1 based on the embodiment. 1 is a diagram illustrating functional blocks of a product placement evaluation device 1 based on an embodiment. FIG. FIG. 4 is a diagram illustrating a product placement management information storage unit 402 and a product identification information storage unit 403 based on the embodiment. It is a figure explaining the interest information stored in the interest information storage part 401 based on embodiment. It is a flowchart figure explaining operation of product placement evaluation device 1 based on an embodiment. It is a figure explaining the interest table based on an embodiment. It is a figure explaining the correlation degree table based on an embodiment. It is a figure explaining the related information output by the related information output part 207 based on embodiment. It is another diagram explaining the related information output by the related information output unit 207 based on the embodiment.

Each embodiment will be described below with reference to the drawings. In the following description, the same parts and components are given the same reference numerals. Their names and functions are also the same. Therefore, detailed explanations thereof will not be repeated. Note that each embodiment and each modification described below may be selectively combined as appropriate.

FIG. 1 is a diagram illustrating an overview of a product placement evaluation system based on an embodiment.

Referring to FIG. 1, the product placement evaluation system includes a product placement evaluation device 1 and a video camera 2301. A video camera 2301 is provided in the store 2300. Note that the number of video cameras 2301 is not limited to one, and a plurality of video cameras can be provided.

The video camera 2301 is placed at a position where it can capture images of a plurality of products placed on a display shelf 2302 of the store 2300. Specifically, the video camera 2301 is installed facing a display shelf 2302 on which products to be evaluated (for example, products in the same category) are displayed. The video camera 2301 acquires captured moving image data. The moving images captured by the video camera 2301 are transmitted to the product placement evaluation device 1 and stored in the memory via an interface or the like. The position of the video camera 2301 is preferably such that the product is not hidden by the customer P (user).

The product placement evaluation device 1 analyzes the behavior of the customer P and evaluates the placement of products that the user is interested in.

FIG. 2 is a diagram illustrating a display example of one frame of moving image data stored in the memory of the product placement evaluation device 1 based on the embodiment.

Referring to FIG. 2, here, as shown by dotted lines, in the frame image, using information such as coordinates, an area corresponding to the position of each product is set in advance for each product.

The area ID, which is the identification information of each area, and the product name, which is the product identification information arranged in each area, are associated with each other and stored in the memory in advance.

Using the area, it is determined whether the user has engaged in an action that shows interest (for example, contact).

In this example, a case is shown in which areas 101 to 103 are set for a plurality of products placed on the top shelf of display shelf 2302. Note that areas are also set in advance for each of the plurality of products in the middle and lower tiers of the display shelf 2302. In this example, a case will be described in which one area is set for each product, but an area may be set for each of a plurality of products.

FIG. 3 is a diagram illustrating the hardware of the product placement evaluation device 1 based on the embodiment.

Referring to FIG. 3, product placement evaluation device 1 includes a CPU (Central Processing Unit) 2, a memory 4, and a communication section 6. The CPU 2, the memory 4, and the communication section 6 are connected by a bus and are configured to be able to exchange data with each other. The CPU 2 controls the entire product placement evaluation device 1 .

The memory 4 stores application programs, system programs, etc. for realizing various functions of the product placement evaluation device 1, and also stores various data.

The communication unit 6 is a device for communicating with external devices, and is connected to a video camera 2301 as an example. The communication unit 6 acquires moving image data captured by the video camera 2301 and transmits it to the memory 4, and the memory 4 stores the moving image data.

The communication unit 6 may also be able to communicate with an external server via a network. For example, data may be sent to an external server, and some or all of the processing by the CPU 2 may be executed in the external server. In this example, a case will be described in which moving image data stored in the memory 4 is used. It is also possible to

Furthermore, although the product placement evaluation device 1 will be described as operating standalone, it may be a server device in a server/client system. In the latter case, the reception unit and the output unit will accept input and output a screen via the communication line.

Furthermore, in this embodiment, each component may be configured by dedicated hardware, or components that can be implemented by software may be implemented by executing a program. For example, each component can be realized by a program execution unit such as a CPU reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

Note that in the above program, the functions realized by the program do not include functions that can only be realized by hardware. For example, functions that can only be realized by hardware such as a modem or an interface card in an acquisition unit that acquires information, an output unit that outputs information, etc. are not included in the functions that are realized by the above program. Further, the number of CPUs that execute this program may be single or plural. That is, centralized processing or distributed processing may be performed.

FIG. 4 is a diagram illustrating functional blocks of the product placement evaluation device 1 based on the embodiment.

Referring to FIG. 4, the memory 4 includes an interest information storage section 401 that stores interest information, a product placement management information storage section 402 that stores information regarding product placement positions, and relationships between product placement positions and products. It includes a product identification information storage section 403 that stores product-related information related to the product, and an image information storage section 404 that stores video data.

The CPU 2 includes an evaluation section 200 that evaluates the arrangement of products, and an image detection section 210 that performs image data analysis processing to detect various information.

The image detection unit 210 stores interest information based on the detected information in the interest information storage unit 401.

The evaluation section 200 includes an interest information acquisition section 201, a related information generation section 202, and a related information output section 207.

The interest information acquisition unit 201 acquires interest information stored in the interest information storage unit 401. The interest information is information indicating that the user has expressed an interest in a product group consisting of a plurality of products, each of which has location information.

The related information generation unit 202 generates related information between products in which the user has shown interest among the product group based on the acquired interest information.

The related information output unit 207 outputs the related information generated by the related information generation unit 202. Note that the related information includes distance information between products.

The related information generation unit 202 includes a correlation degree calculation unit 203, an inter-product distance acquisition unit 204, and an interest table creation unit 205.

The correlation degree calculation unit 203 calculates the correlation degree between products in which the user has shown interest among the product group based on the acquired interest information.

The inter-product distance acquisition unit 204 acquires distance information between products in a group of products in which the user has shown interest.

The interest table creation unit 205 creates an interest table based on the acquired interest information.

Processing of the image detection unit 210 according to the embodiment will be described.

The image detection unit 210 sequentially reads frames of moving image data from the image information storage unit 404. The unit of reading may be one frame or multiple frames. Then, for example, motion detection is performed on the plurality of read frame images to determine whether the user has entered the frame image of the moving image data (that is, whether the user has entered the frame). When a user's frame-in is detected, user identification information (user ID) is automatically assigned. Next, the image detection unit 210 determines whether the user has stopped within the frame image. This can be done, for example, by detecting a moving object that is considered to be a user in a frame image, and detecting it based on the magnitude of the movement. If the user exits the frame image without stopping within the frame image, user identification information (user ID) is assigned, but information indicating that there has been contact with the product, etc. is not acquired. The acquired information is temporarily stored in the memory of the product placement evaluation device 1.

When it is detected that the user has stopped in the frame image, contact with the product is detected from the frame image.

The image detection unit 210 determines whether contact detection (contact event) occurs.

First, here, for example, the movement of the user's hand is detected by skin color, motion detection, etc., and it is determined whether the user's hand has stopped in any area set in the frame image. If it stops in any area, it is determined that the product in that area has been picked up (a contact event has occurred). Then, information indicating that contact has occurred is obtained. Furthermore, the coordinates of the position where the user's hand is stopped are acquired, the area containing these coordinates is detected from the product placement management information storage unit 402, and the "product name" associated with the area is stored in the product identification information. 403.

For example, if it is detected that the user's hand is located in area 101 in FIG. 2 for a certain period of time, image detection unit 210 acquires the product name associated with the area ID corresponding to area 101.

The acquired information is temporarily stored in a memory (not shown). After that, the system will continue to detect the user's hand movements and temporarily store them in memory.

The image detection unit 210 performs the above-described processing until the user leaves the frame image. Frame-out can be detected when an object, possibly a user, moves from inside the frame to outside the frame. Note that the process in which the image detection unit 210 detects contact with a product, etc., described here is an example, and detection may be performed by other processes.

For example, if a person in charge of analysis checks the video data and determines that the user has come into contact with the product, the person in charge of analysis manually enters the fact that the user has come into contact with the product (e.g., the product in the video data (or by manually inputting the product ID) to associate it with the user ID.

Then, at the time when it is detected that the product has gone out of frame, the image detection unit 210 stores information indicating that a contact (event) has been obtained for each product in the memory 4 as interest information for each event. Furthermore, product identification information, which is information for identifying the touched product, may be further included. The products described here may be multiple products or a single product. The product may be, for example, a plurality of products constituting one genre or category. Here, for example, products managed by the same product name, product number, product number, etc. may be considered as the same product. Furthermore, for example, products associated with the same trademark may be considered to be the same product.

The product identification information may be any information as long as it allows one product to be identified from another product. The product identification information is, for example, a product name, a character string, a number, etc. assigned to the product, such as a product code. The product identification information may partially include information indicating attributes of the product (for example, information indicating the manufacturer's name, product genre, category, etc.).

For example, the number of times a user contacts a product may be counted as one time when each user comes into contact with the same product at least once from the time the user stops in the area where the product is placed until the time the user leaves. However, the number of times of contact may be counted. In addition, the number of times a user contacts a product is defined as the case where a user comes into contact with at least one product from the time he or she stops in the area where the product is placed until the time he or she leaves, regardless of the number of times the user contacts the product. It may be counted as one contact. In this case, the number of times a user has contacted the product may be considered as the number of users who have contacted the product. Further, the number of times of contact (number of users) in this case may be particularly used as the number of contacts. The number of times a product has been contacted for each product identification information may be a count of the number of times a product indicated by each product identification information has been contacted. Alternatively, one contact may be counted as one contact when one user comes into contact with at least the product indicated by each product identification information, that is, the number of users who come into contact with the product indicated by each product identification information may be counted.

The related information output unit 207 outputs the related information generated by the related information generation unit 202. The related information output unit 207 may output the related information in any output format. The related information includes distance information between products, and the related information output unit 207 may output the distance information between the products in any output format. For example, the related information output unit 207 may provide nodes corresponding to products and display related information including distance information between products using line segments connecting the nodes. Specifically, the degree of correlation between products in which the user has shown interest may be calculated, and the display form of the line segments connecting nodes may be changed according to the degree of correlation.

The outputs described here include displaying on a display, projecting using a projector, printing on a printer, sending to an external device, storing on a recording medium, and transmitting processing results to other processing devices or programs. This is a concept that includes things like delivery.

The related information output unit 207 can be realized by output device driver software, output device driver software and the output device, or the like.

FIG. 5 is a diagram illustrating the product placement management information storage unit 402 and product identification information storage unit 403 based on the embodiment.

Referring to FIG. 5(A), an example of area management information stored in product placement management information storage section 402 is shown.

In this example, a "region ID" is associated with "coordinates" indicating the region corresponding to the region ID.

As an example, the upper right coordinates (x1 "10", y1 "10") and lower left coordinates (x2 "15", y2 "12") of a rectangular region are associated with the region ID "12345670001". In this example, the range of the rectangular area is indicated by the coordinates of two points, but the present invention is not limited to this, and the coordinates of the rectangular area may be set by four points. Further, a rectangular area may be set based on the center point and distance, and various methods can be adopted for specifying the area. Further, the area is not limited to a rectangular area, and an area of any shape may be set. As another example, the upper right coordinates (x1 "16", y1 "10") and lower left coordinates (x2 "20", y2 "14") of a rectangular area are associated with each other in correspondence to the region ID "12345678901". It is being Corresponding to the region ID "12345678902," the upper right coordinates (x1 "21", y1 "10") and lower left coordinates (x2 "30", y2 "14") of the rectangular region are associated. Corresponding to the region ID "12347658901", the upper right coordinates (x1 "31", y1 "10") and lower left coordinates (x2 "50", y2 "18") of the rectangular region are associated.

In this example, a case will be described in which four area IDs and their corresponding coordinates are associated with each other, but the present invention is not limited to this, and it is naturally possible to provide a plurality of areas.

Referring to FIG. 5(B), an example of product management information stored in product identification information storage section 403 is shown.

In this example, "product name" and "region ID" are associated.

As an example, "area ID (12345670001)" is associated with "product A". Furthermore, “area ID (12345678901)” is associated with “product B”. “Area ID (12345678902)” is associated with “Product C”. “Area ID (12347658901)” is associated with “Product D”.

Thereby, when the user's hand enters the area corresponding to the area ID, it is possible to easily identify which product the user touched.

In this example, a case will be described in which area IDs are set for four products, but the invention is not limited to this, and it is naturally possible to provide a plurality of areas. Further, a region ID may be provided for each product, or a region ID may be set for each of a plurality of products. For example, area IDs may be set for a group of products with the same product name.

FIG. 6 is a diagram illustrating interest information stored in the interest information storage unit 401 based on the embodiment.

Referring to FIG. 6, the interest information stored in interest information storage section 401 includes a plurality of interest data.

The interest data includes an event time, a product name, a user ID, and an interest flag associated with the event time.

Each piece of interest data is created by the image detection unit 210.

Specifically, the image detection unit 210 detects that a contact (event) has been made for each product from the product placement management information storage unit 402 and acquires the product name based on the product identification information storage unit 403. Furthermore, the image detection unit 210 creates interest data that associates a user ID automatically issued for each user with an interest flag. The interest flag is data indicating that the user has shown interest in the product, and is data indicating, for example, that the user has contacted the product.

In this example, a case will be described in which the image detection unit 210 creates interest data for each event and stores it in the interest information storage unit 401.

In this example, we will explain the case where the interest flag is set to "1" when the user comes into contact with the product, but the invention is not limited to this, for example, when the user comes into contact with the product and picks it up. If the purchase is made, the interest flag may be set to "1", or if the purchase is actually made, the interest flag may be set to "1".

Further, the interest data may further include various additional information such as the user's gender and age, detailed product information, and store information.

FIG. 7 is a flowchart diagram illustrating the operation of the product placement evaluation device 1 based on the embodiment. Hereinafter, the operation of the product placement evaluation device 1 will be explained using the flowchart of FIG. 7. Note that here, for example, interest information stored in the interest information storage unit 401 is assumed to be data to be analyzed.

Referring to FIG. 7, interest information acquisition unit 201 acquires interest information stored in interest information storage unit 401 (step S1).

Specifically, the interest information is information indicating that the user has expressed an interest in a product group consisting of a plurality of products, each of which has location information. In this example, the number of people who came into contact with the product will be explained.

The interest table creation unit 205 creates an interest table based on the interest information acquired by the interest information acquisition unit 201 (step S2).

FIG. 8 is a diagram illustrating an interest table based on the embodiment.

Referring to FIG. 8, the interest table is a table that summarizes the relationships between products in which the user has shown interest among a group of products.

Specifically, as an example, products A to K are provided in the row and column directions, and the number of times (number of users) that a user has contacted one set of products is registered.

The interest table creation unit 205 analyzes the plurality of interest data acquired by the interest information acquisition unit 201. Specifically, the interest table creation unit 205 analyzes the contact behavior of the users corresponding to the same user ID with respect to the product among the plurality of interest data including the interest flag "1".

For example, in the example of FIG. 6, the user corresponding to the user ID (“U1”) is in contact with product A, product B, and product C.

Therefore, the interest table creation unit 205 counts up the number of people in the columns for products B and C as combinations of product A and other products in the column for product A. The interest table creation unit 205 counts up the number of people in the column for product A and product C as a combination with product B and other products in the column for product B. The interest table creation unit 205 counts up the number of people in the column for product A and product B as a combination with product C and other products in the column for product C.

Next, in the example of FIG. 6, the user corresponding to the user ID (“U2”) is in contact with product A and product B.

Therefore, the interest table creation unit 205 counts up the number of people in the column for product B as a combination of product A and other products in the column for product A. The interest table creation unit 205 counts up the number of people in the column for product A in the column for product B as a combination of product B and other products.

Next, in the example of FIG. 6, the user corresponding to the user ID (“U3”) is in contact with only product A.

Therefore, the interest table creation unit 205 counts up the number of people in the product A column for the product A column.

The interest table creation unit 205 executes the above process for all interest data stored in the interest information storage unit 401.

Through this process, the interest table shown in FIG. 8 is created as an example.

For example, in the column for product A, the number of users who have come into contact with product A and other products is registered. Specifically, a case is shown in which two users have contacted the combination of product A and product B, and one user has contacted the combination of product A and product D.

Items for product A and product A indicate the number of people who came into contact with product A. The same applies to other items, and items for the same product indicate the number of people who came into contact with the product.

For the product B column, there are 2 users for the combination of product B and product A, 5 users for the combination of product B and product E, and 2 users for the combination of product B and product F. Cases of contact are shown.

In the column for product C, the combination of product C and product J is shown when two users have contacted the combination.

For the column of product D, cases are shown in which one user contacts the combination of product D and product A, and one user contacts the combination of product D and product K.

For the product E column, there are 5 people for the combination of product E and product B, 10 people for the combination of product E and product F, 7 people for the combination of product E and product G, and 7 people for the combination of product E and product G. Cases are shown in which three users contacted the combination of product H and product H, and five users contacted the combination of product E and product K.

For the product F column, there are 2 people for the combination of product F and product B, 10 people for the combination of product F and product E, 8 people for the combination of product F and product G, and 8 people for the combination of product F and product G. For the combination of and product K, the case where one user came into contact is shown.

For the product G column, there are 7 people for the combination of product G and product E, 8 people for the combination of product G and product F, 5 people for the combination of product G and product H, and 5 people for the combination of product G and product G. The case where two users contacted the combination of product I and product I, and the case where two users contacted product G and product K are shown.

For the product H column, cases are shown in which 3 users contacted products H and E, 5 users contacted products H and G, and 1 user contacted products H and I. ing.

For the column of product I, two users have contacted product I and product G, one user has contacted product I and product H, and one user has contacted product I and product K. ing.

In the column for product J, the case where two users have contacted product J and product C is shown.

For the product K column, 1 person for product K and product D, 5 people for product K and product E, 1 person for product K and product F, and 1 person for product K and product G. A case is shown in which two people have contacted product K and one user for product I.

Referring again to FIG. 7, next, the inter-product distance acquisition unit 204 calculates the distance between the products (step S3). Specifically, the inter-product distance acquisition unit 204 calculates the distance between the arranged products. Specifically, a region ID is associated with each product, and the center point of the coordinates of a rectangular region specified by the region ID is calculated. The distance between the center points of the coordinates of the rectangular area corresponding to the products is calculated as the distance between the products.

Therefore, the distance between products placed close together is short, and the distance between products placed far away is long. In this example, a case will be described in which the distance between products in a frame image is used, but the present invention is not limited to this, and the distance between products actually placed on a display shelf may be used.

Next, the correlation degree calculation unit 203 calculates the correlation degree between products (step S4).

FIG. 9 is a diagram illustrating a correlation degree table based on the embodiment.

Referring to FIG. 9, in this example, the correlation degree calculation unit 203 calculates the degree of correlation based on the number of times of interest (for example, the number of people in contact) between products included in the interest information and the distance between the products. Calculate the degree of correlation between products and create a correlation degree table. Specifically, the correlation degree calculation unit 203 calculates the correlation degree using the interest table and the calculated distance between products, and creates a correlation degree table. In this regard, more specifically, the correlation degree calculation unit 203 calculates the product of the number of contacts and the distance as the correlation degree.

For example, in the column for product A, the degree of correlation between product A and other products is registered. Specifically, a case is shown in which the degree of correlation between product A and product B (product of the number of contacts and distance) is calculated as 11.2, and the degree of correlation between product A and product D is calculated as 28.2. ing.

Items for product A and product A indicate the total degree of correlation between product A and other products. The case where the total sum is 39.4 is shown. The same applies to other items, and the sum total of the degree of correlation between the product of interest and other products is shown.

For the product B column, the correlation between product B and product A is 11.2, the correlation between product B and product D is 52.0, and the correlation between product B and product E is 24. 2 is shown. A case is shown in which the total sum is 87.6.

For the column of product C, a case is shown in which the degree of correlation between product C and product J is 52.0. A case is shown in which the total sum is 52.0.

For the product D column, the correlation between product D and product A is 28.2, and the correlation between product D and product K is 21.6. A case is shown in which the total sum is 49.7.

For the product E column, the correlation between product E and product B is 52.2, the correlation between product E and product F is 80.6, and the correlation between product E and product G is 108.7. , the correlation between product E and product H is 84.2, and the correlation between product E and product K is 165.8. A case is shown in which the total sum is 491.5.

For the product F column, the correlation between product F and product B is 24.2, the correlation between product F and product E is 80.6, the correlation between product F and product G is 60, and the correlation between product F and product G is 60. A case is shown in which the degree of correlation between F and product K is 25.5. A case is shown in which the total sum is 190.3.

For the product G column, the correlation between product G and product E is 108.7, the correlation between product G and product F is 60, the correlation between product G and product H is 62.7, and the correlation between product G and product H is 62.7. A case is shown in which the degree of correlation between G and product I is 42.4, and the degree of correlation between product G and product K is 38.4. A case is shown in which the total sum is 312.5.

For the product H column, the correlation between product H and product E is 84.2, the correlation between product H and product G is 62.7, and the correlation between product H and product I is 31.1. The case is shown. A case is shown in which the total sum is 178.0.

For the product I column, the correlation between product I and product G is 42.2, the correlation between product I and product H is 31.1, and the correlation between product I and product K is 30.6. The case is shown. A case is shown in which the total sum is 104.1.

For the column of product J, a case is shown in which the degree of correlation between product J and product C is 52.0. A case is shown in which the total sum is 52.0.

For the product K column, the correlation between product K and product D is 21.6, the correlation between product K and product E is 165.8, and the correlation between product K and product F is 25.5. , the correlation between product K and product G is 38.4, and the correlation between product K and product I is 30.6. A case is shown in which the total sum is 281.9.

Referring again to FIG. 7, next, the related information output unit 207 outputs the related information (step S6). Specifically, the related information output unit 207 outputs related information based on the correlation degree table.

Then, the product placement evaluation device 1 ends the process (end).

FIG. 10 is a diagram illustrating related information output by the related information output unit 207 based on the embodiment.

Referring to FIG. 10, the related information output unit 207 refers to the correlation table to provide a node corresponding to the area associated with the area ID corresponding to each product, and also creates a product by a line segment connecting the nodes. Output relevant information between.

Specifically, a case is shown in which nodes N0 to N10 are provided corresponding to products A to K, respectively. In this example, a case is shown in which area IDs are set for a group of products with the same product name. A node is provided at the center of the area associated with the area ID.

Then, based on the degree of correlation between one product and another product, the density of the color of the line segment connecting the related products is changed. Specifically, in this example, the lines are displayed in gray scale, and line segments with high density have a high degree of correlation, and line segments with low density have a low degree of correlation.

In this example, the degree of correlation between the line segment connecting node N4 of product E and node N10 of product K is displayed as the highest and darkest. On the other hand, the degree of correlation between the line segment connecting node N0 of product A and product B is the smallest and displayed faintly.

The degree of correlation is high when the number of users who have come into contact with the products is relatively large and the distance between the products is long. Therefore, by calculating the degree of correlation, it is possible to evaluate the placement of products that the user is interested in relatively.

As an example, it is possible to estimate that a line segment with a high degree of correlation indicates that it is desirable to change the arrangement relationship between products. For example, it is possible to reduce the degree of correlation by arranging product E and product K such that the distance between the products is shortened. For example, by setting the placement relationship between products so that the degree of correlation is small, users can easily pick up products that they are likely to be interested in, making it more convenient for users to make purchases.

The product placement evaluation device 1 acquires interest information indicating that a user is interested in a product group consisting of a plurality of products, each of which has location information, and based on the acquired interest information. The system generates related information between the products that the user is interested in among the product groups, and outputs the generated related information. The related information includes distance information between products. Since the related information includes distance information between products, it is possible to evaluate the placement of products that the user is interested in based on the output related information.

The related information output unit 207 sets the size of the node provided corresponding to each product to be proportional to the number of people who have come into contact with the product. Specifically, the number of people who came into contact with product A was 10. The number of people who came into contact with product B was 10. The number of people who came into contact with product C was 5. The number of people who came into contact with product D was three. The number of people who came into contact with product E was 40. The number of people who came into contact with Product F was 35. The number of people who came into contact with product G was 30. The number of people who came into contact with product H was 15. The number of people who came into contact with Product I was 8. The number of people who came into contact with Product J was 6. The number of people who came into contact with product K is 20.

The size of the node is set according to the number of people in contact. In this respect, the number of people who have come into contact with product E is the largest, and the node is set to be larger according to the number of people. It is possible to understand at a glance which product the user is interested in based on the display format.

Furthermore, the related information output unit 207 sets the color of the node. Specifically, the color of a node is set according to the sum of the correlation degrees of line segments connected to the node.

Specifically, the total correlation degree of node N0 of product A is 39.4. The total correlation degree of node N1 of product B is 87.6. The total correlation degree of node N2 of product C is 52.0. The total correlation degree of node N3 of product D is 49.8. The total correlation degree of node N4 of product E is 491.5. The sum of the correlation degrees of node N5 of product F is 190.3. The total correlation degree of node N6 of product G is 312.2. The sum of the correlation degrees of node N7 of product H is 178.0. The total correlation degree of node N8 of product I is 104.1. The total correlation degree of node N9 of product J is 52.0. The total correlation degree of node N10 of product K is 281.9.

The color of the node is set according to the total sum of the correlation degrees. At this point, the total sum of product E is the largest, and the color of the node is set according to the value of the total sum. Specifically, the color of the node is indicated by the density of hatching, and the density of hatching is set to be high.

With this display format, it is possible to understand at a glance which product has a higher total correlation degree than other products.

As an example, it can be estimated that a node with a large total correlation degree indicates that it is desirable to change the arrangement relationship between products. For example, it is possible to set the optimal product placement position for product E by changing the position to a position where the degree of correlation can be reduced in relation to other products. For example, by arranging products in such a way that the total sum of correlations is small, users can easily pick up products that they are likely to be interested in, making it more convenient for users to make purchases.

In addition, in this example, we explained the case where the display form of line segments between nodes and the color of nodes is changed to output related information between products that the user has shown interest in, but it is also possible to use either one of them. It is.

FIG. 11 is another diagram illustrating the related information output by the related information output unit 207 based on the embodiment.

Referring to FIG. 11, a case is shown in which related information is output and displayed in a superimposed manner on a frame image.

The output display allows the user to easily understand at a glance which product placement relationships should be focused on, and it is possible to easily evaluate the placement of products that the user is interested in.

(Other forms)
In the above embodiment, the case where interest information acquired using moving image data captured by the video camera 2301 is used has been described as an example, but in this embodiment, what kind of interest information is used? The information may be information acquired by other means.

In the embodiment described above, an image processing unit (not shown) performs pattern matching or the like from the moving image data stored in the image information storage unit 404 to obtain information regarding products arranged on a product shelf or the like. This information may be used to create a table in the product identification information storage section 403 and area management information in the product placement management information storage section 402. For example, an image processing unit (not shown) uses information that associates product identification information prepared in advance in the memory 4 with image information indicating the appearance of the product, such as shape and color, to create an image that matches this image information. The area may be detected by pattern matching in an image of a product shelf, and coordinate information indicating the matching area and product identification information such as a product name corresponding to this image may be obtained. Alternatively, pattern matching may be performed using image information such as a product logo on a product label instead of using image information showing the appearance of the product.

In the above embodiment, a behavior detection device (not shown) that detects the user's behavior using a sensor using a laser or the like is used, and the information that this behavior detection device acquires and outputs using the sensor is used. This may be used to determine whether or not the user has touched the product. As a behavior detection device that detects user behavior using a sensor using a laser or the like, multiple sensors are placed around the area where the user's behavior is to be detected, and the output of the sensors is processed. It detects the user's position or changes in position, automatically assigns an ID number, etc. to the user, and can obtain the user's position coordinates in real time.

As an example, we will explain the case where interest information is created using video image data, but the invention is not limited to this. For example, if an RFID tag is attached to a product or the like, a change in the position indicated by this RFID tag is performed. may be detected by a position detection unit (not shown) equipped with an RFID tag reader/writer or the like to determine which product has been contacted by the user (picked up by the user). Changes in the position of the RFID tag can be detected, for example, by adjusting the positions of multiple antennas that read information from the RFID tag, or by detecting from the strength of signals output by the RFID tag that are received by multiple antennas. .

In addition, a vibration sensor, etc. that is associated with the product identification information should be placed at the location where the product is placed, and when this vibration sensor vibrates, it will be detected that the user has touched the product. You can also do it.

Furthermore, in this example, a case has been described in which the user's hand touching a product is detected and the detection result is stored as interest data in the interest information storage unit 401. The detection result may be stored in the interest information storage unit 401 as interest data.

Specifically, an image processing unit (not shown) or the like identifies the user's face direction and gaze direction from the video data stored in the image information storage unit 404. The image detection unit 210 detects which product the user is paying attention to based on the information. When the image detection unit 210 detects that the user has visually focused on the product for a predetermined period of time or longer, the image detection unit 210 may store the detection result in the interest information storage unit 401 as interest data.

The image information storage unit 404 stores moving image data that is an image taken of a situation in which a plurality of products are being sold. The moving image data is, for example, an image shot with a camera such as a video camera. Note that the moving image data may be images captured by multiple cameras. The moving image data is, for example, an image of a sales floor or display shelf where products are arranged. The moving image data may be an image captured by a surveillance camera or the like in the store. The images here are usually moving images, but may also be continuous still images acquired at fixed or irregular predetermined timings. The file format of the image does not matter. The process by which moving image data is stored in the image information storage unit 404 does not matter. For example, moving image data may be accumulated via a recording medium, moving image data transmitted via a communication line etc. may be accumulated, and moving image data output from a camera etc. may be accumulated. May be accumulated.

In the above embodiment, a case has been described in which the density of the line segment color connecting related products is changed based on the degree of correlation between one product and another product. It is possible to adopt any form. For example, the thickness of the line segment may be changed instead of the density of the line segment color, or the shape of the line segment may be changed to a broken line or the like. Alternatively, the display form may be changed using a plurality of colors based on changes in the degree of correlation.

Although we have explained the case where the color of the node corresponding to a certain product is changed depending on the total correlation between that product and another product, this display format is just an example, and various display formats can be adopted. It is. For example, you may change the thickness of the outer line of the node instead of the color of the node, you may change the shape of the outer line of the node to a broken line, or you may change the shape of the node. Alternatively, the display form may be changed using a plurality of colors based on a change in the total correlation degree.

In addition, in this example, we have explained a case in which the placement relationship between products is such that the degree of correlation is small, but the arrangement is not limited to this, and may be changed depending on the product layout situation, store situation, user preference, etc. The arrangement relationship between the products may be such that the degree of correlation increases.

In the above embodiments, each process (each function) may be realized by being centrally processed by a single device (system), or may be realized by being distributed by multiple devices. Good too.

(Additional note)
The embodiment described above includes the following technical idea.

[Additional note 1]
A product placement evaluation program that is executed by a computer (2),
The computer includes:
a step (S1) of acquiring interest information indicating that the user has expressed interest in a product group consisting of a plurality of products, each of which has location information;
generating related information between products in which the user has shown interest among the product group based on the acquired interest information (S2 to S4);
and a step (S6) of outputting the related information,
A product placement evaluation program that executes a process in which the related information includes distance information between products.

[Additional note 2]
Product placement evaluation according to appendix 1, wherein the step of generating the related information includes a step (S4) of calculating a degree of correlation between products in which the user has shown interest among the product groups based on the acquired interest information. program.

[Additional note 3]
Note that the step of calculating the degree of correlation between the products calculates the degree of correlation between the products based on the number of times of interest between the products included in the interest information and the distance between the products. Product placement evaluation program described in 2.

[Additional note 4]
The product placement evaluation program according to appendix 3, wherein the number of interests is the number of users who have contacted one product set.

[Additional note 5]
The step of outputting the related information includes:
displaying line segments indicating relationships between the products;
The product placement evaluation program according to any one of Supplementary Notes 3 to 4, including the step of changing the display form of the line segment based on the calculated degree of correlation between the products.

[Additional note 6]
The product placement evaluation program according to any one of Supplementary Notes 3 to 5, wherein the step of generating the related information includes the step of calculating a total sum of degrees of correlation between the products.

[Additional note 7]
The step of outputting the related information includes:
displaying a plurality of nodes respectively corresponding to the plurality of products;
The product placement evaluation program according to appendix 6, comprising the step of changing the display form of each node based on the calculated sum of correlations between the products.

[Additional note 8]
The step of outputting the related information includes the product arrangement according to any one of Supplementary Notes 1 to 7, wherein the related information is outputted in a superimposed manner on an image obtained by capturing a product group consisting of the plurality of products. Evaluation program.

[Additional note 9]
a step (S1) of acquiring interest information indicating that the user has expressed interest in a product group consisting of a plurality of products, each of which has location information;
generating related information between products in which the user has shown interest among the product group based on the acquired interest information (S2 to S4);
and a step (S6) of outputting the related information,
In the product placement evaluation method, the related information includes distance information between products.

[Additional note 10]
a storage unit (401) that stores interest information indicating that a user has expressed an interest in a product group consisting of a plurality of products, each of which has location information;
a related information generation unit (202) that generates related information between a plurality of products in which the user has shown interest among the product group based on interest information stored in the storage unit;
an output unit (207) that outputs the related information;
A product placement evaluation device in which the related information includes distance information between products.

[Additional note 11]
a storage unit (401) that stores interest information indicating that a user has expressed an interest in a product group consisting of a plurality of products, each of which has location information;
a related information generation unit (202) that generates related information between a plurality of products in which the user has shown interest among the product group based on interest information stored in the storage unit;
an output unit (207) that outputs the related information;
The related information includes distance information between products in a product placement evaluation system.

The embodiments disclosed this time should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is indicated by the claims rather than the above description, and it is intended that all changes within the meaning and range equivalent to the claims are included.

1 Product placement evaluation device, 2 CPU, 4 Memory, 6 Communication unit, 200 Evaluation unit, 201 Interest information acquisition unit, 202 Related information generation unit, 203 Correlation degree calculation unit, 204 Inter-product distance acquisition unit, 205 Interest table creation unit , 207 related information output unit, 210 image detection unit, 401 interest information storage unit, 402 product placement management information storage unit, 403 product identification information storage unit, 404 image information storage unit, 2300 store, 2301 video camera, 2302 display shelf.

Claims (11)

A product placement evaluation program executed by a computer,
acquiring interest information indicating that the user has expressed interest in a product group consisting of a plurality of products, each of which has location information;
generating related information between products in which the user has shown interest among the product group based on the acquired interest information;
outputting the related information;
The related information is a product placement evaluation program including distance information between products. 2. The product placement evaluation program according to claim 1, wherein the step of generating the related information includes the step of calculating a degree of correlation between products in which the user has shown interest among the product group based on the acquired interest information. In the step of calculating the degree of correlation between the products, the degree of correlation between the products is calculated based on the number of times of interest between the products included in the interest information and the distance between the products. Product placement evaluation program described in Section 2. 4. The product placement evaluation program according to claim 3, wherein the number of times of interest is the number of users who have contacted one product set. The step of outputting the related information includes:
displaying line segments indicating relationships between the products;
4. The product placement evaluation program according to claim 3, further comprising the step of changing the display form of the line segment based on the calculated degree of correlation between the products. 4. The product placement evaluation program according to claim 3, wherein the step of generating the related information includes the step of calculating a total sum of degrees of correlation between the products. The step of outputting the related information includes:
displaying a plurality of nodes respectively corresponding to the plurality of products;
7. The product placement evaluation program according to claim 6, further comprising the step of changing the display form of each of the nodes based on the calculated sum of correlations between the products. 2. The product placement evaluation program according to claim 1, wherein the step of outputting the related information outputs the related information superimposed on an image of a product group made up of the plurality of products. acquiring interest information indicating that the user has expressed interest in a product group consisting of a plurality of products, each of which has location information;
generating related information between products in which the user has shown interest among the product group based on the acquired interest information;
outputting the related information;
In the product placement evaluation method, the related information includes distance information between products. a storage unit that stores interest information indicating that a user is interested in a product group consisting of a plurality of products, each of which has location information;
a related information generation unit that generates related information between a plurality of products in which the user has shown interest among the product group based on interest information stored in the storage unit;
and an output unit that outputs the related information,
A product placement evaluation device in which the related information includes distance information between products. a storage unit that stores interest information indicating that a user is interested in a product group consisting of a plurality of products, each of which has location information;
a related information generation unit that generates related information between a plurality of products in which the user has shown interest among the product group based on interest information stored in the storage unit;
and an output unit that outputs the related information,
A product placement evaluation system in which the related information includes distance information between products.

Images