JP7061326B1 - Information processing equipment, information processing system and information processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make it possible to evaluate an article from a plurality of different viewpoints while reducing the work of a user for an information processing device for evaluating an article based on captured image data. SOLUTION: A server 3 acquires photographed image data generated by a target article photographed by a target user from a terminal via a network, analyzes an image of the target article recorded in the photographed image data, and analyzes the target article. A process of recognizing the state of the appearance of the target article, a process of recognizing the character image of the character included in the image of the target article, a process of image analysis of the image of the target article to recognize the model number of the target article, and a process of recognizing the model number of the target article. At least one of the processes of analyzing the image to determine the authenticity of the target article is executed, and among the recognized state of the appearance of the target article, the recognized character, the recognized model number, and the result of the determination of the authenticity. The evaluation unit 13 for evaluating the target article by reflecting at least one is provided. [Selection diagram] Fig. 2

Description

The present invention relates to an information processing device that evaluates an article based on captured image data, an information processing system including the information processing device and a terminal, and an information processing method by the information processing device.

Conventionally, there is known a system for evaluating an article by using photographed image data generated by photographing the article. Regarding this type of system, for example, in Patent Document 1, after the server acquires a panoramic photograph (photographed image) generated by taking a used car, the panoramic photograph is stored, and the situation of scratches on the used car after the fact, etc. Is described as a system that allows you to check the image with a panoramic photograph.

Japanese Unexamined Patent Publication No. 2018-97679

Here, in general, when evaluating an article, it is required to evaluate the article not only from a single viewpoint but also from a plurality of different viewpoints. Normally, not only one element of an article affects the evaluation, but by evaluating the article from a plurality of different viewpoints, it is possible to evaluate the article by adding multiple elements, and the validity of the evaluation result is high. Because it becomes. Further, in the conventional system, prior to the evaluation of the article, the user takes a picture of the article or provides the information necessary for the evaluation of the article (for example, the information used for the evaluation is input to the given user interface). However, this work was complicated for the user. Based on the above, there was a need to be able to evaluate goods from a plurality of different viewpoints while reducing the work of the user.

The present invention has been made to solve such a problem, and an object of the present invention is to make it possible to evaluate an article from a plurality of different viewpoints while reducing the work of a user.

In order to solve the above-mentioned problems, the present invention acquires photographed image data generated by photographing the target article by the target user from the terminal via the network. Then, the image of the target article recorded in the captured image data is image-analyzed to recognize the state related to the appearance of the target article, and the character recognition process for the image of the character included in the image of the target article is performed. At least one of a process of recognizing the model number of the target article by image analysis and a process of determining the authenticity of the target article by image analysis of the image of the target article is executed. Then, the target article is evaluated by reflecting the state regarding the appearance of the recognized target article and at least one of the recognized characters, the recognized model number, and the result of the determination of authenticity.

According to the present invention configured as described above, in addition to the state relating to the appearance of the article, the character recognized by the character recognition targeting the image of the character and the model number recognized by the image analysis targeting the image of the article. , And, since the article is evaluated by reflecting at least one of the results of the authenticity determination performed on the image of the article, the article can be evaluated from a plurality of different viewpoints. At that time, at least one of recognition of the state regarding the appearance of the article, recognition of characters by character recognition, recognition of model number by image analysis, and determination of authenticity is performed based on common photographed image data. Therefore, the user only needs to take a picture of the target article when evaluating the article, and needs to separately perform the work of inputting characters to be recognized, the work of inputting the model number, the work of providing information used for authenticity determination, and the like. not. That is, according to the present invention, it is possible to evaluate an article from a plurality of different viewpoints while reducing the work of the user.

It is a figure which shows the structural example of the information processing system which concerns on one Embodiment of this invention. It is a block diagram which shows the functional structure example of the terminal and the server which concerns on one Embodiment of this invention. It is a figure which shows an example of the article classification tree. It is a figure which shows an example of the screen displayed on a terminal. It is a figure which shows an example of the system-related information which concerns on a notebook computer. It is a figure which shows an example of the screen displayed on a terminal. It is a figure which shows an example of the system-related information which concerns on a smartphone. It is a figure which shows an example of the screen displayed on a terminal. It is a figure which shows an example of the screen displayed on a terminal. It is a flowchart which shows the operation example of the information processing apparatus which concerns on one Embodiment of this invention.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing a configuration example of the information processing system 1 according to the present embodiment. As shown in FIG. 1, the information processing system 1 includes a terminal 2 and a server 3. Both the terminal 2 and the server 3 can connect to the network N including the Internet, a telephone network, and other communication networks.

The server 3 is a server device having the terminal 2 as one of the clients. In FIG. 1, the server 3 is represented by one block, but the server 3 does not have to be a single server device, and may be configured by, for example, a plurality of server devices, or may be a part of a predetermined system. There may be. The server 3 is managed and operated by a service providing company (predetermined entity), and provides services described later. The server 3 corresponds to the "information processing device" in the claims.

The terminal 2 is a smartphone in which a touch screen 4 (display panel + touch panel) is provided in a wide area on the entire surface of a tablet-type housing. In particular, the terminal 2 according to the present embodiment is equipped with a camera 5 and has a function of generating captured image data based on the result of photographing by the camera 5. A predetermined application (hereinafter referred to as "dedicated application") is installed in the terminal 2 in advance by using the application download system. The function of the dedicated application will be described later. Note that FIG. 1 schematically shows one of the innumerable terminals 2 connected to the network N.

FIG. 2 is a block diagram showing a functional configuration example of the terminal 2 and the server 3. As shown in FIG. 2, the terminal 2 includes a terminal-side control unit 10 and a terminal-side communication unit 11 as a functional configuration. Further, the server 3 includes a server-side communication unit 12 and an evaluation unit 13 as a functional configuration. Each of the above functional blocks 10 to 12 can be configured by any of hardware, DSP (Digital Signal Processor), and software. For example, when configured by software, each of the above functional blocks 10 to 12 is actually configured to include a computer CPU, RAM, ROM, etc., and is a program stored in a recording medium such as RAM, ROM, hard disk, or semiconductor memory. Is realized by the operation of. In particular, the terminal-side control unit 10 performs various processes by the hardware such as the CPU reading and executing the dedicated application (however, the OS, the API provided by the OS, and other accompanying programs) stored in the storage medium. Is feasible. Further, the server 3 includes a server-side storage unit 14 as a storage medium.

The terminal-side communication unit 11 communicates with a device connected to the network N according to a predetermined protocol. In the following description, it is assumed that the communication between the terminal 2 and the device connected to the network N is appropriately performed by the terminal-side communication unit 11, and detailed description thereof will be omitted. Further, the server-side communication unit 12 communicates with the device connected to the network N according to a predetermined protocol. In the following description, it is assumed that the communication between the server 3 and the device connected to the network N is appropriately performed by the server-side communication unit 12, and detailed description thereof will be omitted.

Here, the server 3 provides the following services (hereinafter referred to as "this service") to the user. That is, assume a user who wants to obtain funds based on the goods he / she owns. User-owned items are, for example, branded bags, branded accessories, and other branded items, and, for example, laptops, smartphones, game consoles, digital cameras, and other electronic devices (but these). Is just an example). The user takes a picture of the article by the terminal 2, and the photographed image data based on the photographed result is transmitted from the terminal 2 to the server 3. The server 3 derives the assessed amount of the article based on the captured image data, and provides the user with information indicating the assessed amount. In the following description, it may be appropriately expressed as "assessment" to finally derive the assessed amount by performing various processes.

Although detailed explanation is omitted, after the valuation amount of the goods is derived, if the user consents, the goods are purchased by the service provider at the valuation amount and the money equivalent to the valuation amount is provided to the user. Will be done. The goods purchased by the service provider are then leased to the user subject to payment of the lease fee. At the time of leasing, a lease contract is concluded between the user and the service provider, and the user is obliged to pay the lease fee in accordance with the lease contract. Therefore, the user can obtain funds equivalent to the assessed amount while keeping the goods at hand without handing them over to the service provider.

The server 3 systematically realizes the above provision of this service in cooperation with the terminal 2. In particular, the server 3 according to the present embodiment has a unique configuration described below, and while reducing the work of the user, it makes an assessment from a plurality of different viewpoints and derives the assessed amount. Hereinafter, the operations of the server 3 and the terminal 2 at the time of providing this service will be described.

Here, prior to the description of the processing of the server 3 and the terminal 2, the "article classification" and the "deepest classification" in the present embodiment will be described. In this embodiment, a tree-structured article classification tree (hereinafter referred to as “article classification tree”) is defined in advance for articles that can be assessed in this service. FIG. 3 is a diagram showing an example of an article classification tree. Hereinafter, the article classification tree will be described with reference to FIG. However, the article classification tree illustrated in FIG. 3 is very simplified for convenience of explanation. In the example of FIG. 3, in the hierarchy one level below the root node, three article classifications of a notebook computer (article classification), a smartphone, and a bag (article classification) are defined for the purpose of roughly classifying articles. In the following description, when expressing the hierarchical state of the article classification, the root node is assumed to exist as a matter of course, and the root node may be omitted. Further, in the present embodiment, the bag is assumed to be a brand product.

At the next level below the laptop computer (article classification), two article classifications, Windows (article classification) and MacOS (article classification), are defined focusing on the OS (however, Windows and MacOS are both registered trademarks). ). Further, in the layer immediately below Windows (article classification), two article classifications, maker MK1 (article classification) and maker MK2 (article classification), are defined focusing on the manufacturer. Also, in the hierarchy one level below the smartphone (article classification), two article classifications, iOS (article classification) and Android (article classification), are defined focusing on the OS (however, iOS and Android are both registered trademarks). ). At the next level below the bag (article classification), three article classifications, brand B1 (article classification), brand B2 (article classification), and brand B3 (article classification), are defined, focusing on the brand of the bag. Has been done.

In the above example of FIG. 3, the article classification corresponding to the leaf node of the article classification tree corresponds to the "deepest classification". For example, "laptop (article classification)> Windows (article classification)> maker MK1 (article classification)" is one independent "deepest classification", and "bag (article classification)> brand B3 (article classification)" is also independent. It is one of the "deepest classifications". The deepest classification corresponds to the "classification" of the claims. Further, as is clear from the above description, the "article classification" means each classification when the upper hierarchy is classified into two or more in a certain hierarchy.

Now, when using this service, the user activates the dedicated application of the terminal 2. In response to the activation of the dedicated application, the terminal side control unit 10 of the terminal 2 and the evaluation unit 13 of the server 3 cooperate to appropriately authenticate the user, and the evaluation unit 13 uses the user identification information for identifying the user. Recognize. Hereinafter, the user of the terminal 2 (the user who intends to use this service) is particularly referred to as a "target user", and the article targeted by the target user for assessment is particularly referred to as a "target article".

Next, the target user performs a predetermined operation on the user interface provided by the function of the dedicated application to display the second layer article classification selection screen G4A (FIG. 4A) on the touch screen 4 of the terminal 2. Instruct. In response to the instruction, the terminal side control unit 10 of the terminal 2 and the evaluation unit 13 of the server 3 cooperate to execute the deepest classification recognition process. Hereinafter, the deepest classification recognition process will be described in detail.

In the deepest classification recognition process, the terminal side control unit 10 of the terminal 2 requests the server 3 for drawing data for displaying the second layer article classification selection screen G4A. The request is made, for example, as an HTTP request. In response to the request, the evaluation unit 13 of the server 3 generates drawing data and responds to the terminal side control unit 10 of the terminal 2. The terminal side control unit 10 of the terminal 2 receives the drawing data, and displays the second layer article classification selection screen G4A on the touch screen 4 based on the drawing data.

Below, generation / transmission of drawing data by the evaluation unit 13 of the server 3, detection of input to various screens displayed based on the drawing data, acquisition of information input to various screens, dynamic change of various screens, etc. Various processes related to the screen of the above shall be appropriately executed using CGI, Javascript (registered trademark), Ajax, DHCP, and other existing technologies, and detailed description will not be given. Further, the evaluation unit 13 of the server 3 transmits the drawing data to the terminal side control unit 10 of the terminal 2, and the screen based on the drawing data is displayed on the touch screen 4 of the terminal 2. The unit 10 may express such as "display the XX screen on the touch screen 4" or simply "display the XX screen by the evaluation unit 13.".

FIG. 4A is an example of the second layer article classification selection screen G4A. The second layer article classification selection screen G4A is a screen in which icons indicating each of the second layer article classifications in the article classification tree are displayed in a list. Each icon can be selected by touch operation. The second layer of article classification roughly classifies the articles that can be assessed by this service, and sufficient types are prepared so that the articles that can be assessed by this service belong to any of the article categories. Has been done. The target user selects the article classification by touching the icon corresponding to the article classification of the target article.

When any of the article classifications is selected on the second layer article classification selection screen G4A, the evaluation unit 13 tells the terminal side control unit 10 an icon indicating each of the article classifications in the next lower layer of the selected article classification. Is displayed on the touch screen 4. The target user selects an article classification by touching any one of the icons displayed on the screen. As described above, when the target user selects an article classification on a certain screen, a screen displaying a list of article classifications in the next lower layer of the selected article classification is displayed on the touch screen 4, and the target user again displays the article classification. When the article classification is selected, the process that the screen displaying the list of the article classifications one level below the selected article classification is displayed on the touch screen 4 is repeatedly executed until the deepest classification is selected by the target user. Will be done.

For example, it is assumed that the hierarchical structure of the article classification follows the article classification tree exemplified in FIG. 3, and the target article is a “smartphone whose OS is iOS”. In this case, referring to FIG. 4, the target user selects the icon B4A indicating the smartphone (article classification) on the second layer article classification selection screen G4A (FIG. 4A), and the article classification related to the OS is correspondingly selected. The screen G4B (FIG. 4 (B)) for selecting is displayed, and the target user selects the icon B4B indicating iOS (article classification) on this screen G4B. As described above, "smartphone (article classification)> iOS (article classification)" is selected as the deepest classification by the target user.

The evaluation unit 13 recognizes the deepest classification (the deepest classification of the target article) selected by the target user as described above. Hereinafter, the deepest classification of the target article is referred to as "target deepest classification". The above processing is the deepest classification recognition processing.

After the deepest classification recognition process, the evaluation unit 13 and the terminal side control unit 10 cooperate to execute the captured image data acquisition process. Hereinafter, the captured image data acquisition process will be described in detail.

As described above, in the present embodiment, the deepest classification is defined according to the article classification tree, and the article belongs to any of the deepest classifications. In the present embodiment, it is determined in advance by what method the photographed image data is required for each deepest classification, and the photographed image data is acquired for each deepest classification accordingly. The mode of processing is different. Hereinafter, the method for photographing an article is referred to as an "article photography method". As will become clear later, the photographed image data is used when deriving the assessed amount of the target article. Then, the article photographing method for a certain deepest classification is determined from the viewpoint of preparing data having appropriate contents as photographed image data to be used when deriving the assessed amount of the article belonging to the deepest classification. Has been done.

Hereinafter, assuming that the article classification tree follows the tree shown in FIG. 3, when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1", "smartphone (article classification)> iOS (article classification)". The photographed image data acquisition process will be described by taking each of the case of "classification)" and the case of "bag (article classification)> brand B1" as examples.

In the following description, the "model number" means information for identifying the type, model, type or model of the article. The model number may be referred to as a manufacturer's model number, a product number, a product number, a model name, a model, a model number, a model, a model number, a model, a type, a product, or the like. Further, the "unique number" means information unique to each article. The unique number may be called a serial number, a serial number, a serial number, a serial number, or the like. Of course, even if the items have the same model number, the unique numbers will always be different. Especially for smartphones, IMEI corresponds to a unique number.

<When the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)">
First, the captured image data acquisition process when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)" will be described. In this case, the target article belongs to a notebook computer as a major category, but the notebook computer generally has the following characteristics.
(1) Having a display, it is possible to display system-related information including at least specifications for a model number and a predetermined element on the display.
(2) Even if the model number is the same, the specifications may differ.
(3) Deterioration that occurs in the part including the front of the display affects the assessment (evaluation).
That is, a laptop computer has a display and can display system-related information including at least specifications for a model number and a predetermined element on the display, and even if the model number is the same, the specifications may be different. , It is an electronic device having three characteristics that deterioration occurring in a part including the front surface of a display affects the evaluation.

Regarding (1), the system-related information is various information related to electronic devices such as specifications, specifications, settings, statuses, attributes, etc. related to hardware and software. System-related information is called system information in a Windows system. Generally, smartphones, general-purpose laptop computers, general-purpose tablet terminals, general-purpose laptop terminals, and general-purpose desktop terminals are configured to be able to display system-related information on a display by performing predetermined operations according to the installed OS. ing. In addition, there are also dedicated devices such as digital watches that are configured to be able to display system-related information on the display.

FIG. 5 is a diagram showing a typical example of system-related information that can be displayed on a notebook computer. As shown in FIG. 5, system-related information relating to a notebook computer usually includes a model number, a unique number, a processor type, and a total number of memories. The processor type and the total number of memories correspond to the "specs for a predetermined element" in the claims. Note that other terms may be used with the same meaning for the model number, unique number, processor type, and total number of memories in FIG. For example, the processor type may be expressed as a processor name, and the total number of memories may be simply expressed as memory.

Regarding (2), for example, a notebook computer may have a processor type that can be selected at the time of purchase, and even notebook computers of the same model number may have different processor types (= different specifications). Also, for example, in a notebook computer, memory (main memory) may be added later, and even if the notebook computer has the same model number, the total number of memories (main memory capacity) is different (= specifications are different). Sometimes. For laptops, differences in specifications affect the assessment.

Regarding (3), the portion including the front of the display is, specifically, the display and the keyboard that are exposed at the same time when the notebook computer is opened. Regarding the deterioration that occurs in the portion including the front surface of the display, the deterioration of the display is cracks, scratches, stains, dents, and the like. Deterioration of the keyboard includes missing parts, scratches, dirt, wear, and the like. Deterioration of the display and keyboard affects the usability of the laptop computer, and therefore has a stronger impact on the assessment than deterioration in other parts.

When the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)", the evaluation unit 13 first refers to the article photographing method database stored in the server-side storage unit 14. Then, the data related to the article photography method corresponding to the deepest classification of the target is acquired. The article photography method database is a database in which data related to the article photography method is registered for each deepest classification. The article shooting method-related data includes drawing data of various screens displayed on the terminal side control unit 10 by the evaluation unit 13 in the shot image data acquisition process. The processing of the evaluation unit 13 in the captured image data acquisition processing described below is executed based on the article imaging method-related data corresponding to the target deepest classification.

The evaluation unit 13 causes the terminal side control unit 10 to display the screen G6A of FIG. 6A on the touch screen 4. The screen G6A instructs the notebook computer to be opened and shoots so that the entire area of the display and keyboard (the part including the front of the display) can be captured while the system-related information is displayed on the display, and the shooting procedure is performed. It is a screen to guide (explain). In particular, on the screen 6A, the model number, the unique number, the processor type, and the total number of memories included in the system-related information are instructed to be displayed on the display. This is because this information will be used in the assessment, as will become clear later.

As shown in FIG. 6A, a laptop computer is opened at the upper part of the screen 6A, and system-related information (expressed as "system information" in FIG. 6A) is displayed on the display, and the display and keyboard are displayed. A sentence is displayed instructing the photographer to take a picture. Further, on the screen G6A, an image showing an open notebook computer is displayed below the text. This image is an image for allowing the target user to imagine how to take the image, and is not limited to the content illustrated in FIG. 6A.

On the screen G6A, an explanatory text explaining the shooting procedure is displayed below this image. Although omitted in FIG. 6A, the description shows system-related information (particularly the model number, unique number, processor type, and total number of memories included in the system-related information) displayed on the display. It also contains information that the target user should be aware of and keep in mind in order to capture the entire area of the keyboard. For example, the description includes information indicating a procedure for displaying system-related information on a display. The information indicating the procedure indicates, for example, the procedure for each OS version when the procedure differs for each OS version. Further, the description reflects that the OS of the notebook computer is Windows and that the manufacturer of the notebook computer is MK1.

The screen G6A is a portion of the claims, including the front of the display, in which the characters of the target article are photographed together with the appearance of the object and the system-related information is displayed on the display. It corresponds to "a screen that guides you to be done". That is, the evaluation unit 13 recognizes the classification of the target article prior to the shooting when the target user takes a picture of the target article, and the recognized classification belongs to the electronic device having the above-mentioned three characteristics. If this is the case, the terminal 2 is displayed with a screen for guiding the portion including the front of the display to be photographed while the system-related information is displayed on the display.

A button B6A instructing the start of shooting is displayed on the screen G6A of FIG. 6A, and the target user operates the button B6A when the shooting is ready. In response to the operation of the button B6A, the terminal side control unit 10 enables the camera function of the terminal 2 and cooperates with the evaluation unit 13 to accommodate the target article at the time of shooting as shown in FIG. 6B. The screen G6B on which the lines and precautions for shooting are displayed is displayed. The target user executes shooting while the screen G6B is displayed, and captured image data is generated according to the shooting. The terminal side control unit 10 transmits the captured image data to the evaluation unit 13, and the evaluation unit 13 acquires the captured image data.

As described above, regarding the captured image data acquisition process, when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)", the system-related information is displayed on the display. , The evaluation unit 13 guides the portion including the front surface of the display (more specifically, the display + keyboard) to be photographed. Then, when the target user takes a picture according to the guidance, one shot image data in which the image of the notebook computer (target article) in which the system-related information is shown on the display is recorded is generated, and the evaluation unit 13 generates this 1 Acquire one shot image data.

The shooting image data acquisition process when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)" has been described above, but the article has the same characteristics as the notebook computer. The captured image data acquisition process is executed in the same manner. Whether or not it has the same characteristics as a laptop computer is determined based on the deepest classification. An article having the same characteristics as a laptop computer is, for example, a laptop computer.

<When the target deepest classification is "smartphone (article classification)> iOS (article classification)">
Next, the captured image data acquisition process when the target deepest classification is "smartphone (article classification)> iOS (article classification)" will be described. In this case, the target article belongs to the smartphone as a major category, but the smartphone generally has the following characteristics.
(1) A touch screen (display) is provided in a wide area on the front surface, and system-related information including at least a model number and an IMEI (unique number) can be displayed on the display.
(2) The terminal may be purchased by installment payment (installment payment).
(3) Deterioration of the touch screen (display) on the front of the housing affects the assessment.
In other words, smartphones are characterized by having a display in a large area on the front and being able to display system-related information including at least the model number and unique number on the display, the feature that they may be purchased by installment payment, and the front of the display. It is a tablet terminal having three characteristics that the deterioration caused in the portion including the above affects the evaluation.

Regarding (1), FIG. 7 is a diagram showing a typical example of system-related information that can be displayed on a smartphone. As shown in FIG. 7, the system-related information relating to the smartphone typically includes a model number (expressed as a model number in FIG. 7) and an IMEI (unique number). Regarding (2), a service that allows smartphones to be purchased by installment payment is widely used, and terminals may be purchased by installment payment through this service. Regarding (3), since the deterioration of the touch screen affects the usability of the smartphone, it has a stronger influence on the assessment than the deterioration in other parts. Especially for smartphones, the touch screen may crack, and in general, if the touch screen is cracked, the assessed amount of the smartphone will be considerably low.

When the target deepest classification is "smartphone (article classification)> iOS (article classification)", the evaluation unit 13 acquires the article shooting method-related data corresponding to the target deepest classification from the article photography method database, and acquires the acquired article photography. Perform the following processing based on the method-related data. That is, the evaluation unit 13 causes the terminal side control unit 10 to display the screen G8 of FIG. 8 on the touch screen 4 instead of the screen G6A of FIG. 6 (A). The screen G8 is a screen for instructing that the entire front surface of the housing is captured with the system-related information displayed on the touch screen, and for guiding (explaining) the shooting procedure. In particular, on the screen G8, the model number and IMEI (unique number) included in the system-related information are instructed to be displayed on the touch screen. This is because this information will be used in the assessment, as will become clear later.

As shown in FIG. 8, the system-related information (expressed as “system information” in FIG. 8) is displayed on the touch screen at the upper part of the screen G8, and the entire front surface of the housing is photographed so as to be captured. A sentence instructing that is displayed. Further, on the screen G8, an image showing a state in which the smartphone is viewed from the front is displayed below the text. This image is an image for making the target user imagine what kind of method should be taken, and is not limited to the content illustrated in FIG. 8 as a matter of course.

On the screen G8, an explanatory text explaining the shooting procedure is displayed below this image. Although omitted in FIG. 8, the description includes the target user in order to capture the entire front surface of the housing with the system-related information (particularly the model number and IMEI) displayed on the touch screen. Contains information that should be recognized and noted. For example, the description contains information indicating a procedure for displaying system-related information on a touch screen. The information indicating the procedure indicates, for example, the procedure for each OS version when the procedure differs for each OS version. In addition, the description reflects that the OS of the smartphone is iOS.

The screen G8 is a front view of the housing with the claims "a screen that guides the characters of the target article to be photographed together with the appearance of the target article" and "a system-related information is displayed on the display". It corresponds to the "screen that guides you". That is, the evaluation unit 13 recognizes the classification of the target article prior to the shooting when the target user takes a picture of the target article, and the recognized classification belongs to the tablet terminal having the above-mentioned three characteristics. If this is the case, the terminal 2 is displayed with a screen that guides the housing to be photographed from the front while the system-related information is displayed on the display.

When the button B8 on the screen G8 is operated, the screen corresponding to FIG. 6B is displayed, and the target user takes a picture. The captured image data is generated according to the shooting, the captured image data is transmitted from the terminal side control unit 10 to the evaluation unit 13, and the evaluation unit 13 acquires the captured image data.

As described above, in the captured image data acquisition process, when the target deepest classification is "smartphone (article classification)> iOS (article classification)", the system-related information is displayed on the touch screen and the housing is viewed from the front. You will be guided to be photographed. Then, when the target user takes a picture according to the instruction, one shot image data in which the image of the smartphone (target article) in which the system-related information is reflected on the touch screen is generated, and the evaluation unit 13 generates this. To get.

The captured image data acquisition process when the target deepest classification is "smartphone (article classification)> iOS (article classification)" has been described above, but for articles with the same characteristics as smartphones, captured images are captured by the same method. Data acquisition process is executed. Goods having the same characteristics as smartphones are, for example, tablet terminals excluding smartphones (however, those that can be purchased by installment payment).

<When the target deepest classification is "bag (article classification)> brand B1 (article classification)">
Next, the captured image data acquisition process when the target deepest classification is "bag (article classification)> brand B1 (article classification)" will be described. In this case, the target article belongs to the bag as a major category, but the bag generally has the following characteristics.
(1) While the model number as characters may not be recorded on the article, the model number can be determined from the appearance of the article.
(2) It may be fake, and it is important whether the article is genuine or not in the assessment.
In other words, the bag may not have the model number as characters recorded on the article, but the model number can be determined from the appearance of the article, and it may be fake, so whether the article is genuine or not for evaluation. It is an article that has two characteristics: what is important.

Regarding (1), the model number may be recorded on the bag by engraving, printing, or other means, but the model number may not be recorded. In particular, depending on the brand, there are cases where the model number is not recorded uniformly on the bags provided by that brand. On the other hand, with respect to a bag, the model number can generally be determined by the appearance characteristics when the bag is viewed from the front. Regarding (2), there are cases where the bag is fake, and it is important to determine the authenticity at the time of assessment. Normally, the authenticity is judged at the time of assessment. In general, the authenticity determination is performed by using the authenticity determination target displayed on the bag. The authenticity determination target is, for example, a logo recorded on an article, a pattern, a mark, a characteristic planar or three-dimensional shape, or the like. In some cases, the entire article (for example, the three-dimensional shape of the entire article) is subject to authenticity determination instead of the portion of the article.

When the target deepest classification is "bag (article classification)> brand B1 (article classification)", the evaluation unit 13 acquires the article shooting method-related data corresponding to the target deepest classification from the article photography method database, and the acquired article. The following processing is executed based on the shooting method related data. That is, the evaluation unit 13 causes the terminal side control unit 10 to display the screen G9 of FIG. 9 on the touch screen 4 instead of the screen G6A of FIG. 6 (A). The screen G9 is a screen for instructing the shooting so that the entire front surface of the bag is captured and guiding (explaining) the shooting procedure. The reason for having the target user take a picture so that the entire front of the bag is taken is that the appearance when the bag is taken from the front can be most effectively used to identify the model number of the bag, and the bag is taken from the front. This is because the elements related to the bag, which are sometimes reflected, can be most effectively used to determine the authenticity of the bag.

As shown in FIG. 9, at the upper part of the screen G9, a sentence instructing to take a picture so that the entire front surface of the bag is captured is displayed. Further, on the screen G9, an image showing the appearance of the bag as viewed from the front is displayed below the text. This image is an image for the user to imagine what kind of method should be taken, and is not limited to the content illustrated in FIG. 9 as a matter of course.

On the screen G9, an explanatory text explaining the shooting procedure is displayed below this image. Although omitted in FIG. 9, the description contains information that the user should be aware of and should be aware of in order to capture the entire front surface of the bag. In addition, the description reflects that the brand of the bag is brand B1.

The screen G9 is a "screen that guides the appearance of the target article to be photographed so that the generated photographed image data can be used for recognizing the model number" and "generated photographed image data" in the scope of the patent claim. "Screen that guides the appearance of the target article to be photographed so that the data can be used to determine the authenticity of the target article" and "The generated photographed image data can be used to recognize the model number and is used to determine the authenticity. It corresponds to "a screen that guides the appearance of the target article to be photographed so that the data becomes possible". That is, when the target user takes a picture of the target article, the evaluation unit 13 recognizes the classification of the target article prior to the shooting, and the recognized classification is the classification to which the article having two characteristics belongs. A screen for guiding the appearance of the target article to be photographed is displayed on the terminal 2 so that the generated photographed image data can be used for recognizing the model number and for determining the authenticity.

When the button B9 on the screen G9 is operated, the screen corresponding to FIG. 6B is displayed, and the user takes a picture. The captured image data is generated according to the shooting, the captured image data is transmitted from the terminal side control unit 10 to the evaluation unit 13, and the evaluation unit 13 acquires the captured image data.

As described above, in the captured image data acquisition process, when the target deepest classification is "bag (article classification)> brand B1 (article classification)", the evaluation unit 13 guides the entire front surface of the bag to be photographed. .. Then, when the target user takes a picture according to the instruction, one photographed image data in which the image of the front surface of the bag is recorded is generated, and the evaluation unit 13 acquires this. The shooting image data acquisition process when the target deepest classification is "bag (article classification)> brand B1 (article classification)" has been described above, but for articles with the same characteristics as the bag, the images are taken by the same method. Image data acquisition processing is executed. Articles having similar characteristics to bags are, for example, shoes and other branded products other than bags.

The above is the captured image data acquisition process executed by the evaluation unit 13 and the terminal side control unit 10. As described above, as a result of the captured image data acquisition process, the article photographing method according to the target deepest classification is guided, and (ideally) the target article is photographed by the method according to the target deepest classification. Image data is generated, and the evaluation unit 13 acquires the generated captured image data.

After the captured image data acquisition process, the evaluation unit 13 executes the assessment process. The assessment process will be described in detail below. Regarding the assessment process, the evaluation unit 13 executes the assessment process according to the deepest classification of the target. Based on this, below, the case where the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)" and the target deepest classification is "smartphone (article classification)> iOS (article classification)". ) ”And the case where the target deepest classification is“ bag (article classification)> brand B1 ”, the processing of the evaluation unit 13 will be described.

<When the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)">
First, the processing of the evaluation unit 13 when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)" will be described. As described above, in this case, the evaluation unit 13 acquires the captured image data generated by photographing the entire area of the display and the keyboard with the system-related information displayed on the display.

First, the evaluation unit 13 executes the expected image determination process. The expected image determination process determines whether or not the content of the captured image data acquired by the evaluation unit 13 is appropriate for normally performing the processing performed using the subsequent captured image data. It is a process to do. For example, the evaluation unit 13 photographs when the target article is not photographed in the expected manner (for example, when the target article is not photographed from the expected viewpoint or when the image of the target article is abnormally small). It is determined that the content of the image data is not appropriate. Further, for example, the evaluation unit 13 determines that the content of the captured image data is not appropriate when the image of the captured image data is blurred to the extent that the subsequent processing cannot be normally executed.

The expected image determination process is performed using, for example, the following model prepared for each type of deepest classification. The model inputs the captured image data, performs various image processing on the input captured image data, and indicates whether the content of the input captured image data is normal (even a value indicating the possibility of normal content). Good) is output. All existing image processing techniques can be applied to the model, and the model may be learned by a predetermined machine learning method (for example, deep learning).

When it is determined that the content of the captured image data is not appropriate, the evaluation unit 13 executes the corresponding process. For example, as a corresponding process, the evaluation unit 13 causes the terminal side control unit 10 to display a screen on the touch screen 4 for urging the photographing of the target article to be repeated.

On the other hand, when it is determined that the content of the captured image data is appropriate, the evaluation unit 13 executes the character recognition process. The character recognition process is a process of recognizing a character image (in this example, an image of system-related information) included in the image of the target article. In the character recognition process, the evaluation unit 13 analyzes the captured image data by image processing and identifies the image of the target article from the image recorded in the captured image data. Next, the evaluation unit 13 analyzes the captured image data by image processing, and identifies an image of system-related information (an image of characters included in the image of the target article recorded in the captured image data) from the image of the target article. Next, the evaluation unit 13 analyzes the image of the system-related information by the optical character recognition process, and recognizes the character group indicated by the image of the system-related information.

Next, the evaluation unit 13 executes the model number recognition process. The model number recognition process is a process of recognizing a model number by recognizing characters on an image of system-related information. In the model number recognition process, the evaluation unit 13 identifies a character string indicating the model number from the character group indicated by the image of the system-related information based on the result of the character recognition process, and recognizes the model number. For example, in system-related information, for example, combinations of item names and item values are usually arranged side by side in a list. Based on this, the evaluation unit 13 identifies a character string (for example, a system model, a model, a model, etc.) used as an item name of a model number from the character group shown in the image of system-related information, and the specified character string. The item value associated with is recognized as a model number. For example, the character string is specified by a character string search using text data as a key.

Next, the evaluation unit 13 executes the unique number recognition process. The unique number recognition process is a process of recognizing a model number by recognizing characters on an image of system-related information. In the unique number recognition process, the evaluation unit 13 identifies a character string indicating the unique number from the character group shown by the image of the system-related information based on the result of the character recognition process, and recognizes the unique number. For example, the evaluation unit 13 identifies a character string (for example, a serial number or a serial number) used as an item name of a unique number from a character group shown by an image of system-related information, and associates it with the specified character string. Recognize the item value as a unique number.

Next, the evaluation unit 13 executes the spec recognition process. The spec recognition process is a process of recognizing specifications for a predetermined element (processor type and total number of memories in this example) by recognizing characters for an image of system-related information. In the spec recognition process, the evaluation unit 13 identifies a character string indicating the processor type and the total number of memories from the character group indicated by the image of the system-related information based on the result of the character recognition process, and recognizes these. For example, the evaluation unit 13 identifies a character string used as an item name of the processor type and the total number of memories from the character group shown in the image of the system-related information, and each associated with each specified character string. Recognize the item value as the processor type and the total number of memories.

Next, the evaluation unit 13 executes the state recognition process. The state recognition process is a process of recognizing a state related to the appearance of the target article by image analysis of the image of the target article recorded in the photographed image data, and more specifically, the target article recorded in the photographed image data. This is a process of analyzing an image to recognize a state related to the appearance of a part including the front of the display of the target article. In particular, in the present embodiment, the evaluation unit 13 derives the article state level of the target article based on the photographed image data (that is, deriving the article state level corresponds to recognizing the state regarding the appearance of the target article). .. The article condition level is how close the appearance of the article is to new (how much, considering the condition of factors related to deterioration such as scratches, dirt, dents, wear, and missing parts. It is a level that indicates whether the deterioration is small). In the present embodiment, the value of the article state level is from the level L5 indicating that the state is the closest to the new item (the state with the smallest deterioration) to the level indicating the state farthest from the new item (the state with the largest deterioration). Five values up to L1 are prepared.

In particular, in this example, the target article is a notebook computer, and the photographed image data includes images of the front of the display of the notebook computer and the keyboard. The evaluation unit 13 derives the article state level by reflecting the state of factors related to deterioration such as scratches (including cracks in the display), dirt, dents, wear, and defective parts of the display and keyboard. The evaluation unit 13 derives the article state level by the existing image processing. The data required to execute the article status level is prepared in advance. The necessary data is, for example, template data for each model number when pattern matching using template data corresponding to the model number of the article is executed, and image processing based on the background subtraction method according to the model number is executed, for example. In this case, it is the background image data for each model number. Further, at least a part of the state recognition processing may be performed using a machine-learned model.

Next, the evaluation unit 13 executes the fraud possibility investigation process. The fraud possibility investigation process is a process of investigating the possibility of fraudulent use of this service by using an individual number. In the fraud possibility investigation process, the evaluation unit 13 refers to the usage history database. The usage history database is a database that manages the usage history of this service (not limited to the usage history of the target user), and each record is at least the user identification information of the user who used this service and the target of assessment. Includes the unique number of the item that has become. That is, in the usage history database, the user identification information and the unique number are managed in association with each case in which this service has been used in the past. The usage history database includes "data managed by associating the unique number of the article with the user identification information of the user who owned the article at least at one time in the past" and "the article evaluated in the past". Corresponds to "data that manages the unique number of the article in association with the user identification information of the user who owned the article at the time of evaluation".

After referring to the usage history database in the fraud possibility investigation process, the evaluation unit 13 determines whether or not there is a record having the same unique number as the unique number of the target article in the usage history database. There may be no such record, or one or more such records. The existence of such a record in the usage history database means that this service has been used for the target article in the past. If no such record exists in the usage history database, the evaluation unit 13 ends the fraud possibility investigation process and executes the subsequent valuation amount derivation process.

On the other hand, when one or more such records exist in the usage history database, the evaluation unit 13 determines whether or not the user identification information of the target user and the user identification information of each record match. When the user identification information of a certain record and the user identification information of the target user are different, it means that a user different from the target user has used this service for the target article as an assessment target in the past. There is a possibility that you are trying to use this service for goods owned by others.

If there are a plurality of records having the same unique number as the unique number of the target article in the usage history database, the evaluation unit 13 inputs the user identification information having a value different from the user identification information of the target user. If there is a record including the record, it is determined that the user identification information of the target user and the user identification information of each record do not match. However, when the value of the user identification information included in the most recently generated record and the value of the user identification information of the target user are different, the evaluation unit 13 determines the user identification information of the target user and the user identification information of each record. It may be configured to determine that does not match.

When the user identification information of the target user and the user identification information of each record do not match, the evaluation unit 13 executes the corresponding process. For example, the evaluation unit 13 executes a process of notifying the operator as a corresponding process. Further, for example, the evaluation unit 13 controls the terminal side control unit 10 to notify that a person other than the target user has used this service in the past for the same article, and whether the target article is the property of the target user. Please confirm. However, the illustrated process is merely an example, and the evaluation unit 13 may naturally execute another process.

In the present embodiment, the usage history database is a database that manages the usage history of this service, but it may also be a database that also manages the usage history of similar services other than this service. Further, although the usage history database is stored in the server 3, the usage history database may be stored in a device other than the server 3.

Next, the evaluation unit 13 executes the valuation amount derivation process. The valuation amount derivation process is a process for deriving the valuation amount. In the valuation amount derivation process, the evaluation unit 13 refers to the valuation amount table corresponding to the target deepest classification (in this example, "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)"). The valuation amount table for the deepest classification of the target is the value that can be taken by the model number, the value that can be taken by the article state level (level L1 to level L5 in this embodiment), the value that can be taken by the processor type, and the total number of memories. It is a table in which the reference valuation amount is associated with each combination with the obtained value.

Hereinafter, the combination of the model number, the article state level, the processor name, and the total number of memories is referred to as an "evaluation combination". In the valuation amount table, the value of the reference valuation amount associated with a certain valuation combination is a value that reflects the value of each element of the valuation combination. The reference assessment amount is basically determined by the model number, and the standard amount is lower as the article condition level is smaller (= the greater the deterioration of the target article) and lower as the processor performance is lower. , It is set by adjusting so that the smaller the total number of memories is, the lower it is. As a matter of course, the reference amount may be adjusted so that the larger the article state level (= the smaller the deterioration of the target article), the higher the processor performance, and the larger the total number of memories, the higher the value.

The evaluation unit 13 acquires a reference valuation amount associated with the valuation combination for the target article in the valuation amount table, and uses this as the valuation amount.

The above is the assessment process executed by the evaluation unit 13 when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)". The order of processing in the assessment processing is not limited to the order exemplified in this embodiment. As described above, according to the present embodiment, in addition to the state related to the appearance of the target article, the characters (model number, unique number, specifications) recognized by the character recognition targeting the image of the system-related information (character image). ) Is reflected in the assessment (evaluation of the article), so the target article can be assessed from multiple different perspectives. In particular, in the present embodiment, in view of the fact that the specifications affect the assessed amount (affects the evaluation), the specifications are reflected and the evaluation unit 13 assesses the target article, so that it is more accurate in that respect. The target article can be assessed.

At that time, the recognition of the state regarding the appearance of the target article and the recognition of the characters (model number, specifications, unique number) by the character recognition are performed based on the common photographed image data. Therefore, the target user may take a picture of the target article when evaluating the target article, for example, inputting a model number, a unique number, and a spec in a predetermined user interface, and selecting a model number, a unique number, and a spec. There is no need. In particular, in the present embodiment, the evaluation unit 13 performs the recognition of the state regarding the appearance of the target article and the recognition of the characters (model number, specifications, unique number) by the character recognition based on the captured image data common to them. For this reason, the user wants to generate shooting image data used for recognizing the appearance of the target article (notebook computer) and shooting image data used for recognizing the model number, unique number, and specifications. There is no need to separate the shooting from the shooting, and there is less work for the user in that respect as well. That is, according to the present embodiment, it is possible to evaluate an article from a plurality of different viewpoints while reducing the work of the user.

<When the target deepest classification is "smartphone (article classification)> iOS (article classification)">
Next, the processing of the evaluation unit 13 when the target deepest classification is “smartphone (article classification)> iOS (article classification)” will be described. As described above, in this case, the evaluation unit 13 acquires the captured image data generated by photographing the housing from the front while the system-related information is displayed on the touch screen.

The evaluation unit 13 sequentially executes expected image determination processing, character recognition processing, model number recognition processing, unique number recognition processing, state recognition processing, and fraud possibility investigation processing. These processes are performed in the same manner as in the case where the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)". In particular, in the unique number acquisition process, the evaluation unit 13 acquires the IMEI as a unique number. Regarding the state recognition process, in this example, the target article is a smartphone, and the captured image data includes an image of the front surface of the housing including the entire area of the touch screen. The evaluation unit 13 derives the article state level on the front surface of the housing by reflecting the state of elements related to deterioration such as scratches (including cracks on the touch screen), dirt, dents, wear, and missing parts.

In this example, the model number acquisition process is "a process of recognizing a model number by recognizing characters for an image of system-related information". Further, the unique number recognition process is "a process of recognizing a unique number by recognizing characters for an image of system-related information". Further, the state recognition process is "a process of image analysis of the image of the target article recorded in the captured image data to recognize the state regarding the appearance of the portion including the front surface of the display of the target article".

After the fraud possibility investigation process, the evaluation unit 13 executes the payment status recognition process. The payment status recognition process is "a process of making an inquiry using the recognized unique number and recognizing the payment status of the target article". The payment status confirmation process will be described in detail below. In the following description, the IMEI (unique number) acquired in the unique number acquisition process is particularly referred to as "target IMEI".

In the payment status recognition process, the evaluation unit 13 inquires about the payment status of the target IMEI to the payment status management server connected to the network N. The inquiry is made by transmitting data in a predetermined format including the target IMEI (for example, request data including the target IMEI in the query). In the present embodiment, the "payment status" refers to whether or not the target article (smartphone in this example) was purchased by installment, if it was purchased by installment, whether or not it is currently being paid, and whether or not it is currently being paid. It means whether or not there was a delay in payment in the past. The payment status management server is a server device that manages the payment status together with the IMEI in the database, and has a function of responding to the payment status information indicating the payment status for the IMEI in response to the payment status inquiry for the IMEI. ing.

After inquiring about the payment status of the target IMEI, the evaluation unit 13 acquires the payment status information about the target IMEI from the payment status management server and recognizes the payment status. That is, the evaluation unit 13 pays in the past regardless of whether the smartphone as the target item was purchased by installment, whether it is currently being paid if it is purchased by installment, and whether it is currently being paid. Recognize if there was a delay in.

Next, the evaluation unit 13 executes the valuation amount derivation process. In this example, the evaluation unit 13 refers to the valuation amount table corresponding to the target deepest classification. The valuation amount table corresponding to the target deepest classification is a table in which the reference valuation amount is associated with each combination of the value that can be taken by the model number and the value that can be taken by the article state level. The evaluation unit 13 acquires a reference assessment amount corresponding to the combination of the model number and the article condition level of the target article in the assessment amount table. Next, the evaluation unit 13 adjusts the acquired reference assessment amount based on the payment status of the target article, and sets the adjusted amount as the final assessment amount. Adjustments are made so that if the target item (smartphone in this example) is purchased by installment and payment is being made at this time, the assessed amount will be lower, and if payment has been delayed in the past, It is done so that the assessed amount is low. This takes into account the possibility of delays in payment of lease payments. However, the adjustment method is not limited to the one illustrated in the present embodiment, and for example, the adjustment may be made in consideration of only the delay of the past payment.

The above is the assessment process executed by the evaluation unit 13 when the target deepest classification is “smartphone (article classification)> iOS (article classification)”. The order of processing in the assessment processing is not limited to the order exemplified in this embodiment. As described above, according to the present embodiment, in addition to the state related to the appearance of the target article, the characters (model number, IMEI) recognized by the character recognition targeting the image of the system-related information (character image) are reflected. Since the assessment (evaluation of the article) is performed, the target article can be assessed from a plurality of different viewpoints. In particular, in the present embodiment, in view of the possibility that the target article was purchased by installment payment, the evaluation unit 13 assesses the target article by reflecting the payment status, and therefore, in that respect, the target article is more accurately targeted. You can assess the goods.

At that time, the recognition of the state regarding the appearance of the target article and the recognition of the characters (model number, unique number) by the character recognition are performed based on the common photographed image data. Therefore, the target user may take a picture of the target article when evaluating the target article, and does not need to input a model number or IMEI or select a model number or IMEI in a predetermined user interface, for example. In particular, in the present embodiment, the evaluation unit 13 performs the recognition of the state regarding the appearance of the target article and the recognition of the character (model number, IMEI) by the character recognition based on the captured image data in common. For this reason, the user performs shooting for generating captured image data used for recognizing the state of the target article (smartphone) and shooting for generating captured image data used for recognizing the model number and the unique number. There is no need to do it separately, and there is less work for the user in that respect as well. That is, according to the present embodiment, it is possible to evaluate an article from a plurality of different viewpoints while reducing the work of the user.

<When the target deepest classification is "bag (article classification)> brand B1">
Next, the processing of the evaluation unit 13 when the target deepest classification is “bag (article classification)> brand B1” will be described. As described above, in this case, the evaluation unit 13 has acquired the photographed image data generated by photographing the entire front surface of the bag.

First, the evaluation unit 13 executes the expected image determination process. Next, the evaluation unit 13 executes an image analysis process for model number recognition. The model number recognition image analysis process corresponds to "a process of image-analyzing an image of a target article and recognizing the model number of the target article". The image analysis here means image processing other than "character recognition for a character image". Hereinafter, an example of the image analysis process for model number recognition will be described.

First, the evaluation unit 13 recognizes that the target article is a bag and the brand of the bag based on the target deepest classification (the deepest classification of the target article). The server-side storage unit 14 stores a database in which template data (an image showing a front view of the bag and template data to be compared) for each model number are registered for each of the bag brands. The evaluation unit 13 identifies and recognizes the model number by performing template matching using each of the template data corresponding to the brand of the target article on the photographed image data.

Note that template matching is already performed after preprocessing including noise removal for captured image data and size / angle correction (however, size / angle correction may be performed on the template data). (For example, template matching using template data holding pixel values, chamfer matching, active search using histogram information) is appropriately executed. However, the method of specifying the model number using the photographed image data is not limited to the illustrated method. For example, it may be a method of using feature amount matching or a combination of template matching and feature amount matching. Further, for example, a model may be used in which the captured image data is used as one of the inputs and the corresponding model number (or the possibility of corresponding to each model number) is output. In this case, the model can be a machine-learned model by a predetermined machine learning method (for example, deep learning).

Next, the evaluation unit 13 executes the authenticity determination process. The authenticity determination process is "a process of image-analyzing an image of a target article to determine the authenticity of the target article". Hereinafter, an example of the authenticity determination process will be described. In the authenticity determination process, for example, the evaluation unit 13 executes the following process. For example, when the image of the front of the bag recorded in the captured image data includes an image of the logo, the evaluation unit 13 determines the model number (the model number recognized by the image number recognition processing for model number recognition) by the logo recorded as an image in the captured image data. = The photographed image data is analyzed from the viewpoint of whether or not the target article is genuine as the logo of the bag (model number of the target article), and it is determined whether or not the target article is genuine. The analysis of the captured image data is performed from various viewpoints. For example, the analysis of the captured image data is performed by determining the validity of the shape of the logo, the validity of the color of the logo, the validity of the position of the logo, and the like.

The validity of the position of the logo means whether or not the position where the logo is attached matches the real one. The validity of the shape and position of the logo can be determined, for example, by pattern matching using template data corresponding to a real logo prepared in advance, or feature quantity matching. Further, the validity of the color of the logo can be determined by, for example, analysis of a histogram of color components or analysis of the distribution of each color component in an image. In the determination of whether or not the target article is genuine based on the analysis of the photographed image data, for example, the photographed image data is used as one of the inputs as an actual process, and the information indicating whether or not the object is genuine (or the possibility of being genuine). A model that outputs (information indicating) is prepared, and this model is used and executed. In this case, the model can be a machine-learned model by a predetermined machine learning method (for example, deep learning).

Although the authenticity determination process using the logo has been described above, various existing techniques can be used for the authenticity determination. In particular, instead of the logo or in addition to the logo, a pattern, a mark, a characteristic planar or three-dimensional shape, or the like may be used for authenticity determination processing. Also, regarding the authenticity determination processing other than the bag, the photographed image data is image-analyzed by an appropriate method according to the article and the authenticity determination target, and it is determined whether or not the image is genuine.

When it is determined in the authenticity determination process that the target article is not genuine, the evaluation unit 13 executes the corresponding process. For example, the evaluation unit 13 notifies the operator that the target article may not be genuine. According to this, the operator can take measures such as confirming the captured image data in more detail. In the present embodiment, when it is determined in the authenticity determination process that the target article is not genuine, the evaluation unit 13 does not derive the following assessed amount. However, the evaluation unit 13 may be configured to derive the assessed amount as a fake. In any case, the evaluation unit 13 assesses (evaluates) the target article by reflecting the result of the authenticity determination.

Next, the evaluation unit 13 executes the state recognition process. Regarding the state recognition process, in this example, the target article is a bag, and the photographed image data records an image of the entire front surface of the bag. The evaluation unit 13 performs image processing on the photographed image data, and derives an article state level on the front surface of the bag by reflecting the state of elements related to deterioration such as scratches, stains, dents, wear, and missing parts.

Next, the evaluation unit 13 executes the valuation amount derivation process. In the valuation amount derivation process according to this example, the evaluation unit 13 refers to the valuation amount table corresponding to the target deepest classification. The valuation amount table corresponding to the target deepest classification is a table in which the reference valuation amount is associated with each combination of the value that can be taken by the model number and the value that can be taken by the article state level. The evaluation unit 13 acquires a reference valuation amount associated with the combination of the model number and the article state level of the target article in the valuation amount table, and uses this as the valuation amount.

The above is the assessment process executed by the evaluation unit 13 when the target deepest classification is "bag (article classification)> brand B1 (article classification)". The order of processing in the assessment processing is not limited to the order exemplified in this embodiment. As described above, according to the present embodiment, in addition to the state regarding the appearance of the target article, the model number recognized by the image analysis targeting the image of the target article and the image of the target article are targeted. Since the evaluation (evaluation) of the target article is performed by reflecting the result of the determination of authenticity, the target article can be assessed from a plurality of different viewpoints. In particular, in the present embodiment, in view of the fact that whether or not the product is genuine is important for the assessment, the authenticity of the target article is determined, and the result of the authenticity determination is reflected and the evaluation unit 13 assesses the target article. Therefore, in that respect, the target article can be assessed more accurately.

At that time, the recognition of the state regarding the appearance of the target article, the recognition of the model number by the image analysis, and the authenticity determination by the image analysis are performed based on the common photographed image data. Therefore, the target user may take a picture of the target article when assessing the target article, and does not need to perform work such as inputting a model number or providing information for authenticity determination in a predetermined user interface. In particular, in the present embodiment, the target user takes a picture for generating a photographed image data used for recognizing a state regarding the appearance of the target article (bag) and a photograph for generating a photographed image data used for recognizing a model number. It is not necessary to perform the shooting separately for generating the shot image data used for the authenticity determination, and the user's work is also small in that respect. That is, according to the present embodiment, it is possible to evaluate an article from a plurality of different viewpoints while reducing the work of the user.

The assessment process has been described above for a plurality of cases. After the valuation amount is derived by the valuation process, as described above, the service provider purchases the target goods at the valuation amount with the consent of the target user, and the money equivalent to the valuation amount is provided to the target user. The target goods are leased to the target user on condition that the lease fee is paid.

Next, the information processing method by the server 3 (information processing device) will be described using a flowchart. FIG. 10 is a flowchart showing an operation example of the server 3. As shown in FIG. 10, the evaluation unit 13 of the server 3 acquires the photographed image data generated by the target article being photographed by the target user from the terminal 2 via the network N (step SA1).

Next, the evaluation unit 13 of the server 3 analyzes the image of the target article recorded in the photographed image data to recognize the state regarding the appearance of the target article, and at the same time, characterizes the image of the character included in the image of the target article. At least one of a process of recognizing, a process of image-analyzing the image of the target article to recognize the model number of the target article, and a process of image-analyzing the image of the target article to determine the authenticity of the target article is executed. (Step SA2). Next, the evaluation unit 13 of the server 3 evaluates the target article by reflecting the state regarding the appearance of the recognized target article and at least one of the recognized character, the recognized model number, and the result of the determination of authenticity (step SA3). ..

Although one embodiment of the present invention has been described above, the above-described embodiment is merely an example of the embodiment of the present invention, whereby the technical scope of the present invention is limitedly interpreted. It should not be done. That is, the present invention can be implemented in various forms without departing from its gist or its main features.

For example, in the above embodiment, the present invention can be applied to a system that simply presents the derived valuation amount, not a system that purchases the target article with the valuation amount derived by the evaluation unit 13. Further, for example, the present invention can be applied to a system in which the target goods purchased by the service provider are delivered from the target user to the service provider by a predetermined means, instead of being kept in the hands of the user by leasing. ..

Further, the evaluation of the target article is not limited to deriving the monetary value, and for example, the evaluation unit 13 may be configured to rank the target article.

Further, the information recognized as characters by character recognition from the captured image data is not limited to those exemplified in this embodiment. The information recognized as characters by character recognition from the captured image data may affect the evaluation of the target article by the evaluation unit 13. As an example, information that shows when the target article was manufactured (manufacturing date), information that shows how the target article was used, information that shows what kind of environment the target article was used in, etc. There may be.

Further, in the above embodiment, when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)", or "smartphone (article classification)> iOS (article classification)", In each case of "bag (article classification)> brand B1 (article classification)", the evaluation unit 13 acquires one photographed image data through the photographed image data acquisition process. However, this does not mean that the photographed image data to be acquired by the evaluation unit 13 in the evaluation of the target article (assessment in the above embodiment) is limited to "one".

For example, when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> maker MK1 (article classification)", the surface when the evaluation unit 13 closes the notebook computer is photographed and generated. The image data may be further acquired, and the captured image data may be further used to execute the state recognition process. Further, for example, when the target deepest classification is "smartphone (article classification)> iOS (article classification)", the evaluation unit 13 further acquires the photographed image data generated by photographing the back surface of the housing, and this photographed image data. It may be configured to execute the state recognition process by further using. Further, for example, when the target deepest classification is "bag (article classification)> brand B1 (article classification)", the evaluation unit 13 further acquires the photographed image data generated by photographing the back surface of the bag, and this photographed image data. May be further used to execute at least one of the state recognition process, the model number recognition image analysis process, and the authenticity determination process.

Further, in the system-related information (of course, other information may be used), the information to be photographed is arranged at a distance, and in order to photograph the information to be photographed, the image should be photographed twice or more. If necessary, of course, shooting is performed two or more times, and the evaluation unit 13 acquires two or more shot image data.

Further, although various screens displayed on the touch screen 4 of the terminal 2 have been described, the content of each screen is not limited to the described content.

In addition, the evaluation unit is for cases where the deepest target classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article classification)" and "smartphone (article classification)> iOS (article classification)". The configuration may be such that 13 does not execute the fraud possibility investigation process. On the contrary, when the target deepest classification is "bag (article classification)> brand B1 (article classification)" and the individual number can be obtained, the evaluation unit 13 may execute the fraud possibility investigation process.

Further, in the above embodiment, the medium on which the evaluation unit 13 displays various screens is the terminal 2. Regarding this point, the evaluation unit 13 may be a device having a display other than the terminal 2 and may be configured to display various screens on a device in which the target user can visually recognize the display.

In addition, when the target deepest classification is "notebook computer (article classification)> Windows (article classification)> manufacturer MK1 (article separation)" (including cases equivalent to this, of course), the evaluation unit 13 executes the spec recognition process. However, the assessment may be performed without reflecting the specifications. For example, when the target article is an article such as an electronic dictionary in which the specifications are not expected to change if the model numbers are the same, it is not necessary for the evaluation unit 13 to execute the process related to the specifications. In addition, when the target deepest classification is "smartphone (article classification)> iOS (article classification)" (including cases equivalent to this, of course), the evaluation unit 13 does not execute the payment status recognition process and reflects the payment status. It may be configured to make an assessment without doing so. In these cases, the target article has a display, and system-related information including at least the model number can be displayed on the display, and deterioration caused in a part including the front surface of the display affects the evaluation. It is an electronic device having the following two features. Then, the evaluation unit 13 acquires photographed image data generated by photographing the appearance of the target article including the front surface of the display while the system-related information is displayed on the display. The evaluation unit 13 performs an image analysis of the image of the target article recorded in the captured image data to recognize the state regarding the appearance of the portion including the front of the display of the target article, and the system recorded in the captured image data. The process of recognizing the model number is executed by recognizing characters for the image of the related information. The evaluation unit 13 evaluates the target article by reflecting the state regarding the appearance of the recognized portion including the front surface of the display of the target article and the recognized model number. Further, the evaluation unit 13 recognizes the classification (deepest classification) of the target article prior to the photographing when the target user takes a picture of the target article, and the recognized classification is an electron having the above-mentioned two characteristics. In the case of the classification to which the device belongs, the screen for guiding the part including the front of the display to be photographed is displayed on the terminal or the device visible to the target user while the system-related information is displayed on the display.

In addition, when the deepest target classification is "bag (article classification)> brand B1 (article classification)" (including cases equivalent to this, of course), the evaluation unit 13 makes an assessment without executing the authenticity determination process. good. In this case, the target article is an article having one feature that the model number as characters may not be recorded on the article, but the model number can be determined from the appearance of the article, and the evaluation unit 13 has the target article. The process of acquiring the photographed image data generated by photographing the appearance of the target article and analyzing the image of the target article recorded in the photographed image data to recognize the state regarding the appearance of the target article, and the image of the target article. The process of recognizing the model number of the target article by image analysis is executed, and the target article is evaluated by reflecting the state regarding the appearance of the recognized target article and the recognized model number. Further, the evaluation unit 13 recognizes the classification of the target article prior to the photographing when the target user takes a picture of the target article, and the recognized classification is the classification to which the article having one feature belongs. A screen for guiding the appearance of the target article to be photographed so that the generated photographed image data becomes data that can be used for recognizing the model number is displayed on the terminal 2 or a device that can be visually recognized by the target user.

Further, in the above embodiment, the evaluation unit 13 is configured to derive the assessed amount using the assessed amount table, but the method for deriving the assessed amount is not limited to the illustrated method. As an example, the evaluation unit 13 may derive the assessed amount by using a calculation formula having various elements used for deriving the assessed amount as parameters.

Further, in the above embodiment, the object to be the target of character recognition is basically system-related information, but the object to be the target of character recognition is not limited to the system-related information. For example, a name plate label (sometimes called a name plate sticker) attached to an electric appliance or the like may be used as an object for character recognition. In addition, character information recorded on the target article or an object attached to the target article by engraving, printing, distribution of a medium, or other means may be used as an object for character recognition.

Further, in the above embodiment, the terminal 2 is a smartphone, but the terminal 2 is not limited to a smartphone. For example, the terminal 2 may be a tablet terminal or a notebook computer having no terminal function.

1 Information processing system 2 Terminal 3 Server (information processing device)
13 Evaluation Department

Claims (15)

The photographed image data generated by the target article being photographed by the target user is acquired from the terminal via the network, and the target article is acquired from the terminal.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is equipped with an evaluation unit that derives the assessed amount of the target article by reflecting the recognized state regarding the appearance of the target article and at least one of the recognized characters, the recognized model number, and the result of the determination of authenticity.
The image of the character includes an image of the character indicating the unique number of the target article.
After the valuation amount is derived by the evaluation unit, the target article is purchased by the predetermined entity at the valuation amount with the consent of the target user, money equivalent to the valuation amount is provided to the target user, and the lease fee is charged. The subject article is leased to the subject user on condition of payment of
The target article is an article that may be purchased by installment payment.
The evaluation unit is responsible for deriving the assessed amount of the target article.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and the image of the characters included in the image of the target article is recognized as the target. Recognize the unique number of the article, make an inquiry using the recognized unique number, recognize the payment status of the target article, and
An information processing device for deriving an assessed amount of the target article by reflecting the recognized state of the appearance of the target article and the recognized payment status. The target article has a feature that a display is provided in a wide area on the front surface and system-related information including at least a model number and a unique number can be displayed on the display, a feature that the target article may be purchased by installment, and a feature of the display. It is a tablet terminal that has three characteristics that the deterioration that occurs in the part including the front affects the evaluation.
The evaluation unit
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the tablet terminal having the above three characteristics belongs. Displays a screen instructing the housing to be photographed from the front on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the housing of the target article, which is a tablet terminal, is photographed from the front and the generated image data is acquired.
A process of image-analyzing an image of the target article recorded in the captured image data to recognize a state regarding the appearance of a portion including the front of the display of the target article, and an image of the system-related information recorded in the captured image data. The process of recognizing the model number by recognizing the character of the target, the process of recognizing the unique number by recognizing the character of the image of the system-related information recorded in the captured image data, and the process of recognizing the unique number. Inquire about the item and execute the process of recognizing the payment status of the target item.
Claim 1 is characterized in that the valuation amount of the target article is derived by reflecting the state regarding the appearance of the recognized portion including the front of the display of the target article, the recognized model number, and the recognized payment status. The information processing device described. When the evaluation unit derives the valuation amount of the target article by reflecting the payment status, the valuation amount is low if the payment is delayed in the past when the target article is purchased by installment. Adjust to be
The information processing apparatus according to claim 1 or 2. The evaluation unit uses data for managing the unique number of the article in association with the user identification information of the user who owned the article at least at one time in the past, and is based on the recognized unique number. To investigate the possibility that the target article is not the property of the target user.
The information processing apparatus according to any one of claims 1 to 3. The evaluation unit recognizes an article evaluated in the past by using data that manages the unique number of the article in association with the user identification information of the user who owned the article at the time of evaluation. Investigate the possibility that the target article is not the property of the target user based on the unique number.
The information processing apparatus according to claim 4. The photographed image data generated by the target article being photographed by the target user is acquired from the terminal via the network, and the target article is acquired from the terminal.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is provided with an evaluation unit that evaluates the target article by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of authenticity determination.
The target article has two features: that it has a display and can display system-related information including at least a model number on the display, and that deterioration that occurs in a part including the front of the display affects the evaluation. It is an electronic device with features
The evaluation unit
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above two characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
The process of image-analyzing the image of the target article recorded in the captured image data to recognize the state of the appearance of the portion including the front of the display of the target article, and the system-related information recorded in the captured image data. Executes the process of recognizing the model number by recognizing characters for the image of
An information processing device for evaluating the target article by reflecting the state regarding the appearance of the recognized portion including the front surface of the display of the target article and the recognized model number. The photographed image data generated by the target article being photographed by the target user is acquired from the terminal via the network, and the target article is acquired from the terminal.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is provided with an evaluation unit that evaluates the target article by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of authenticity determination.
The target article has a display, and is capable of displaying system-related information including at least specifications for a model number and a predetermined element on the display, a feature that the specifications may be different even if the model number is the same, and a feature. It is an electronic device that has the three characteristics that deterioration that occurs in the part including the front of the display affects the evaluation.
The evaluation unit
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above three characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
A process of image-analyzing an image of the target article recorded in the captured image data to recognize a state regarding the appearance of a portion including the front of the display of the target article, and an image of the system-related information recorded in the captured image data. A process of recognizing the model number by recognizing characters as a target, and a process of recognizing specifications for a predetermined element by recognizing characters of the image of the system-related information recorded in the captured image data are executed. ,
Information characterized by evaluating the target article by reflecting the state regarding the appearance of the recognized portion including the front of the display of the target article, the recognized model number, and the specifications for the recognized predetermined element. Processing device. The system-related information includes a unique number and
The evaluation unit
The unique number is recognized by recognizing characters for the image of the system-related information recorded in the captured image data.
With respect to the article, the target article is based on the recognized unique number by using the data managed by associating the unique number of the article with the user identification information of the user who owned the article at least at one time in the past. Investigate the possibility that it is not the property of the target user
The information processing apparatus according to claim 6 or 7. The evaluation unit recognizes an article evaluated in the past by using data that manages the unique number of the article in association with the user identification information of the user who owned the article at the time of evaluation. Investigate the possibility that the target article is not the property of the target user based on the unique number.
The information processing apparatus according to claim 8. An information processing system including a terminal and an information processing device connected to the terminal via a network.
The information processing device is
The photographed image data generated by the subject article being photographed by the target user is acquired from the terminal via the network.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is equipped with an evaluation unit that derives the assessed amount of the target article by reflecting the recognized state regarding the appearance of the target article and at least one of the recognized characters, the recognized model number, and the result of the determination of authenticity .
The image of the character includes an image of the character indicating the unique number of the target article.
After the valuation amount is derived by the evaluation unit, the target article is purchased by the predetermined entity at the valuation amount with the consent of the target user, money equivalent to the valuation amount is provided to the target user, and the lease fee is charged. The subject article is leased to the subject user on condition of payment of
The target article is an article that may be purchased by installment payment.
The evaluation unit of the information processing apparatus determines the assessed amount of the target article when deriving the assessed amount.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and the image of the characters included in the image of the target article is recognized as the target. Recognize the unique number of the article, make an inquiry using the recognized unique number, recognize the payment status of the target article, and
Derivation of the assessed amount of the target article reflecting the recognized state of the appearance of the target article and the recognized payment status.
An information processing system characterized by this. An information processing system including a terminal and an information processing device connected to the terminal via a network.
The information processing device is
The photographed image data generated by the subject article being photographed by the target user is acquired from the terminal via the network.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is provided with an evaluation unit that evaluates the target article by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of authenticity determination.
The target article has two features: that it has a display and can display system-related information including at least a model number on the display, and that deterioration that occurs in a part including the front of the display affects the evaluation. It is an electronic device with features
The evaluation unit of the information processing apparatus
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above two characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
The process of image-analyzing the image of the target article recorded in the captured image data to recognize the state of the appearance of the portion including the front of the display of the target article, and the system-related information recorded in the captured image data. Executes the process of recognizing the model number by recognizing characters for the image of
The target article is evaluated by reflecting the state regarding the appearance of the recognized part including the front of the display of the target article and the recognized model number.
An information processing system characterized by this. An information processing system including a terminal and an information processing device connected to the terminal via a network.
The information processing device is
The photographed image data generated by the subject article being photographed by the target user is acquired from the terminal via the network.
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and at the same time.
Character recognition processing for the image of characters included in the image of the target article, image analysis of the image of the target article to recognize the model number of the target article, and image analysis of the image of the target article. At least one of the processes for determining the authenticity of the target article is executed.
It is provided with an evaluation unit that evaluates the target article by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of authenticity determination.
The target article has a display, and is capable of displaying system-related information including at least specifications for a model number and a predetermined element on the display, a feature that the specifications may be different even if the model number is the same, and a feature. It is an electronic device that has the three characteristics that deterioration that occurs in the part including the front of the display affects the evaluation.
The evaluation unit of the information processing apparatus
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above three characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
A process of image-analyzing an image of the target article recorded in the captured image data to recognize a state regarding the appearance of a portion including the front of the display of the target article, and an image of the system-related information recorded in the captured image data. A process of recognizing the model number by recognizing characters as a target, and a process of recognizing specifications for a predetermined element by recognizing characters of the image of the system-related information recorded in the captured image data are executed. ,
The target article is evaluated by reflecting the state regarding the appearance of the recognized part including the front of the display of the target article, the recognized model number, and the specifications for the recognized predetermined element.
An information processing system characterized by this. The first step in which the evaluation unit of the information processing device acquires the photographed image data generated by the target article being photographed by the target user from the terminal via the network.
The evaluation unit of the information processing apparatus analyzes the image of the target article recorded in the photographed image data to recognize the state regarding the appearance of the target article, and at the same time, an image of characters included in the image of the target article. Character recognition processing, image analysis of the target article to recognize the model number of the target article, and image analysis of the target article image to determine the authenticity of the target article. At least one of the processes is executed , and the assessed amount of the target article is determined by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of the determination of authenticity. Including the second step to derive
The image of the character includes an image of the character indicating the unique number of the target article.
After the valuation amount is derived by the evaluation unit, the target article is purchased by the predetermined entity at the valuation amount with the consent of the target user, money equivalent to the valuation amount is provided to the target user, and the lease fee is charged. The subject article is leased to the subject user on condition of payment of
The target article is an article that may be purchased by installment payment.
In the second step, the evaluation unit
The image of the target article recorded in the captured image data is image-analyzed to recognize the state of the appearance of the target article, and the image of the characters included in the image of the target article is recognized as the target. Recognize the unique number of the article, make an inquiry using the recognized unique number, recognize the payment status of the target article, and
Derivation of the assessed amount of the target article reflecting the recognized state of the appearance of the target article and the recognized payment status.
An information processing method characterized by that. The first step in which the evaluation unit of the information processing device acquires the photographed image data generated by the target article being photographed by the target user from the terminal via the network.
The evaluation unit of the information processing apparatus analyzes the image of the target article recorded in the photographed image data to recognize the state regarding the appearance of the target article, and at the same time, an image of characters included in the image of the target article. Character recognition processing, image analysis of the target article to recognize the model number of the target article, and image analysis of the target article image to determine the authenticity of the target article. At least one of the processes is executed, and the target article is evaluated by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of the determination of authenticity. Including 2 steps
The target article has two features: that it has a display and can display system-related information including at least a model number on the display, and that deterioration that occurs in a part including the front of the display affects the evaluation. It is an electronic device with features
In the second step, the evaluation unit
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above two characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
The process of image-analyzing the image of the target article recorded in the captured image data to recognize the state of the appearance of the portion including the front of the display of the target article, and the system-related information recorded in the captured image data. Executes the process of recognizing the model number by recognizing characters for the image of
The target article is evaluated by reflecting the state regarding the appearance of the recognized part including the front of the display of the target article and the recognized model number.
An information processing method characterized by that. The first step in which the evaluation unit of the information processing device acquires the photographed image data generated by the target article being photographed by the target user from the terminal via the network.
The evaluation unit of the information processing apparatus analyzes the image of the target article recorded in the photographed image data to recognize the state regarding the appearance of the target article, and at the same time, an image of characters included in the image of the target article. Character recognition processing, image analysis of the target article to recognize the model number of the target article, and image analysis of the target article image to determine the authenticity of the target article. At least one of the processes is executed, and the target article is evaluated by reflecting at least one of the recognized state regarding the appearance of the target article, the recognized character, the recognized model number, and the result of the determination of authenticity. Including 2 steps
The target article has a display, and is capable of displaying system-related information including at least specifications for a model number and a predetermined element on the display, a feature that the specifications may be different even if the model number is the same, and a feature. It is an electronic device that has the three characteristics that deterioration that occurs in the part including the front of the display affects the evaluation.
In the second step, the evaluation unit
When the target user takes a picture of the target article, the classification of the target article is recognized prior to the shooting, and the recognized classification is the classification to which the electronic device having the above three characteristics belongs. Displays a screen for guiding a part including the front of the display to be photographed on the terminal or a device visible to the target user while the system-related information is displayed on the display.
With the system-related information displayed on the display, the photographed image data generated by photographing the appearance of the object including the front of the display is acquired.
A process of image-analyzing an image of the target article recorded in the captured image data to recognize a state regarding the appearance of a portion including the front of the display of the target article, and an image of the system-related information recorded in the captured image data. A process of recognizing the model number by recognizing characters as a target, and a process of recognizing specifications for a predetermined element by recognizing characters of the image of the system-related information recorded in the captured image data are executed. ,
The target article is evaluated by reflecting the state regarding the appearance of the recognized part including the front of the display of the target article, the recognized model number, and the specifications for the recognized predetermined element.
An information processing method characterized by that.

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