Sales information management device, sales information management device control method, sales information management system and program

Abstract

To provide a sales information management device, control method therefor, sales information management system, and program, which enable appropriate estimation of a customer group and sales information on products purchased by the customer group.SOLUTION: A sales information management device 30 is provided, comprising a control unit 301 for performing processing to manage sales information of a ticket vending machine 10. The control unit 301 is configured to acquire sales information on each ticket issued by the ticket vending machine 10, estimate the time when customers moved away from the ticket vending machine 10 based on captured images of the surroundings of the ticket vending machine, and estimate a customer group and sales information corresponding to the customer group on the basis of the time when customers moved away and the time when tickets were issued.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a sales information management device that manages sales information based on ticketing, a control method for the sales information management device, a sales information management system that manages sales information based on ticketing, and a program that causes a computer to execute functions for managing sales information based on ticketing. [Background technology]

[0002] Currently, ticket vending machines for purchasing predetermined products are installed in restaurants, train stations, stores, etc. For example, in a restaurant, a customer operates the ticket vending machine to select the product they want, and the ticket vending machine issues a voucher corresponding to the selected item. The customer can use the issued voucher to receive food and drink.

[0003] In this case, it would be preferable for the installer of the ticket machine to be able to understand what kinds of products groups of customers, such as families, married couples, or other couples, tend to purchase depending on the season and time of day. This would allow the installer to appropriately develop a product strategy for their store and efficiently develop their business.

[0004] The following Patent Document 1 describes a group attribute estimation method for estimating the group attributes of customers who purchase a product. In this method, changes in the distance between customers in real space are detected from images captured inside a store. Based on these changes, customers who form the same group are estimated. Then, attributes are estimated for each customer in the group, and the group attributes are estimated based on the estimated attributes. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 4198951 Summary of the Invention [Problem to be solved by the invention]

[0006] However, with the estimation method described above, when a store is crowded, for example, and customers from another group are approaching one group, the method may mistakenly estimate that the customers from the other group are customers from the first group.

[0007] In view of the above, the present invention aims to provide a sales information management device, a control method for a sales information management device, a sales information management system, and a program that can accurately estimate sales information for a group of customers and the products purchased by that group. [Means for solving the problem]

[0008] A first aspect of the present invention relates to a sales information management device that includes a control unit that acquires sales information for each ticket issued by a ticket vending machine, estimates the timing at which customers dispersed from in front of the ticket vending machine based on captured images of the vicinity of the ticket vending machine, and estimates a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the ticket.

[0009] According to the sales information management device of this aspect, a customer group and sales information corresponding to that group are estimated based on the timing when customers leave the ticket vending machine and the timing when tickets are issued by the ticket vending machine. Therefore, even when a group of customers is close to another group, such as when the store is crowded, it is unlikely that customers from the other group will be mistakenly estimated as customers from the first group. Therefore, it is possible to accurately estimate a customer group and sales information for products purchased by that group.

[0010] In the sales information management device according to this embodiment, the control unit can be configured to estimate that customers who dispersed within a predetermined time before and after the timing of the ticket issuance belong to the same group, and to estimate the sales information of the ticket issuance that estimates the group as the sales information corresponding to the group.

[0011] Typically, a customer who has performed the operation to issue a ticket will leave the ticket vending machine once the ticket has been issued. Furthermore, if a customer who has performed the operation to issue a ticket is present in front of the ticket vending machine together with a customer accompanying them, the customer may leave the ticket vending machine once the ticket has been issued, or, once they have decided which item they wish to purchase, they may inform the customer who performed the ticket issuing operation of the item and leave the ticket vending machine before the ticket is issued. Therefore, by assuming that customers who leave within a predetermined time before and after the timing of ticket issuance belong to the same group, as in the above configuration, it is possible to accurately identify customers who belong to the same group. Furthermore, by assuming that the sales information of this ticket is the sales information of the group, it is possible to accurately link the group and the sales information.

[0012] In the sales information management device according to this embodiment, the control unit can be configured to, when multiple tickets are issued within a predetermined time interval or less, estimate that customers who are dispersed within the period between the first and last of the multiple tickets and within a predetermined time before and after that period belong to the same group, and to estimate the sales information of the multiple tickets that have been used to estimate the group as the sales information corresponding to that group.

[0013] When customers in the same group purchase multiple products, multiple ticket issuing operations may be performed. In this case, these ticket issuing operations are performed continuously in a certain flow, and the time interval between these ticket issuing operations is significantly shorter than when tickets are issued by customers from different groups. Therefore, if multiple ticket issuing operations are performed within a predetermined time interval, these multiple ticket issuing operations can be assumed to be performed by the same group. Therefore, as described above, by assuming that discrete customers within the period between the first and last ticket issuing times of multiple ticket issuing operations performed within a predetermined time interval or within a predetermined time before and after the first and last tickets are the same group, it is possible to accurately identify customers belonging to the same group. Furthermore, by assuming the sales information of these multiple ticket issuing operations as sales information corresponding to the group, it is possible to accurately estimate the sales information of the products purchased by the group.

[0014] In the sales information management device according to this aspect, the predetermined time before the predetermined time before and after can be set to start immediately after the last discrete timing of the customer in the previous group estimation.

[0015] With this configuration, even if customers from the same group leave the ticket vending machine relatively early before the ticket issuance timing, the separated customers can be included in the group. Also, since the predetermined time period before the start of the group starts from the time when the customers last left in the previous group estimation, customers from other groups will not be included in the group. Therefore, customers in the same group can be more accurately estimated.

[0016] In the sales information management device according to this aspect, the predetermined time before and after the event may be set to a fixed time that is set in advance, thereby simplifying the processing.

[0017] In the sales information management device of this embodiment, the control unit can be configured to infer that customers who disperse from in front of the ticket vending machine in response to ticket issuance belong to the same group, and to infer the sales information of the ticket issuance that inferred the group as the sales information corresponding to that group.

[0018] Usually, customers disperse from in front of the ticket vending machine after issuing a ticket. Therefore, in most cases, customers who disperse from in front of the ticket vending machine in response to issuing a ticket can be assumed to be part of the same group. With the above configuration, it is assumed that customers who disperse from in front of the ticket vending machine in response to issuing a ticket are part of the same group. Therefore, customers in the same group can be accurately assumed. Furthermore, the sales information of the ticket that inferred this group is inferred as the sales information corresponding to the group. Therefore, the sales information of the group can be accurately inferred. Therefore, with the above configuration, it is possible to accurately infer the group of customers and the sales information of the products purchased by the group.

[0019] In this configuration, the control unit can be configured to include sales information for at least one other ticket issuance in the sales information corresponding to the group if there is at least one other ticket issuance between the first ticket issuance timing that estimates the group and the second ticket issuance timing immediately before that, among a series of ticket issuance timings at which customers disperse from in front of the ticket machine in response to ticket issuance.

[0020] According to this configuration, the sales information for other tickets that are likely to be included in the sales information for the group estimated based on the first ticket issuance timing is further included in the sales information for the group, thereby enabling more accurate estimation of the sales information for the group.

[0021] In addition, in this configuration, the control unit can be configured to include another customer in the group if the other customer leaves in front of the ticket vending machine between the timing a predetermined time before the oldest ticket issuance corresponding to the group and the first ticket issuance timing.

[0022] According to this configuration, other customers who are likely to be included in the group estimated based on the first ticket issuance timing are also included in the group, thereby making it possible to more accurately estimate the customers included in the group.

[0023] In the sales information management device according to this embodiment, the control unit may be configured to estimate, based on the captured image, other customers who have been facing the customer estimated to be in the same group for a predetermined period of time or more, or other customers who have been in contact with the customer estimated to be in the same group for a predetermined period of time or more, and include the estimated customers in the group.

[0024] According to this configuration, other customers who are likely to be included in the group can be included in the group, and the customers included in the group can be estimated more accurately.

[0025] In the sales information management device according to this aspect, the control unit may be configured to exclude customers who have dispersed without remaining in front of the ticket vending machine from the estimation targets for the group.

[0026] This configuration makes it possible to prevent customers who are not in the same group but simply pass by the ticket vending machine from being assumed to be customers in the same group, thereby enabling more accurate estimation of customers who are in the same group.

[0027] In the sales information management device according to this aspect, the control unit may be configured to estimate attributes of the group based on the captured image.

[0028] In this way, by further estimating the attributes of a group, the sales information of the group can be further linked to the attributes of the group, and therefore, information on the relationship between the group attributes and the sales information can be provided to the manager of the store where the ticket vending machine is installed.

[0029] In this case, the control unit can be configured to estimate the attributes of each customer included in the group based on the captured image, and to estimate the attributes of the group based on the estimated attributes of each customer and the number of customers included in the group.

[0030] In this way, the attributes of a group (family, married couple, friends, single, etc.) can be estimated accurately by estimating the attributes of the group based on the attributes of each customer in the group (gender, age, etc.) and the number of customers in the group.

[0031] The sales information management device according to this aspect includes a memory unit that stores information, and the control unit can be configured to store the attributes of the group and the sales information of the group in association with each other in the memory unit.

[0032] According to this configuration, by appropriately reading out the group attributes and sales information of the group stored in the memory unit from the memory unit, it is possible to provide the manager of the store, etc. with information on the relationship between the group attributes and sales information in the store, etc. where the ticket vending machine is installed.

[0033] The control unit may also be configured to extract facial information of each customer included in the group based on the captured image, and store the extracted facial information in the memory unit in association with at least one of the group and the sales information.

[0034] According to this configuration, it is possible to provide information such as the repeat customer rate and the product purchasing tendency of the same customer to the manager of a store or the like based on the face information stored in the storage unit.

[0035] In the sales information management device according to this aspect, the sales information may include the time of sale, the product sold, and the sales quantity, thereby providing the manager of the store or the like with useful information indicating the relationship between customer attributes and product purchases.

[0036] A second aspect of the present invention relates to a control method for a sales information management device. The control method according to this aspect acquires sales information for each ticket issued by a ticket vending machine, estimates the timing at which customers dispersed in front of the ticket vending machine based on captured images around the ticket vending machine, and estimates a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the ticket.

[0037] A third aspect of the present invention relates to a sales information management system. The sales information management system according to this aspect includes a ticket vending machine, a camera that captures images of the vicinity of the ticket vending machine, and a control unit that manages sales information of the ticket vending machine. The control unit acquires sales information for each ticket issued by the ticket vending machine, estimates the timing when customers dispersed from in front of the ticket vending machine based on the images captured by the camera, and estimates a customer group and sales information corresponding to that group based on the timing of the dispersion and the timing of the issuance of the ticket.

[0038] A fourth aspect of the present invention is a program that causes a computer to perform the following functions: acquire sales information for each ticket issued at a ticket vending machine; estimate the timing at which customers dispersed from in front of the ticket vending machine based on captured images of the area around the ticket vending machine; and estimate a group of customers and sales information corresponding to that group based on the timing of the dispersion and the timing of the issuance of the tickets.

[0039] According to the second to fourth aspects of the present invention, the same effects as those of the first aspect can be achieved. [Effects of the Invention]

[0040] As described above, according to the present invention, it is possible to provide a sales information management device, a control method for a sales information management device, a sales information management system, and a program that are capable of accurately estimating sales information for a group of customers and products purchased by the group.

[0041] The effects and significance of the present invention will become more apparent from the following description of the embodiments, however, the embodiments shown below are merely examples of how the present invention can be implemented, and the present invention is not limited to the embodiments described below. [Brief explanation of the drawings]

[0042] [Figure 1] FIG. 1 is a diagram showing the configuration of a sales information management system according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the configuration of the sales information management system according to the first embodiment. [Figure 3] Fig. 3(a) is a flowchart showing a process of estimating customer departure timing according to embodiment 1. Fig. 3(b) is a flowchart showing a process of linking attributes of groups of customers who visit a store with sales information of products purchased by each group according to embodiment 1. [Figure 4] FIG. 4 is a time chart schematically illustrating an example of processing for linking customer groups with sales information according to the first embodiment. [Figure 5] FIG. 5 is a time chart schematically illustrating another example of the process of linking customer groups with sales information according to the first embodiment. [Figure 6] Fig. 6(a) is a flowchart showing a group attribute estimation process according to embodiment 1. Fig. 6(b) is a diagram showing a state in which sales information and group attributes are linked according to embodiment 1. Fig. 6(c) is a diagram showing a state in which a group is linked with attributes and face information of customers included in the group according to embodiment 1. [Figure 7] FIG. 7 is a time chart schematically illustrating an example of processing for linking a customer group with sales information according to a modification of the first embodiment. [Figure 8] FIG. 8 is a flowchart showing a process for linking attributes of groups of customers who visit a store with sales information of products purchased by each group, according to the second embodiment. [Figure 9] FIG. 9 is a time chart schematically illustrating an example of processing for linking customer groups with sales information according to the second embodiment. [Figure 10] FIG. 10 is a flowchart schematically illustrating an example of processing for linking a customer group with sales information according to the first modification of the second embodiment. [Figure 11] FIG. 11 is a time chart schematically illustrating an example of processing for linking a customer group with sales information according to the first modification of the second embodiment. [Figure 12] FIG. 12 is a flowchart schematically illustrating an example of processing for linking a customer group with sales information according to the second modification of the second embodiment. [Figure 13] FIG. 13 is a time chart schematically illustrating an example of processing for linking a customer group with sales information according to the second modification of the second embodiment. [Figure 14] FIG. 14 is a time chart schematically illustrating another example of the process of linking a customer group with sales information according to the second modification of the second embodiment. [Figure 15]FIG. 15 is a time chart schematically showing an example of processing for linking customer groups with sales information according to another modified example. [Figure 16] FIG. 16 is a diagram showing a state in which sales information and face information of each group are linked together according to yet another modification. DETAILED DESCRIPTION OF THE INVENTION

[0043] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0044] <Embodiment 1> FIG. 1 is a diagram showing the configuration of a sales information management system 1 according to the first embodiment.

[0045] The sales information management system 1 includes a ticket vending machine 10, a camera 20, and a sales information management device 30 (hereinafter referred to as "management device 30").

[0046] The ticket vending machine 10 is installed in a store such as a restaurant. A customer visiting the store purchases a voucher for a product of their choice from the ticket vending machine 10. The camera 20 captures images of the area around the ticket vending machine 10. The camera 20 captures images of a predetermined area in front of the ticket vending machine 10 from behind the ticket vending machine 10. The management device 30 is connected to the ticket vending machine 10 and the camera 20 so that they can communicate with each other. The management device 30 is installed in an office or the like of the store where the ticket vending machine 10 is installed. The management device 30 may also be installed in a facility other than a store. In this case, the management device 30 communicates with the ticket vending machine 10 and the camera 20 via a public communication network such as the Internet.

[0047] Sales information based on ticket issuance is transmitted from ticket vending machine 10 to management device 30 at a predetermined timing, along with time information indicating the timing of ticket issuance. In addition, images captured by camera 20 are transmitted to management device 30 along with time information (time stamp). Management device 30 stores the sales information and time information received from ticket vending machine 10, and the captured images and time information received from camera 20. Management device 30 is configured, for example, by a server computer.

[0048] When a store has multiple sets of ticket vending machines 10 and cameras 20, management device 30 may be communicatively connected to each set of ticket vending machines 10 and cameras 20. In this case, management device 30 stores the sales information and time information received from each set of ticket vending machines 10 and cameras 20, as well as the captured images and time information.

[0049] The ticket vending machine 10 has a roughly cubic housing that forms the outer shell of the device. A touch panel type operation and display unit 11 is disposed on the upper front surface of the ticket vending machine 10. As will be described later with reference to FIG. 2, the operation and display unit 11 is configured such that a transparent touch sensor 107 is disposed on the upper surface of a display 106. The display 106 is, for example, a liquid crystal display, and the touch sensor 107 is, for example, a pressure-sensitive (resistive film) touch pad. However, the configuration of the operation and display unit 11 is not limited to this, and the touch sensor 107 may be, for example, a capacitance type touch pad.

[0050] A banknote deposit / withdrawal slot 12 for depositing and withdrawing banknotes, a coin deposit slot 13 for depositing coins, a coin withdrawal slot 14 for withdrawing coins, and a ticket issuing slot 15 for issuing coupons are arranged in the center of the front of the ticket vending machine 10. In addition, a human presence sensor is arranged in the ticket vending machine 10. The human presence sensor detects when a customer is standing in front of the ticket vending machine 10.

[0051] When a human presence sensor detects that a customer is standing in front of the ticket vending machine 10, options are displayed on the operation and display unit 11. Here, options for food and drink that the store can provide are displayed. The customer touches the desired option from among the multiple options displayed on the operation and display unit 11. At this time, the customer can select multiple options at once. When the customer has finished selecting the options, they touch the done button.

[0052] The customer then deposits bills or coins in the amount required to purchase the selected item into bill deposit / withdrawal slot 12 or coin deposit slot 13. This causes a voucher corresponding to the selected item to be issued from ticket issuing slot 15. If the customer has selected multiple items, multiple vouchers will be issued from ticket issuing slot 15. If there is change, the bills or coins corresponding to the change are dispensed from bill deposit / withdrawal slot 12 or coin dispensing slot 14. This completes one step of the transaction.

[0053] FIG. 2 is a block diagram showing the configuration of the sales information management system 1. As shown in FIG.

[0054] The ticket vending machine 10 includes a control unit 101, a memory unit 102, a banknote processing unit 103, a coin processing unit 104, a ticket processing unit 105, a display 106, a touch sensor 107, a speaker 108, and a communication unit 109.

[0055] The control unit 101 includes an arithmetic processing circuit such as a CPU (Central Processing Unit), and controls each unit according to a program stored in the storage unit 102. The storage unit 102 includes storage media such as a ROM (Read Only Memory), a RAM (Random Access Memory), and a hard disk, and stores the programs executed by the control unit 101 and various data. The storage unit 102 is also used as a work area when the control unit 101 performs control.

[0056] The banknote processing unit 103 comprises a banknote storage unit for storing banknotes of various denominations, a transport unit for transporting the banknotes, and a denomination discrimination unit for discriminating the denomination of the transported banknotes, and transports banknotes between the banknote storage unit and the banknote deposit / withdrawal slot 12 (see FIG. 1) under the control of the control unit 101. The coin processing unit 104 comprises a coin storage unit for storing coins of various denominations, a transport unit for transporting the coins, and a denomination discrimination unit for discriminating the denomination of the transported coins, and transports coins between the coin storage unit and the coin deposit slot 13 and coin withdrawal slot 14 (see FIG. 1) under the control of the control unit 101.

[0057] The ticket issuing processing unit 105 includes a strip generating unit that generates paper strips and a printing unit that prints on the strips, and sends the vouchers with the names of food and drink items printed on the strips by the printing unit to the ticket issuing port 15.

[0058] The display 106 and the touch sensor 107 constitute the operation display unit 11 in FIG. 1. The touch sensor 107 is a transparent film-like member that is overlaid on the display surface of the display 106. The display 106 displays predetermined information under the control of the control unit 101. The touch sensor 107 outputs coordinate information of the position touched by the operator to the control unit 101. The speaker 108 outputs predetermined sound under the control of the control unit 101. The output sound is output to the outside from a sound output window (not shown) formed on the housing of the ticket vending machine 10. The communication unit 109 communicates with the management device 30 under the control of the control unit 101.

[0059] Camera 20 includes control unit 201, imaging unit 202, and communication unit 203. Control unit 201 is configured, for example, by a microcomputer or the like, and controls each unit according to a program stored in an internal memory. Imaging unit 202 includes an imaging lens and an imaging element, and captures an image of the field of view under the control of control unit 201. Communication unit 203 communicates with management device 30 under the control of control unit 201.

[0060] The management device 30 includes a control unit 301, a storage unit 302, and a communication unit 303. The control unit 301 includes a processing circuit such as a CPU, and controls each unit according to a program stored in the storage unit 302. The storage unit 302 includes storage media such as a ROM, RAM, and hard disk, and stores the programs executed by the control unit 301 and various data. The storage unit 302 is also used as a work area when the control unit 301 performs control.

[0061] In addition, the storage unit 302 stores a face recognition engine that the control unit 301 uses to perform face recognition from captured images. The storage unit 302 also stores an attribute estimation engine that the control unit 301 uses to estimate customer attributes such as the age and gender of each customer from each piece of face information extracted by the face recognition engine.

[0062] The control unit 101 of the ticket vending machine 10 periodically transmits sales information based on each ticket issued during the period temporarily stored in the memory unit 102 and time information indicating the timing of ticket issuance to the management device 30 via the communication unit 109. In addition, the control unit 201 of the camera 20 transmits, for example, imaging information captured continuously during the store's business hours and time information that is a timestamp of the captured images to the management device 30 via the communication unit 203.

[0063] Control unit 301 of management device 30 stores in memory unit 302 the sales information and time information received from ticket vending machine 10 via communication unit 303, and the captured images and time information received from camera 20 via communication unit 303. For example, after business hours for one day have ended, control unit 301 of management device 30 uses the sales information and time information for that day stored in memory unit 302, and the captured images and time information for that day, to link the attributes of groups of customers who visited the store that day with the sales information of the products purchased by each group.

[0064] FIG. 3(a) is a flowchart showing a process for estimating the discrete timing of a customer.

[0065] The control unit 301 executes face recognition processing on one day's worth of captured images stored in the storage unit 302 (S101) and identifies faces included in the captured images (S102). The control unit 301 tracks the identified faces in the series of captured images (S103) and estimates whether the tracked faces stayed in front of the ticket vending machine 10 and then dispersed from in front of the ticket vending machine 10 (S104).

[0066] In step S104, the control unit 301 determines whether the face being tracked has stopped for a predetermined period of time or more (for example, several seconds or more) in an area set in the captured image that corresponds to the area in front of the ticket vending machine 10, and then moved out of (left) the captured image (the field of view of the camera 20). If the determination is YES, the control unit 301 presumes that the face being tracked stayed in front of the ticket vending machine 10 and then dispersed away from in front of the ticket vending machine 10 (S104: YES), and if the determination is NO, the control unit 301 presumes that the face being tracked did not stay in front of the ticket vending machine 10 but dispersed away from in front of the ticket vending machine 10 (simply crossed in front of the ticket vending machine 10) (S104: NO).

[0067] If the determination in step S104 is YES, the control unit 301 stores facial information of the tracked face and discrete timings of the face in the storage unit 302. The stored facial information is obtained, for example, as a difference between feature amounts at multiple sample points of a preset standard facial image and feature amounts at corresponding sample points of the tracked facial image. The discrete timings are obtained, for example, as the times at which the tracked face moves out of (exits) the captured image. Alternatively, the discrete timings may be the times at which the face being tracked moves out of an area set in the captured image that corresponds to the area in front of the ticket vending machine 10. Alternatively, a matrix may be estimated from the captured image, and the times at which the face being tracked moves out of the matrix may be determined as the discrete timings.

[0068] If the determination in step S104 is NO, that is, if the tracked face disperses without remaining in front of the ticket vending machine 10, the control unit 301 ends the processing for the tracked face without storing the facial information and dispersal timing for that face in the memory unit 302. The control unit 301 executes the processing of FIG. 3(a) for all faces identified in the captured images for one day that are the processing target. As a result, the facial information and dispersal timing of customers who remained in front of the ticket vending machine 10 on that day are stored in the memory unit 302.

[0069] FIG. 3(b) is a flowchart showing the process of linking the attributes of groups of customers who visited a store with sales information on products purchased by each group.

[0070] The processing in Figure 3(b) is performed on the facial information and discrete timings of each customer stored in step S105 of Figure 3(a), and the sales information and time information (ticket issuance timing) for that day stored.

[0071] The control unit 301 references the time information (ticket issuance timing) of one day's worth of sales information stored in the memory unit 302 (S111). The control unit 301 groups tickets issued consecutively at a predetermined time interval or less as tickets issued by the same group of customers (S112). The predetermined time interval in step S112 is set to a time interval (for example, several tens of seconds) that can be expected when customers in the same group issue tickets sequentially. The control unit 301 estimates that customers (face information) that include discrete timings either in the period from the earliest ticket to the latest ticket issuance or in a predetermined time before or after this period belong to the same group (S113).

[0072] The control unit 301 estimates that the sales information of the tickets grouped in step S112 is the sales information of the customers estimated to be in the same group in step S113 (S114). The control unit 301 estimates the attributes of the group (family, married couple, couple, single, etc.) based on the facial information of the customers estimated to be in the same group (S115). The control unit 301 associates the estimated attributes of the group with the sales information estimated for the group in step S114 and stores them in the storage unit 302 (S116). Furthermore, the control unit 301 associates the attributes and facial information of the customers included in the group with each other and stores them in the storage unit 302 (S117).

[0073] In step S112, if the predetermined ticket issuance timing is not consecutive with other ticket issuance timings within a predetermined time interval, the control unit 301 presumes that only tickets issued at that timing are issued by the same group. In this case, in step S113, the control unit 301 presumes that customers (face information) whose discrete timings are included in any of the predetermined times before and after the predetermined ticket issuance timing are the same group.

[0074] FIG. 4 is a time chart that schematically shows an example of the process of linking customer groups with sales information according to the process of FIG. 3(b).

[0075] The top row of FIG. 4 shows the timing of ticket issuance. Here, tickets TC1 to TC3 are issued. The second row from the top of FIG. 4 shows the timing when customer faces are recognized from the captured image. Here, the faces of customers C1 to C7 are recognized and tracked. The third row from the top of FIG. 4 shows the timing when customers C1 to C7 leave the ticket vending machine 10. Customers C1 and C2 leave the ticket vending machine 10 substantially simultaneously, and customer C3 leaves the ticket vending machine 10 alone. Furthermore, customers C4 to C7 leave the ticket vending machine 10 substantially simultaneously.

[0076] The second row from the bottom in Figure 4 shows customers who are presumed to be in the same group, and the bottom row in Figure 4 shows the ticket (sales information) linked to each group. Here, the sales information for ticket TC2 is linked to the group of customers C1 and C2, and the sales information for ticket TC1 and TC3 is linked to the group of customers C3 to C7. This linking is performed as follows using the processing in Figure 3(b).

[0077] First, the time interval ΔT10 between issuing TC1 and TC3 is shorter than the predetermined time interval in step S112 of Figure 3(b). Therefore, in step S112, issuing TC1 and TC3 are grouped as tickets issued by the same group. Since the time interval between issuing TC2 and TC3 is longer than the predetermined time interval, issuing TC2 and TC3 are not grouped.

[0078] Next, predetermined times ΔT11 and ΔT12 before and after the grouped tickets TC1 and TC2 are set, and customers whose discrete timings fall within either the time interval ΔT10 or the predetermined times ΔT11 and ΔT12 before and after are presumed to be in the same group (step S113 in FIG. 3(b)). The predetermined times ΔT11 and ΔT12 are set to, for example, predetermined fixed times (e.g., several tens of seconds). Here, because the discrete timings of customer C3 and customers C4 to C7 are included in the predetermined times ΔT11 and ΔT12 before and after, these customers C3 to C7 are presumed to be in the same group.

[0079] Since ticket TC2 is not grouped with other tickets, predetermined times ΔT11 and ΔT12 are set before and after the issuance timing of ticket TC2. Here, since the discrete timings of customers C1 and C2 are included in the predetermined time ΔT12 on the back side, it is assumed that customers C1 and C2 are in the same group.

[0080] Once customers are grouped in this way, the sales information of the tickets that estimated the group is estimated as the sales information corresponding to that group (step S114 in FIG. 3(b)). In this case, the tickets estimated for the group of customers C3 to C7 are tickets TC1 and TC3, so the sales information of tickets TC1 and TC3 is linked to the group of customers C3 to C7. Also, the ticket estimated for the group of customers C1 and C2 is ticket TC2, so the sales information of ticket TC2 is linked to the group of customers C1 and C2.

[0081] Unlike the example in Figure 4, there may be cases where the time interval ΔT10 set by ticket issuing TC1 and TC3 and the predetermined times ΔT11 and ΔT12 before and after it contain only the discrete timing of one customer. Similarly, there may be cases where the predetermined times ΔT11 and ΔT12 before and after it set by ticket issuing TC2 contain only the discrete timing of one customer. In these cases, it is estimated that a group is made up of a single customer, and sales information is linked to this group as described above.

[0082] 4, the predetermined time ΔT11 and the predetermined time ΔT12 are shown as having the same length, but the predetermined time ΔT11 and the predetermined time ΔT12 do not necessarily have to be the same length. For example, the predetermined time ΔT11 set on the front side may be set longer than the predetermined time ΔT12 set on the rear side.

[0083] Furthermore, the predetermined time periods ΔT11 and ΔT12 before and after the predetermined time periods ΔT11 and ΔT12 do not necessarily have to be fixed times that have been set in advance. For example, as shown in Fig. 5, the predetermined time period ΔT11 before the predetermined time periods ΔT11 and ΔT12 may start immediately after the last discrete timing of the customer in the previous group estimation, that is, immediately after the latest discrete timing of customers C1 and C2 in the example of Fig. 5. This makes it possible to prevent customers associated with the same group from being overlooked.

[0084] FIG. 6(a) is a flowchart showing the group attribute estimation process in step S115 of FIG. 3(b).

[0085] The control unit 301 references the facial information of customers included in the same group (S131). The control unit 301 estimates the attributes (gender, age) of each customer based on the referenced facial information (S132). The control unit 301 estimates the attributes (gender, age) of each customer in the group and the number of customers (number of facial information pieces) included in the group (S133). The control unit 301 estimates the attributes of the group (family, married couple, couple, single, etc.) based on the estimated attributes (gender, age) of each customer in the group and the number of customers in the group (S134).

[0086] For example, if a group includes only male and female customers of parent generation age and customers of child generation age, the control unit 301 estimates the attribute of the group as family. If a group includes only male and female customers of the same age and at least one customer of the same age (regardless of gender), and the age difference between these customers is within a range that would allow them to be considered parent and child, the control unit 301 estimates the attribute of the group as family. If a group includes only male and female customers of parent generation age, the control unit 301 estimates the attribute of the group as married couple. If a group includes only male and female customers of younger generation age, the control unit 301 estimates the attribute of the group as couple. If a group includes multiple males or multiple females of younger generation age, the control unit 301 estimates the attribute of the group as friends. If a group includes only one customer, the control unit 301 estimates the attribute of the group as single. The control unit 301 estimates the attribute of the group as described above based on group attribute estimation rules previously stored in the storage unit 302.

[0087] FIG. 6(b) is a diagram showing a state in which sales information and group attributes are linked together through the process of step S116 in FIG. 3(b).

[0088] As shown in Figure 6(b), the sales information includes the date and time of sale, the product sold, and the price. The sales information also includes the sales quantity of each product. In the linkage in the top row of Figure 6(b), the products sold are one each of products A, B, C, and D. In the linkage in the fifth row from the top of Figure 6(b), the products sold are two products G and one product H.

[0089] FIG. 6(c) is a diagram showing a state in which a group is linked to the attributes and face information of customers included in the group through the process of step S117 in FIG. 3(b).

[0090] As shown in Figure 6(c), customer attributes include gender, age, and number of people. Customer attributes are linked to the group attributes of the corresponding group. In addition, facial information of customers who make up each group is linked to each customer.

[0091] The information in FIGS. 6(b) and 6(c) is stored in the storage unit 302 of the management device 30 in steps S116 and S117 of FIG. 3(b). A store manager can refer to the information in FIGS. 6(b) and 6(c), for example, via a terminal capable of communicating with the management device 30. In this case, the terminal may display sales information aggregated for each group attribute for a predetermined period (day of the week, week, month, season, etc.) or time period. For example, the total amount may be displayed for each group attribute. Alternatively, the number of purchases or the ratio of purchase amounts for each product may be displayed for a group attribute selected by the manager. Furthermore, for a product selected by the manager, the terminal may display the tendency of the group attribute that purchased the product (for example, the number of purchases or the ratio of purchases for each group attribute).

[0092] Furthermore, the repeat rate of the same customer over a predetermined period may be displayed based on the facial information. Furthermore, the type of group in which the same customer visits the store may be displayed. For example, the ratio of the number of visits by the same customer who visits the store as a single person to the number of visits by other customers over a predetermined period may be displayed. Furthermore, for a group of customers who visit the store as a single person multiple times over a predetermined period, the ratio of the number of times this group of customers purchased the same product to the total number of visits by this group of customers may be displayed.

[0093] The control unit 301 of the management device 30 may be capable of executing the tallying and editing functions for causing the terminal to perform the above-described display. Such functions may be included in the above-described program stored in the storage unit 302 of the management device 30.

[0094] <Effects of the First Embodiment> According to the first embodiment, the following effects can be achieved.

[0095] In the configuration of FIG. 2, the control unit 301 of the management device 30 acquires sales information for each ticket issued by the ticket vending machine 10 via the communication unit 303, estimates the timing at which customers dispersed from in front of the ticket vending machine 10 based on captured images around the ticket vending machine 10 using the process of FIG. 3(a), and estimates the customer group and sales information corresponding to that group based on the timing of dispersion and the timing of ticket issuance using the process of FIG. 3(b). This prevents customers from being mistakenly assumed to be members of the first group, even when a store is crowded and other groups of customers are close to one another. This allows for accurate estimation of customer groups and sales information for products purchased by the group.

[0096] As shown in Fig. 3(b), the control unit 301 estimates that customers who are separated within a predetermined time before and after the timing of ticket issuance belong to the same group (S113), and estimates the sales information of the ticket that represents the estimated group as the sales information corresponding to the group (S114). For example, in the example of Fig. 4, the control unit 301 estimates that customers C1 and C2 who are separated within predetermined times ΔT11 and ΔT12 before and after the timing of ticket issuance TC2 belong to the same group, and estimates the sales information of ticket issuance TC2 as the sales information corresponding to the group.

[0097] Typically, a customer who has performed the operation to issue a ticket will leave the ticket vending machine once the ticket has been issued. Furthermore, if a customer who has performed the operation to issue a ticket is present in front of the ticket vending machine together with a customer accompanying them, the customer may leave the ticket vending machine once the ticket has been issued, or, once they have decided which item they wish to purchase, they may inform the customer who performed the ticket issuing operation of the item and leave the ticket vending machine before the ticket is issued. Therefore, by estimating that customers who leave within a predetermined time before and after the timing of ticket issuance belong to the same group, it is possible to accurately estimate which customers belong to the same group. Furthermore, by estimating the sales information of this ticket as the sales information of the group, it is possible to accurately link the group and the sales information.

[0098] As shown in Fig. 3(b), when multiple tickets are issued within a predetermined time interval, the control unit 301 estimates that customers who are dispersed within the period between the timing of the first and last issuance of these multiple tickets and within a predetermined time before and after the timing of the first and last issuance of these multiple tickets belong to the same group (S113), and estimates the sales information of the multiple tickets that have been estimated as this group as sales information corresponding to the group (S114). For example, in the example of Fig. 4, when multiple tickets TC1 and TC3 are issued within a predetermined time interval, the control unit 301 estimates that customers C3 to C7 who are dispersed within a time interval ΔT10 between the timing of the first and last issuance of these multiple tickets TC1 and TC3 and within predetermined times ΔT11 and ΔT12 before and after the time interval belong to the same group, and estimates the sales information of these multiple tickets TC1 and TC3 as sales information corresponding to the group.

[0099] When customers in the same group purchase multiple products, multiple ticket issuing operations may be performed. In this case, these ticket issuing operations are performed continuously in a certain flow, and the time interval between these ticket issuing operations is significantly shorter than when tickets are issued by customers from different groups. Therefore, if multiple ticket issuing operations are performed within a predetermined time interval, these multiple ticket issuing operations can be assumed to be performed by the same group. Therefore, as described above, by assuming that discrete customers within the period between the first and last ticket issuing times of multiple ticket issuing operations performed within a predetermined time interval or within a predetermined time before and after the first and last tickets are the same group, it is possible to accurately identify customers belonging to the same group. Furthermore, by assuming the sales information of these multiple ticket issuing operations as sales information corresponding to the group, it is possible to accurately estimate the sales information of the products purchased by the group.

[0100] As shown in Figure 5, the predetermined time ΔT11 before and after ΔT12 can be set to start immediately after the last customer separation timing in the previous group estimation. This allows customers from the same group to be included in the group even if they separate from the ticket vending machine 10 relatively earlier than the ticket issuance timing. Furthermore, because the predetermined time ΔT11 before the start of the group starts immediately after the last customer separation timing in the previous group estimation, customers from other groups will not be included in the group. This allows for more accurate estimation of customers in the same group.

[0101] As shown in Fig. 4, the predetermined time before and after may be set to a fixed time that is set in advance, which can simplify the processing.

[0102] As shown in FIG. 3(a), the control unit 301 sets customers who stay in front of the ticket vending machine 10 and then disperse as targets for inference of the group (S105). This makes it possible to prevent customers who are not in the group but simply pass by the ticket vending machine from being inferred as customers of the same group. This makes it possible to more accurately infer customers who are in the same group.

[0103] As shown in Fig. 3(b), the control unit 301 estimates the attributes of the group based on the captured image (S115). By estimating the attributes of the group in this way, the sales information of the group can be further linked to the attributes of the group. Therefore, in a store or the like where the ticket vending machine 10 is installed, information on the relationship between the group attributes and the sales information can be provided to the manager of the store or the like.

[0104] 6(a), the control unit 301 estimates the attributes of each customer included in the group based on the captured image (S132), and estimates the attributes of the group based on the estimated attributes of each customer and the number of customers included in the group (S134). In this way, by estimating the attributes of the group (family, married couple, couple, friends, single, etc.) based on the attributes of each customer included in the group (gender, age, etc.) and the number of customers included in the group, the attributes of the group can be accurately estimated.

[0105] 3(b), the control unit 301 associates the group attributes with the sales information of the group and stores them in the storage unit 302 (S116). As a result, by appropriately reading out the group attributes and sales information of the group stored in the storage unit 302 from the storage unit 302 as described above, it is possible to provide the manager of the store or the like with information on the relationship between the group attributes and sales information in the store or the like where the ticket vending machine 10 is installed.

[0106] 3(b), the control unit 301 associates the facial information of each customer included in the group with the group and stores it in the storage unit 302 (S117). As a result, based on the facial information stored in the storage unit 302, information such as the repeat customer rate and the product purchasing tendency of the same customer can be provided to the manager of the store, etc.

[0107] As shown in Figure 6(b), the sales information may include the time of sale (sale date and time), the product sold, and the sales quantity. This allows the store manager to receive useful information showing the relationship between customer attributes and product purchases.

[0108] <Example of change> In the process of Figure 3(b), when multiple tickets are issued within a specified time interval, these tickets are grouped and then customers are grouped based on these tickets. However, it is also possible to first group customers whose tickets are issued at discrete times within a specified time before and after each ticket, and then group tickets issued within the specified time interval together with that group.

[0109] FIG. 7 is a time chart that schematically shows an example of processing for linking customer groups with sales information in this case.

[0110] In this case, customers C4 to C7 who are separated within a predetermined time ΔT11 and ΔT12 before and after the issuance of ticket TC1 are grouped, and customer C3 who is separated within a predetermined time ΔT11 and ΔT12 before and after the issuance of ticket TC3 is grouped. Then, because the time interval ΔT10 between ticket TC1 and ticket TC3 is less than the predetermined time interval, customers C4 to C7 and customer C3 who are grouped for ticket TC1 and ticket TC3, respectively, are grouped as being in the same group, and furthermore, the sales information of ticket TC1 and ticket TC3 is linked as the sales information of this group.

[0111] 3(b), this process also estimates that customers dispersed within the time interval ΔT10 between the first and last issuances of multiple tickets TC1 and TC3 issued within a predetermined time interval or less, and within the predetermined times ΔT11 and ΔT12 before and after that, belong to the same group, and the sales information of the multiple tickets TC1 and TC3 that estimated that group is estimated as the sales information corresponding to that group. Thus, customer groups and their sales information can be accurately estimated.

[0112] <Embodiment 2> In the above embodiment 1, customers whose discrete timings are within a specified time before and after the timing of ticket issuance are presumed to be in the same group, but in embodiment 2, customers who dispersed in response to ticket issuance, i.e., customers who dispersed within a specified time from the timing of ticket issuance, are presumed to be in the same group.

[0113] FIG. 8 is a flowchart showing the process of linking the attributes of groups of customers who visit a store with sales information on products purchased by each group.

[0114] In the second embodiment, the process of Fig. 8 is executed instead of the process of Fig. 3(b). The other configurations and controls in the second embodiment are the same as those in the first embodiment.

[0115] The control unit 301 sequentially references the time information (ticket issuance timing) of one day's worth of sales information stored in the memory unit 302 (S201). The control unit 301 compares the referenced ticket issuance timing with the discrete timing stored in step S105 of FIG. 3(a) and determines whether any customers have dispersed in response to the issuance of a ticket at this ticket issuance timing (S202). Specifically, the control unit 301 determines whether any discrete timing is included in the period from this ticket issuance timing until a predetermined time has elapsed. This predetermined time is set based on the time that can normally be expected for a group of customers to disperse after completing the ticket issuance operation. The predetermined time can be set to, for example, several tens of seconds.

[0116] If there are no customers who have dispersed in response to the issuance of tickets at this ticket issuance timing (S202: NO), the control unit 301 determines that there are no customers who will form a group at this ticket issuance timing, and ends the processing for this ticket issuance timing.

[0117] On the other hand, if there are customers who dispersed in response to the issuance of this ticket at this timing (S202: NO), the control unit 301 estimates that face information (customers) containing the dispersed timings within the period from this ticket issuance timing until a predetermined time has elapsed are included in the same group (S203), and further estimates the sales information of the ticket issuance timing as the sales information of the group (S204). Then, the control unit 301 estimates the attributes of the group (S205), associates the estimated group attributes with the sales information of the group, and stores them in the storage unit 302 (S206). Furthermore, the control unit 301 associates the group, customer attributes, and face information with each other and stores them in the storage unit 302 (S207). The processes of steps S205 to S207 are the same as the processes of steps S115 to S117 in FIG. 3(b), respectively.

[0118] When the process for this ticket issuance timing is completed in this way, the control unit 301 refers to the next ticket issuance timing and executes the processes from step S201 for this ticket issuance timing. The control unit 301 repeatedly executes the same process for the ticket issuance timing for one day.

[0119] FIG. 9 is a time chart that schematically shows an example of processing for linking customer groups with sales information when the processing of FIG. 8 is performed.

[0120] In this example, the period ΔT20 from the issuance of ticket TC1 until a predetermined time has elapsed includes the discrete timings of customers C4 to C7. Therefore, customers C4 to C7 are presumed to be included in the same group, and the sales information of ticket TC1 is linked to this group. Furthermore, the period ΔT20 from the issuance of ticket TC2 until a predetermined time has elapsed includes the discrete timings of customers C1 and C2. Therefore, customers C1 and C2 are presumed to be included in the same group, and the sales information of ticket TC2 is linked to this group.

[0121] In contrast, the period ΔT20 from the issuance of ticket TC3 until a predetermined time has elapsed does not include any discrete timing of customers. Therefore, a customer group is not estimated for ticket TC3, and the sales information for ticket TC3 is not linked to any group.

[0122] <Effects of the Second Embodiment> Usually, once a ticket has been issued, customers leave the ticket vending machine 10. Therefore, in most cases, customers who leave the ticket vending machine in response to ticket issuance can be assumed to be part of the same group. According to the processing of the second embodiment, as described above, customers who leave the ticket vending machine in response to ticket issuance can be assumed to be part of the same group. Therefore, customers in the same group can be accurately assumed. Furthermore, the sales information of the ticket that has been issued to infer this group is assumed to be the sales information corresponding to that group. Therefore, the sales information of that group can be accurately estimated. Therefore, the processing of the second embodiment can also accurately infer the group of customers and the sales information of the products purchased by that group.

[0123] <Change example 1> According to the processing of the second embodiment, as shown in the example of Fig. 9, no customer group is estimated for ticket TC3, and the sales information for ticket TC3 is not linked to any group. However, because customers C1 and C2 are separated in response to ticket TC2, it is highly likely that ticket TC3 was issued by a group of customers who dispersed in response to the subsequent ticket TC1.

[0124] Therefore, in modified example 1, if there is at least one other ticket issued between the first ticket issuance timing at which the group is estimated and the second ticket issuance timing immediately before that among a series of ticket issuance timings at which customers disperse from in front of the ticket vending machine 10 in response to ticket issuance, the sales information of that other ticket is included in the sales information corresponding to the group estimated by the first ticket issuance timing.

[0125] FIG. 10 is a time chart schematically showing an example of processing for linking customer groups with sales information according to the first modification.

[0126] Fig. 10 shows only steps S204 and S205 of the flowchart in Fig. 8, and the other steps are omitted. Steps other than steps S204 and S205 are the same as those in Fig. 8. In modified example 1, step S211 is added between steps S204 and S205. In step S211, the control unit 301 adds sales information for tickets issued after the previous ticket issuance for the group to the sales information for that group.

[0127] FIG. 11 is a time chart that schematically shows an example of processing for linking customer groups with sales information when the processing of FIG. 10 is performed.

[0128] The example in Figure 11 is the same as the example in Figure 9. Therefore, as in the case of Figure 9, dispersed customers C4 to C7 are grouped according to issuance TC1, and the sales information of issuance TC1 is linked to this group. Also, dispersed customers C1 and C2 are grouped according to issuance TC2, and the sales information of issuance TC2 is linked to this group.

[0129] Furthermore, in this example, there is at least one other issuance TC3 between issuance TC1 (first issuance timing) and the immediately preceding issuance TC2 (second issuance timing) (period ΔT30). Therefore, in step S211 of Fig. 10, the control unit 301 includes the sales information of the other issuance TC3 in the sales information corresponding to the group of customers C4 to C7. As a result, the sales information corresponding to the group of customers C4 to C7 becomes the sales information for issuance TC1 and TC3.

[0130] According to the process of the first modification, the sales information of the group of customers C4 to C7 is further included in the sales information of the group of customers C4 to C7, which is likely to have been issued by the group of customers C4 to C7. This allows the sales information of the group to be estimated more accurately.

[0131] <Change example 2> According to the processing of the above-described modified example 1, customer C3 is not included in any group, as shown in the example of Fig. 11. However, customer C3 is scattered around ticket TC3, which was estimated to have been issued by the group of customers C4 to C7 by the processing of step S211 of Fig. 10, and therefore is more likely to be included in the group of customers C4 to C7 than in the group of customers C1 and C2.

[0132] Therefore, in modified example 2, if another customer leaves in front of the ticket vending machine 10 between the timing a predetermined time before the oldest ticket issued among those corresponding to the group and the timing of the referenced ticket issuance, the other customer is included in the group.

[0133] FIG. 12 is a time chart schematically showing an example of processing for linking customer groups with sales information according to the second modification.

[0134] Fig. 12 shows only steps S204, S205, and S211 of the flowchart in Fig. 10, and omits the other steps. Steps other than steps S204, S205, and S211 are the same as those in Fig. 10. In Modification 2, step S212 is added between steps S211 and S205.

[0135] In step S212, if another customer leaves the front of the ticket vending machine 10 between the timing a predetermined time (for example, several tens of seconds) before the oldest ticket issued among those corresponding to the group and the timing of the ticket being referenced, the control unit 301 includes the other customer in the group.

[0136] FIG. 13 is a time chart that schematically shows an example of processing for linking customer groups with sales information when the processing of FIG. 12 is performed.

[0137] The example in Fig. 13 is the same as the example in Fig. 11. Therefore, similar to the case in Fig. 11, dispersed customers C4 to C7 are grouped according to the issuance of ticket TC1, and the sales information of the issuance of tickets TC1 and TC3 is linked to this group.

[0138] Furthermore, in this example, another customer C3 is scattered between the timing that predates the oldest ticket TC3 among the tickets TC1 and TC3 corresponding to the group of customers C4 to C7 by a predetermined time ΔT21 and the referenced ticket issuance timing (ticket TC1). Therefore, in step S212 of Fig. 12, the control unit 301 includes the other customer C3 in the group of customers C4 to C7. As a result, customers C3 to C4 are grouped, and the sales information of tickets TC1 and TC3 is linked to this group.

[0139] According to the process of the second modification, customer C3, who is likely to be included in the group of customers C4 to C7, is further included in the group of customers C4 to C7, which allows for more accurate estimation of the customers included in the group.

[0140] In addition, as in the example of Figure 14, if there are no other tickets issued in the period ΔT30 between issuance TC1 and issuance TC2, in step S212 of Figure 12, the control unit 301 will include another customer C3 in the group of customers C4 to C7 if the other customer C3 is separated between the timing going back a predetermined time ΔT21 from issuance TC1 and the timing of issuance of the referenced ticket (issuance TC1).

[0141] <Change example 3> In the second embodiment, whether or not customers have dispersed in response to the issuance of tickets is estimated based on whether or not customers have dispersed within a predetermined time period since the issuance of tickets. However, the method for estimating whether or not customers have dispersed in response to the issuance of tickets is not limited to this.

[0142] For example, customers who dispersed at substantially the same time can be presumed to be in the same group, and if the timing of these customers' dispersion falls within the period from the immediately preceding ticket issuance timing until a predetermined time has elapsed, it can be presumed that these customers dispersed in response to the issuance of a ticket at this timing, and the group can be linked to the sales information for that ticket.

[0143] Alternatively, customers who dispersed at substantially the same time can be presumed to be in the same group, and if the timing of ticket issuance falls within the period from the latest timing of dispersal of these customers to a timing a predetermined time prior, it can be presumed that these customers dispersed in response to the issuance of a ticket at this timing, and the group can be linked to the sales information of the ticket.

[0144] <Other change examples> In the above-described first and second embodiments and their modifications, the attributes of each customer are estimated based on the facial information of each customer acquired from a captured image, but the attributes of each customer may also be estimated based on the appearance or physical characteristics of each customer, such as clothing or height. In this case, the attributes of each customer may be estimated by taking into account the appearance or physical characteristics in addition to the facial information.

[0145] Furthermore, the voice of a customer standing in front of the ticket vending machine 10 may be picked up by a microphone, and the attributes of each customer or group may be estimated by further taking into account this voice (conversation, voiceprint, etc.).

[0146] In the above-described first and second embodiments and their modifications, customer groups are estimated based on the timing at which customers dispersed from in front of the ticket vending machine. However, customer groups may also be estimated by taking into account factors such as the distance between customers, contact, and the orientation of the customer's face. For example, in the example shown in FIG. 4, customer C3 is added to the group of customers C4 to C7 when the timing at which another customer C3 dispersed falls within a predetermined time ΔT11 or ΔT21 from the earliest ticket issuance timing T3 corresponding to the group. However, as shown in FIG. 15, customer C8 may also be added to the group of customers C3 to C7 when customer C3 and customer C8 continue to be in contact with each other, or when customer C8's face faces face each other for a predetermined time or longer. This allows other customers who are likely to be included in the group to be included in the group, thereby more accurately estimating the customers included in the group.

[0147] In this configuration, contact between customers may be estimated based on, for example, whether or not the bodies of customers being tracked overlap using facial images. Furthermore, customers who are added to a group due to contact or face orientation do not necessarily have to be customers not included in any group, but may also be customers estimated to be included in another group.

[0148] Furthermore, the method of estimating a customer group and sales information corresponding to that group based on the timing of dispersal and the timing of ticket issuance is not limited to the methods described in the first and second embodiments and the modified example.

[0149] For example, customers who dispersed at substantially the same time may be assumed to belong to the same group, and ticket sales information whose ticket issuance timing is within a predetermined time from the dispersion timing of the earliest dispersed customer within the group may be linked to the group. In this case, ticket sales information whose ticket issuance timing is within a predetermined time from the dispersion timing of the latest dispersed customer within the group may further be linked to the group.

[0150] In addition, a customer group and the ticket issuance (sales information) corresponding to that group may be estimated by AI (artificial intelligence) processing of the timing of ticket issuance during a predetermined period and the timing of customer separation. Also, the attributes of the group may be estimated by AI processing of the attributes and number of customers included in the group.

[0151] The types and contents of group attributes are not limited to those described above. For example, group attributes such as brothers and sisters may be added based on the similarity of facial information. Furthermore, group attributes may include age groups and the number of people in each age group.

[0152] Furthermore, in the above-mentioned embodiments 1 and 2 and their modified examples, the facial information of the customers included in the group is linked to the group as shown in FIG. 6(c), but the facial information of the customers included in each group may also be linked to the sales information of each group as shown in FIG.

[0153] In the first and second embodiments and their modifications, the sales information and captured images for one day are processed, but the processing targets are not limited to this. For example, the sales information and captured images for one week may be processed, or the sales information and captured images for a predetermined time period over one month may be processed. The manager of the store or the like may be able to specify these processing targets via the terminal.

[0154] Furthermore, the configurations of the ticket vending machine 10, the camera 20, and the management device 30 are not limited to those shown in the above embodiment. For example, although the above describes a type of ticket vending machine 10 that allows multiple tickets to be purchased at once, the ticket vending machine 10 may also be a type that allows tickets to be purchased one by one.

[0155] Furthermore, in the above-mentioned embodiments 1 and 2 and their modified examples, the sales information management system 1 is configured by separately arranging the ticket vending machine 10, the camera 20, and the management device 30, but the ticket vending machine 10, the camera 20, and the management device 30 do not necessarily have to be separately arranged.

[0156] For example, instead of camera 20, a camera that captures images of the area in front of ticket vending machine 10 may be mounted on ticket vending machine 10. In this case, the image captured by the camera and time information (timestamp) are transmitted from ticket vending machine 10 to management device 30 along with sales information and time information (ticket issuance timing). Alternatively, the functions of management device 30 may be mounted on ticket vending machine 10, and management device 30 may be omitted. In this case, ticket vending machine 10 is also used as a sales information management device. The image captured by camera 20 and time information (timestamp) are transmitted from camera 20 to ticket vending machine 10. Alternatively, the functions of camera 20 and management device 30 may be mounted on ticket vending machine 10, and camera 20 and management device 30 may be omitted from the sales information management system 1.

[0157] In addition, the embodiments of the present invention can be modified as appropriate within the scope of the claims. [Explanation of symbols]

[0158] 1 Sales information management system 10 Ticket Machine 20 Camera 30 Sales information management device 301 Control Unit 302 Storage section

Claims

1. A control unit is provided, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, Customers who have dispersed within a predetermined time before and after the timing of issuing the tickets are assumed to be in the same group; A sales information management device that estimates the sales information of the ticket issuance that estimates the group as the sales information corresponding to the group.

2. A control unit is provided, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, If multiple tickets are issued within a predetermined time interval, customers who are separated within a period between the first and last tickets issued and within a predetermined time before and after the period are assumed to be in the same group. A sales information management device that estimates the sales information of the plurality of tickets that have estimated the group as the sales information corresponding to the group.

3. 3. The sales information management device according to claim 1, wherein the predetermined time before the predetermined time before and after the predetermined time starts immediately after the last discrete timing of the customer in the previous group estimation.

4. 4. The sales information management device according to claim 1, wherein the predetermined time before and after the event is a fixed time that is set in advance.

5. A control unit is provided, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, Customers who disperse from in front of the ticket vending machine in response to ticket issuance are assumed to be in the same group; A sales information management device that estimates the sales information of the ticket issuance that estimates the group as the sales information corresponding to the group.

6. The control unit A sales information management device as described in claim 5, wherein if at least one other ticket is issued between a first ticket issuance timing at which the group is estimated and a second ticket issuance timing immediately preceding that, among a series of ticket issuance timings at which customers disperse from in front of the ticket machine in response to ticket issuance, sales information for the other ticket issuance is included in the sales information corresponding to the group.

7. The control unit A sales information management device as described in claim 6, wherein if another customer leaves in front of the ticket machine between a timing that is a predetermined time before the oldest ticket issuance corresponding to the group and the first ticket issuance timing, the other customer is included in the group.

8. The control unit estimates, based on the captured image, other customers who face the customer estimated to be in the same group for a predetermined period of time or more, or other customers who have been in contact with the customer estimated to be in the same group for a predetermined period of time or more, and includes the estimated customers in the group.

9. The sales information management device according to claim 1 , wherein the control unit excludes customers who do not stay in front of the ticket vending machine and who have dispersed from the group of customers to be estimated.

10. The sales information management device according to claim 1 , wherein the control unit estimates an attribute of the group based on the captured image.

11. The sales information management device according to claim 10, wherein the control unit estimates attributes of each customer included in the group based on the captured image, and estimates attributes of the group based on the estimated attributes of each customer and the number of customers included in the group.

12. A storage unit for storing information is provided, The sales information management device according to claim 10 , wherein the control unit causes the storage unit to store the attributes of the groups and the sales information of the groups in association with each other.

13. 13. The sales information management device according to claim 12, wherein the control unit extracts facial information of each customer included in the group based on the captured image, and stores the extracted facial information in the storage unit in association with at least one of the group and the sales information.

14. The sales information management device according to claim 1 , wherein the sales information includes a sales time, a sold product, and a sold quantity.

15. A method for controlling a sales information management device, comprising: Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; In estimating the group and the sales information, Customers who have dispersed within a predetermined time before and after the timing of issuing the tickets are assumed to be in the same group; A control method for a sales information management device, which estimates the sales information of the ticketing that estimates the group as the sales information corresponding to the group.

16. A control method for a sales information management device, comprising: Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; In estimating the group and the sales information, If multiple tickets are issued within a predetermined time interval, customers who are separated within a period between the first and last tickets issued and within a predetermined time before and after the period are assumed to be in the same group. A control method for a sales information management device that estimates the sales information of the plurality of tickets that have been estimated as the sales information corresponding to the group.

17. A control method for a sales information management device, comprising: Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on a captured image of the vicinity of the ticket vending machine; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; In estimating the group and the sales information, Customers who disperse from in front of the ticket vending machine in response to ticket issuance are assumed to be in the same group; A control method for a sales information management device, which estimates the sales information of the ticketing that estimates the group as the sales information corresponding to the group.

18. Ticket machines and a camera that captures an image of the vicinity of the ticket vending machine; a control unit that manages sales information of the ticket vending machine, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on the image captured by the camera; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, Customers who have dispersed within a predetermined time before and after the timing of issuing the tickets are assumed to be in the same group; A sales information management system that estimates the sales information of the ticketing that estimates the group as the sales information corresponding to the group.

19. A ticket vending machine; a camera that captures an image of the vicinity of the ticket vending machine; a control unit that manages sales information of the ticket vending machine, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on the image captured by the camera; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, If multiple tickets are issued within a predetermined time interval, customers who are separated within a period between the first and last tickets issued and within a predetermined time before and after the period are assumed to be in the same group. A sales information management system that estimates the sales information of the multiple tickets that have been estimated for the group as the sales information corresponding to the group.

20. A ticket vending machine; a camera that captures an image of the vicinity of the ticket vending machine; a control unit that manages sales information of the ticket vending machine, The control unit Acquire sales information for each ticket issued by the ticket vending machine, The timing at which customers dispersed from in front of the ticket vending machine is estimated based on the image captured by the camera; Inferring a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the tickets; The control unit, in estimating the group and the sales information, Customers who disperse from in front of the ticket vending machine in response to ticket issuance are assumed to be in the same group; A sales information management system that estimates the sales information of the ticketing that estimates the group as the sales information corresponding to the group.

21. On the computer, A function to obtain sales information for each ticket issued by the ticket vending machine; a function of estimating the timing at which customers leave the ticket vending machine based on captured images of the vicinity of the ticket vending machine; and a function of estimating a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the ticket; In the function of estimating the group and the sales information, A function of estimating that customers who have dispersed within a predetermined time before and after the timing of the ticket issuance belong to the same group; and a function of estimating the sales information of the ticket that estimated the group as the sales information corresponding to the group.

22. A computer comprising: A function to obtain sales information for each ticket issued by the ticket vending machine; a function of estimating the timing at which customers leave the ticket vending machine based on captured images of the vicinity of the ticket vending machine; and a function of estimating a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the ticket; In the function of estimating the group and the sales information, When multiple tickets are issued within a predetermined time interval, it is possible to estimate that customers who are separated within a period between the first and last tickets issued and within a predetermined time before and after the period belong to the same group. and a function of estimating the sales information of the plurality of tickets that have been estimated as the sales information corresponding to the group.

23. A computer comprising: A function to obtain sales information for each ticket issued by the ticket vending machine; a function of estimating the timing at which customers leave the ticket vending machine based on captured images of the vicinity of the ticket vending machine; and a function of estimating a customer group and sales information corresponding to the group based on the timing of the dispersion and the timing of the issuance of the ticket; In the function of estimating the group and the sales information, A function of inferring that customers who have dispersed from in front of the ticket vending machine in response to ticket issuance belong to the same group; and a function of estimating the sales information of the ticket that estimated the group as the sales information corresponding to the group.

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