Determination device, determination method and determination program

Abstract

To provide a determination device, a determination method, and a determination program for facilitating determination of images of products to be put up for sale.SOLUTION: A system for determining images captured by sellers in e-commerce, such as internet auctions and e-commerce sites, where products are traded over the internet, comprises: an acquisition unit for acquiring images of a product; a calculation unit for calculating a score indicating whether or not the images were captured by a seller based on the images of the product acquired by the acquisition unit; and an output unit for outputting information regarding propriety of the product to be put up for sale based on the score calculated by the calculation unit.SELECTED DRAWING: Figure 2

Description

[Technical field]

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

[0002] Conventionally, electronic commerce, such as Internet auctions and electronic commerce (EC) sites, is used to trade goods over the Internet. In such electronic commerce, sellers prepare product information, which is information about the goods to be put up for auction, such as photographed images of the goods and descriptions of the goods, and provide the prepared product information to a system that provides electronic commerce. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2005-122304 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the above conventional technology, it is difficult to determine whether an image of a product has been photographed by a seller. For example, it is difficult for a purchaser to determine whether an image of a product posted on an auction site, an EC site, or the like is a photograph of a product that the seller has in stock. In addition, for example, images of products provided by manufacturers or images of products of other people may be used as images of products that are put up for sale. As a result, products may be put up for sale on Internet auctions or EC sites even if the product is not actually in stock.

[0005] The present application has been made in consideration of the above, and aims to provide an evaluation device, an evaluation method, and an evaluation program that make it easy to evaluate images of products to be put up for sale. [Means for solving the problem]

[0006] The determination device of the present application is characterized in that it comprises an acquisition unit that acquires an image of a product, a calculation unit that calculates a score as to whether or not the image of the product acquired by the acquisition unit is an image taken by a seller, and an output unit that outputs information regarding whether or not the product can be put up for auction based on the score calculated by the calculation unit. Effect of the Invention

[0007] According to one aspect of the embodiment, it is possible to easily determine whether an image of a product was photographed by the seller. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of a determination method according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of a determination device according to an embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of a determination process of the determination method according to the embodiment. [Figure 4] FIG. 4 is a flowchart showing an example of the flow of the determination process executed by the determination device according to the embodiment. [Diagram 5] FIG. 5 is a flowchart showing an example of the flow of the estimation process executed by the determination device according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, a detailed description will be given of a form for carrying out the determination device, determination method, and determination program according to the present application (hereinafter, referred to as "embodiments") with reference to the drawings. Note that the determination device, determination method, and determination program according to the present application are not limited to these embodiments. In addition, each embodiment can be appropriately combined within a range that does not cause a contradiction in the determination content. In addition, the same parts in each of the following embodiments are given the same reference numerals, and duplicated descriptions are omitted.

[0010] [1. Overview of the Judgment Device] First, an example of the determination according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the determination according to the embodiment, which is realized by a determination device 100. In the example of Fig. 1, an overall system 1 includes a seller terminal 10, the determination device 100, and a single product or multiple products. In addition, the seller terminal 10 and the determination device 100 are connected to each other via a network N so as to be able to communicate with each other via wired or wireless communication.

[0011] The determination device 100 photographs an image of a product by a seller using a dedicated application program (hereinafter, referred to as a "dedicated app") installed in the seller terminal 10 (step S1). For example, when a seller puts up a product he or she has on hand for sale, the seller starts up the dedicated app in the seller terminal 10 and photographs the product to be put up for sale using the camera.

[0012] Next, the determination device 100 acquires an image of the product from the seller terminal 10 (step S2). For example, the determination device 100 acquires an image of a single product or multiple products captured using a dedicated application in the seller terminal 10.

[0013] Next, the determination device 100 estimates whether the acquired image of the product is an image taken by the seller. For example, the determination device 100 compares the position of the photographed product with the positions of products previously put up for sale, and estimates whether the image is an image of the product taken by the seller. In addition, for example, the determination device 100 estimates the position of the product photographed by the seller using a technique such as camera calibration.

[0014] Next, the determination device 100 estimates whether or not the seller has a product in hand, and calculates a score indicating whether or not the image of the product was taken using a dedicated app in the seller terminal 10, based on the estimation result. For example, the calculation is performed so that the score is higher when the estimated product image is in a different position from products previously put up for sale by the seller or other sellers.

[0015] Next, the determination device 100 determines whether the seller has the product in hand based on the score calculated for the product image, and decides whether or not to put the product up for auction (step S3). After determining whether or not to put the product up for auction based on the score, the determination device 100 outputs information regarding whether or not to put the product up for auction to the seller terminal 10. For example, the determination device 100 determines whether or not the score is higher than a predetermined threshold as a method of determining whether or not to put the product up for auction. If the score is higher than the predetermined threshold, the determination device 100 determines that the product can be put up for auction, and if the score is lower, the determination device 100 determines that the product cannot be put up for auction, and outputs the result. The determination device 100 then stores the listing information in the storage unit 120.

[0016] When the determination device 100 determines that the seller has the product in his possession, it allows the product to be put up for sale, and when it determines that the seller does not have the product in his possession, it does not allow the product to be put up for sale. In other words, the determination device 100 calculates a score from the image of the seller's product, and when the score is low, it determines that the seller does not have the product in his possession and does not allow the product related to the image to be put up for sale. Therefore, the determination device 100 can prevent the misuse of images of products provided by manufacturers or images of other people's products, and the act of trying to put up a product when the seller does not have the product in his possession.

[0017] 2. Configuration of the Determination Device Next, the configuration of the determination device 100 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the determination device 100 according to the embodiment. As shown in Fig. 2, the determination device 100 according to the embodiment includes a seller terminal 10, a network N, a communication unit 110, a storage unit 120, and a control unit 130.

[0018] The determination device 100 may be, for example, a PC (Personal Computer), a WS (Work Station), a computer having a server function, etc. The determination device 100 performs processing based on information transmitted from the seller terminal 10 via the network N, for example.

[0019] The seller terminal 10 is an information processing device used by a seller. For example, the information processing device may be a smartphone, a tablet terminal, a desktop PC, a notebook PC, a mobile phone, a PDA (Personal Digital Assistant), etc. In the example shown in FIG. 1, the seller terminal 10 is a smartphone.

[0020] The network N connects the determination device 100 and the seller terminal 10 to be able to communicate with each other by wire or wirelessly. If the network N is wired, it may be realized by ETHERNET (registered trademark) defined in IEEE802.3. If the network N is wireless, it may be realized by wireless LAN (Local Access Memory) defined in IEEE802.11.

[0021] (Regarding communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the seller terminal 10, etc.

[0022] (Regarding the storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in Fig. 2, the storage unit 120 has a seller information storage unit 121, a product image storage unit 122, a calculation result storage unit 123, and a listing information storage unit 124. The configuration of these units will be described below in order.

[0023] (Regarding the seller information storage unit 121) The seller information storage unit 121 stores information related to the seller. For example, the seller information storage unit 121 stores information including the name of the seller and images of the products that have been put up for sale. In addition, for example, the seller information storage unit 121 stores evaluations of the seller from purchasers.

[0024] (Regarding the product image storage unit 122) The product image storage unit 122 stores images of products in the seller's possession. For example, the product image storage unit 122 stores images of products photographed by the seller using a dedicated app in the seller terminal 10. Also, for example, the product image storage unit 122 stores only images of products photographed by the seller using a dedicated app in the seller terminal 10. Also, for example, the product image storage unit 122 stores images of a single product or multiple products photographed by the seller using a dedicated app in the seller terminal 10. Also, for example, the product image storage unit 122 stores multiple images of products photographed by the seller using a dedicated app in the seller terminal 10. Also, for example, the product image storage unit 122 saves and stores images of products photographed by the seller using a dedicated app in the seller terminal 10 as drafts within 24 hours.

[0025] (Regarding the calculation result storage unit 123) The calculation result storage unit 123 stores the score based on whether or not the image of the product taken by the seller is a score. For example, the calculation result storage unit 123 stores the score calculated based on the image of the product stored in the product image storage unit 122.

[0026] (Regarding the commodity information storage unit 124) The selling information storage unit 124 stores information related to all selling. For example, the selling information storage unit 124 stores all selling information of the seller, regardless of whether the item can be sold. For example, the selling information storage unit 124 stores images of items that the calculation result storage unit 123 has determined to be available for selling and information about the items.

[0027] (Regarding the control unit 130) Next, the control unit 130 in Fig. 2 will be described. The control unit 130 is a controller that controls the determination device 100, and is realized, for example, by a CPU (Central Processing Unit) or the like reading out various programs stored in the storage unit 120 of the determination device 100 and executing them using a RAM as a working area. The control unit 130 is also a controller, and may be realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0028] 2, the control unit 130 has an acquisition unit 131, an estimation unit 132, a calculation unit 133, and an output unit 134. The control unit 130 realizes these functions by reading out a program from the storage unit 120 and executing it using the RAM as a working area, and realizes or executes the determination functions and actions described below. These processes will be described in order below.

[0029] (Regarding the acquisition unit 131) The acquisition unit 131 acquires images of products. For example, when a seller puts up a product he or she owns, the acquisition unit 131 starts a dedicated app in the seller terminal 10 and acquires an image of the product to be put up for sale that has been photographed using a camera. For example, the acquisition unit 131 acquires only images of the product that have been photographed using the dedicated app in the seller terminal 10. For example, the acquisition unit 131 can acquire multiple images of the product that have been photographed using the dedicated app in the seller terminal 10. For example, the acquisition unit 131 can acquire images of a single product or multiple products that have been photographed using the dedicated app in the seller terminal 10. For example, the acquisition unit 131 can acquire images of the product that have been photographed using the dedicated app in the seller terminal 10 within 24 hours.

[0030] (Regarding the estimation unit 132) The estimation unit 132 analyzes the image of the product, identifies the shape of the product, and estimates that the image of the product is an image taken by the seller. Based on the estimated shape of the product, the estimation unit 132 compares the position of the product with the position of the same product previously put up for sale by the seller, and estimates whether the seller has stock of the product. Based on the estimated position of the product, the estimation unit 132 estimates whether the image of the product is a three-dimensional object, and identifies whether the seller has stock of the product. Based on the estimated position and shape of the product, the estimation unit 132 estimates whether the time when the image of the product was taken and the time of putting up the product are separated by a predetermined threshold or more. The estimation unit 132 may also determine whether the image of the product to be put up for sale is an image taken using a camera function after starting a dedicated app.

[0031] For example, the estimation unit 132 may implement a plurality of the above three estimation methods, or may implement any one of them. For example, the estimation unit 132 may estimate whether the image of the product was taken by the seller using a dedicated app in the seller terminal 10 with Yes or No, or may estimate with a number indicating a probability. For example, the estimation unit 132 may estimate the image of the product using a technology such as camera calibration as a technology for confirming the position of the image of the product or whether it is a three-dimensional object. The camera calibration technology can separate the product to be put up for sale from the background from the image of the product. Therefore, the estimation unit 132 can identify the background part of the image of the product and compare it with the background of the image of the product that the seller or another seller has put up in the past. For example, when the NFT (Non Fungible Token) technology is applied to the image of the product provided by the manufacturer, the image of the product posted to a dedicated app, the image of the product taken by the user on the spot, etc., the estimation unit 132 compares the information of the owner linked to the information of the product with the information of the seller, and estimates that the image of the product of the seller is the image of the seller based on whether they match. Therefore, the estimation unit 132 can use NFT technology to estimate that the image of the product was taken using a dedicated app in the seller terminal 10.

[0032] (Regarding the calculation unit 133) The calculation unit 133 calculates a score indicating whether or not the image is an image of a product photographed by the seller, based on the image of the product acquired by the acquisition unit 131. For example, the calculation unit 133 performs calculations such that the score becomes higher as the position of the image of the product estimated by the estimation unit 132 differs from that of products previously put up for sale by the seller or other sellers. Also, for example, the calculation unit 133 performs calculations such that the score becomes higher as the image of the product estimated by the estimation unit 132 is more likely to be a three-dimensional object. Also, for example, the calculation unit 133 performs calculations such that the score becomes lower as the time when the product in the seller's possession is photographed using a dedicated app in the seller terminal 10 is farther away from the time when the product is put up for sale, based on the image of the product estimated by the estimation unit 132.

[0033] (Regarding the output unit 134) The output unit 134 outputs information regarding whether or not the listing is permitted, based on the score calculated by the calculation unit 133. Furthermore, if the score calculated by the calculation unit 133 falls below a predetermined threshold, the output unit 134 disallows the listing. For example, the output unit 134 outputs information regarding whether or not the listing is permitted to be displayed to the seller terminal 10. Furthermore, if the output unit 134 disallows the listing, it outputs a warning modal to the seller terminal 10. Furthermore, for example, if the output unit 134 disallows the listing, it makes the seller terminal 10 invisible.

[0034] 3. An example of processing by the determination device Next, an example of the process of the determination device 100 will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the process of the determination device according to the embodiment, which is realized by the determination device 100. In the example of Fig. 3, the overall system 1 includes a seller terminal 10, the determination device 100, and a single product or multiple products.

[0035] First, the determination device 100 receives an image of a product from a seller using a dedicated app in the seller terminal 10 (step S1). For example, when a seller puts up a product he or she owns, the seller activates the dedicated app in the seller terminal 10 and takes a picture of the product to be put up for sale using the camera. The determination device 100 acquires the product image from the seller terminal 10 (step S2). Also, for example, the seller can save the product image as a draft within 24 hours from the time of the image capture (step S2.1). Then, the determination device 100 stores the acquired product image in the product image storage unit 122.

[0036] The determination device 100 determines whether or not the item can be put up for sale based on the acquired image of the item. When the determination result indicates that the item can be put up for sale (step S3), the determination device 100 outputs to the seller terminal 10 that the item can be put up for sale. Furthermore, for example, when it takes time to determine the image of the item, the determination device 100 displays a badge indicating trust to the purchaser on a dedicated app in the seller terminal 10 when the determination is completed if the item can be put up for sale (step S5). When the determination result indicates that the item cannot be put up for sale (step S4), the determination device 100 outputs to the seller terminal 10 that the item cannot be put up for sale.

[0037] If the determination result indicates that listing is not permitted (step S4), the determination device 100, for example, displays a warning modal on the seller terminal 10 (step S6). Also, for example, the determination device 100 displays or hides the warning modal on the seller terminal 10 (step S7). Also, for example, the determination device 100 performs patrol inspection (step S8). This is regular monitoring by the operator or manager of the dedicated app to expose sellers who have engaged in fraudulent activities.

[0038] Furthermore, the determination device 100 determines that fraudulent acts include a lack of necessary product images, taking multiple photos of one product and trying to sell it, having a history of causing harm that required compensation in the past year, a score lower than a predetermined threshold, etc. Therefore, the determination device 100 can prevent the misuse of product images provided by manufacturers or images of other people's products, and the act of trying to sell a product despite the seller not having the product in hand.

[0039] The determination device 100 is a determination device that performs a determination process, and may be realized by the seller terminal 10, not only by a server device. For example, the calculation of the score and the determination by the determination device 100 may be realized by a dedicated application in the seller terminal 10. For example, the determination device 100 may be replaced with the seller terminal 10, and various processes may be realized by the seller terminal 10.

[0040] [4. Judgment flow] Next, a procedure of judgment according to the embodiment will be described with reference to Fig. 4 and Fig. 5. Fig. 4 and Fig. 5 are flowcharts showing an example of judgment according to the embodiment. Below, the procedure of judgment according to the embodiment will be described with reference to the flowcharts shown in Fig. 4 and Fig. 5.

[0041] First, a procedure for determining an image of a product photographed by a seller using a dedicated application in the seller terminal 10 will be described with reference to FIG. 4. When a seller photographs an image of a product using a dedicated application in the seller terminal 10 and acquires the image of the product (step S101, Yes), the acquisition unit 131 of the determination device 100 estimates whether the acquired image of the product is an image of the product photographed by the seller (step S102). The estimation process will be described in detail later with reference to FIG. 5. On the other hand, when a seller does not use a dedicated application in the seller terminal 10 and uses an image of a product provided by a manufacturer or an image of a product of another person, and an image of the product cannot be acquired (step S101, No), the determination device 100 determines that the product cannot be put up for sale (step S106).

[0042] Next, it is estimated whether or not the seller has an image of the product, and based on the estimation result, a score is calculated based on whether or not the image of the product was taken using a dedicated app in the seller terminal 10 (step S103). If the calculated score is higher than a predetermined threshold (step S104, Yes), the determination device 100 determines that the product can be put up for auction (step S105). On the other hand, if the calculated score is lower than the predetermined threshold (step S104, No), the determination device 100 determines that the product cannot be put up for auction (step S106).

[0043] Next, a procedure for estimating an image of a product photographed by a seller using a dedicated app in the seller terminal 10 will be described with reference to Fig. 5. The estimation unit 132 of the determination device 100 determines whether the image is a product image photographed using a dedicated app in the seller terminal 10 (step S201), and if it is determined that the image is a product image photographed using a dedicated app in the seller terminal 10 (step S201, Yes), it compares the position with images of products previously put up for sale by the seller or other sellers (step S202). On the other hand, if it is determined that the image was not photographed using a dedicated app in the seller terminal 10 (step S201, No), the determination device 100 ends the estimation process.

[0044] Next, the position of the product is compared with images of the product previously put up by the seller or other sellers, and if the position of the product differs (step S202, Yes), it is determined whether the captured image of the product is a three-dimensional object (step S203).On the other hand, if the position of the product has not changed after comparing images of the product previously put up by the seller with the position of the product (step S202), the determination device 100 ends the estimation process.

[0045] Next, if the product image is a three-dimensional object (step S203, Yes), it is determined whether or not it has been within 24 hours since the product image was captured (step S204). On the other hand, if the product image is not a three-dimensional object (step S203, No), the determination device 100 ends the estimation process. Then, if it has been within 24 hours since the product image was captured (step S204, Yes), the determination device 100 ends the estimation process. On the other hand, if it has been more than 24 hours since the product image was captured (step S204, No), the determination device 100 ends the estimation process.

[0046] According to this, an image of a product taken using a dedicated application in the seller terminal 10 is calculated as a score depending on whether the seller has the product in hand, and if the score is higher than a predetermined threshold, it is determined that the product can be put up for sale, and if the score is lower than the predetermined threshold, it is determined that the product cannot be put up for sale. Therefore, it is possible to provide a determination method and determination program that can prevent the misuse of product images provided by manufacturers or images of other people's products, and the act of trying to put up a product when the seller does not have the product in hand.

[0047] [5. Hardware Configuration] The determination device 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in Fig. 6. Fig. 6 is a hardware configuration diagram showing an example of a computer that realizes the functions of the determination device 100. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output IF (Interface) 1060, an input IF 1070, and a network IF 1080 are connected by a bus 1090.

[0048] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050 and programs read from the input device 1020, and executes various processes. The primary storage device 1040 is a memory device, such as a RAM, that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device that stores data used by the arithmetic device 1030 for various calculations and various databases, and is realized by a ROM (Read Only Memory), a HDD (Hard Disk Drive), a flash memory, or the like.

[0049] The output IF 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a monitor or a printer, and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (registered trademark) (High Definition Multimedia Interface). The input IF 1070 is an interface for receiving information from various input devices 1020, such as a mouse, keyboard, and scanner, and is realized by a USB, for example.

[0050] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disk), a DVD (Digital Versatile Disk), or a PD (Phase change rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. The input device 1020 may also be an external storage medium such as a USB memory.

[0051] The network IF 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0052] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output IF 1060 and the input IF 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0053] For example, when the computer 1000 functions as the determination device 100 , the arithmetic unit 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize the functions of the control unit 130 of the determination device 100 .

[0054] [6. Composition and Effects] The determination device 100 according to the present disclosure includes an acquisition unit 131 that acquires an image of a product, a calculation unit 133 that calculates a score indicating whether or not the image of the product was photographed by a seller based on the image of the product acquired by the acquisition unit 131, and an output unit 134 that outputs information regarding whether or not the product can be listed based on the score calculated by the calculation unit 133.

[0055] According to this configuration, a score is calculated based on whether an image of a product taken using a dedicated app in the seller terminal 10 is an image of the product taken using a dedicated app in the seller terminal 10, and if the score is higher than a predetermined threshold, it is determined that the product can be put up for sale. Therefore, it is possible to provide a determination device 100 that can prevent the misuse of images of products provided by manufacturers or images of products of other people, and the act of trying to put up products when the seller does not have them in hand.

[0056] The acquisition unit 131 of the determination device 100 according to the present disclosure acquires an image of a product photographed using a dedicated application in the seller terminal 10.

[0057] According to this configuration, the acquisition unit 131 can acquire only images of products captured using a dedicated application in the seller terminal 10. Also, for example, the seller can temporarily store the images of the products within 24 hours after capturing the images of the products. Therefore, it is possible to provide a determination device 100 that can prevent the misuse of images of products provided by manufacturers or images of products of other people, and the act of a seller trying to put up a product even though he or she does not have the product in hand.

[0058] The output unit 134 of the determination device 100 according to the present disclosure outputs information regarding the acceptability of the seller based on the score calculated by the calculation unit 133.

[0059] According to this configuration, if the score calculated in calculation 133 is higher than a predetermined threshold, output unit 134 determines that the listing is permitted, and if the score is lower than the predetermined threshold, determines that the listing is not permitted, and outputs the result to seller terminal 10. Therefore, it is possible to provide a determination device 100 that can prevent the misuse of images of products provided by manufacturers or images of products of other people, and the act of trying to list a product even though the seller does not have the product in hand.

[0060] The above describes the embodiment of the present application in detail based on the drawings, but this is merely an example, and the present invention can be implemented in other forms that include various modifications and improvements based on the knowledge of those skilled in the art, including the form described in the Disclosure of the Invention section.

[0061] Moreover, the above-mentioned "section, module, unit" can be read as "means" or "circuit", etc. For example, the acquisition unit 131 can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0062] 1. Overall System 10 Seller terminal 100 Judgment device 110 Communications Department 120 Storage section 121 Seller information storage unit 122 Product image storage unit 123 Calculation result storage unit 124 Exhibition information storage section 130 Control section 131 Acquisition Department 132 Estimation Department 133 Calculation section 134 Output section N Network

Claims

1. An acquisition unit for acquiring an image of a product; A calculation unit that calculates a score indicating whether the image of the product was taken by a seller based on the image of the product acquired by the acquisition unit; an output unit that outputs information regarding whether or not the auction can be put up for auction based on the score calculated by the calculation unit; A determination device comprising:

2. An estimation unit that analyzes an image of the product, identifies a shape of the product, and estimates whether the image of the product is an image taken by a seller, The determination device according to claim 1 , wherein the calculation unit calculates the score based on an estimation result estimated by the estimation unit.

3. The estimation unit further includes an estimation unit that, based on the estimated shape of the product, compares the estimated shape of the product with a position of an identical product previously put up for sale by the seller and estimates whether the seller has stock of the product; The determination device according to claim 1 , wherein the calculation unit calculates the score based on an estimation result estimated by the estimation unit.

4. The estimation unit further includes an estimation unit that determines whether an image of the product is a three-dimensional object based on the estimated position of the product and estimates whether a seller has stock of the product; The determination device according to claim 1 , wherein the calculation unit calculates the score based on an estimation result estimated by the estimation unit.

5. The estimation unit further includes an estimation unit that estimates whether or not a time when an image of the product was taken and a time when the product was put up for sale are different from each other by a predetermined threshold value or more based on the estimated position and shape of the product, The determination device according to claim 1 , wherein the calculation unit calculates the score based on an estimation result estimated by the estimation unit.

6. 6. The determination device according to claim 1, wherein the output unit disallows the auction when the score calculated by the calculation unit is below a predetermined threshold value.

7. A determination method executed by a determination device, comprising: An acquisition step of acquiring an image of a product; A calculation step of calculating a score based on whether the image of the product acquired by the acquisition step was taken by a seller; an output step of outputting information regarding whether or not the item can be put up for auction based on the score calculated in the calculation step; A method for determining whether or not a particular

8. An acquisition step of acquiring an image of a product; A calculation step of calculating a score based on whether the image of the product acquired by the acquisition step was taken by a seller; an output step of outputting information regarding whether or not the item can be put up for auction based on the score calculated in the calculation step; A judgment program for causing a computer to execute the above.

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