Badge identification method and system, electronic equipment, storage medium and program product

Abstract

The invention provides a badge identification and classification method and system, an electronic device, a storage medium and a program product, and the method comprises the following steps: building a plurality of different posture outer contour models of a target person according to the historical image data of the target person, and obtaining the posture outer contour models of the target person according to the historical image data of the target person; anchoring a classification category corresponding to each posture outer contour model; the image pattern of the badge is obtained, and pattern outer contour information corresponding to the badge is obtained according to the image pattern; and matching the pattern outer contour information with each posture outer contour model to obtain the posture outer contour model with the highest matching degree with the badge, and taking the classification category corresponding to the posture outer contour model as the classification category of the badge. The badges can be classified efficiently and simply.

Description

Technical Field

[0001] The present invention relates to the field of image recognition, and in particular to a badge recognition and classification method, system, electronic device, readable storage medium and computer program product. Background Art

[0002] Badges of famous people are characterized by a large number and variety, and a long time span. For the needs of history popularization and historical learning and research, it is necessary to classify badges from different periods, but manual autonomous identification relies on the historical and cultural reserves of the personnel themselves, and there are defects such as inaccurate identification, incomplete process data, and lack of systematicity. In the process of using electronic equipment for intelligent identification, it was found that since the badges are made of specific materials, they are relatively abstract compared to the photos of the people, and their patterns cannot be well matched with the images of the people from the computer perspective. Therefore, a simple and effective solution is needed to solve the problem of badge identification and classification. Summary of the invention

[0003] The object of the present invention is to provide a badge recognition and classification method, system, electronic device, readable storage medium and computer program product to achieve efficient and concise classification of badges.

[0004] To achieve the above-mentioned purpose, the present invention provides a badge recognition and classification method, comprising the following steps: establishing a plurality of different body contour models of the target person according to the historical image data of the target person, and anchoring a classification category corresponding to each of the body contour models according to the historical image data of the target person; acquiring the image pattern of the badge, and acquiring the pattern contour information corresponding to the badge according to the image pattern; matching the pattern contour information with each of the body contour models to obtain the body contour model with the highest matching degree with the badge, and using the classification category corresponding to the body contour model as the classification category of the badge.

[0005] Optionally, obtaining the pattern outer contour information corresponding to the badge based on the image pattern specifically includes: obtaining a first Fourier descriptor corresponding to the pattern outer contour information of the badge based on the image pattern; matching the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge specifically includes: obtaining a second Fourier descriptor corresponding to the body outer contour model based on the body outer contour model of the target person; obtaining the body outer contour model with the highest matching degree with the badge based on the first Fourier descriptor and the second Fourier descriptor.

[0006] Optionally, obtaining the pattern outer contour information corresponding to the badge based on the image pattern specifically includes: calling a hollowing-out internal point algorithm to obtain a first pattern outer contour image corresponding to the badge; matching the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest degree of match with the badge specifically includes: calling a hollowing-out internal point algorithm to obtain a second outer contour image of the body outer contour model; obtaining the body outer contour model with the highest degree of match with the badge based on the first outer contour image and the second outer contour image.

[0007] Optionally, based on the historical image data of the target person, a number of different body contour models of the target person are established, specifically comprising: obtaining reconstructed material images of the target task from at least two perspectives in the historical image data of the target person; and reconstructing the body contour model based on the reconstructed material images.

[0008] Optionally, reconstructing the body contour model based on the reconstructed material images specifically includes: establishing a standard scale anchor model based on actual body size data of the target person; scaling a plurality of the reconstructed material images according to the standard scale anchor model so that the image features of the target task in the reconstructed material model are adapted to the standard scale model; and reconstructing the body contour model based on the scaled reconstructed material images.

[0009] Optionally, there is a correspondence between the classification category and the historical image data, and the correspondence is saved. After confirming the classification category corresponding to the badge, each time the pattern of the badge is captured, the historical image data corresponding to the classification category of the badge is retrieved and displayed.

[0010] To achieve the above-mentioned purpose, the present invention also provides a recognition and classification system, comprising: a first execution module, used to establish a plurality of different body contour models of the target person according to the historical image data of the target person, and anchor a classification category corresponding to each of the body contour models according to the historical image data of the target person; a second execution module, used to obtain the image pattern of the badge, and obtain the pattern contour information corresponding to the badge according to the image pattern; a third execution module, used to match the pattern contour information with each of the body contour models to obtain the body contour model with the highest matching degree with the badge, and use the classification category corresponding to the body contour model as the classification category of the badge.

[0011] To achieve the above-mentioned purpose, the present invention also provides an electronic device, comprising: a memory storing a computer program; a processor communicating with the memory and executing any one of the above-mentioned badge recognition and classification methods when the computer program is called; and a display communicating with the processor and the memory and used to display a GUI interaction interface related to the badge recognition and classification method.

[0012] To achieve the above object, the present invention further provides a readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-mentioned badge recognition and classification methods.

[0013] To achieve the above objective, the present invention further provides a computer program product, which, when executed by a processor, implements any of the above-mentioned badge recognition and classification methods.

[0014] The badge identification and classification method, system, electronic device, storage medium and program product provided by the present invention have the following beneficial effects:

[0015] The present invention provides a badge recognition and classification method, comprising the following steps: according to the historical image data of the target person, establishing a plurality of different body contour models of the target person, and anchoring a classification category corresponding to each body contour model according to the historical image data of the target person; obtaining the image pattern of the badge, and according to the image pattern, obtaining the pattern contour information corresponding to the badge; matching the pattern contour information with each body contour model to obtain the body contour model with the highest matching degree with the badge, and using the classification category corresponding to the body contour model as the classification category of the badge. The inventor has found that, since the image of the person on the badge is relatively abstract compared to carriers such as photos and pictures, its contour can still be used as an effective reference for classification, and since the body shape (mainly the head) of the target person changes with time, the image data of the target person in different periods are used as the material for extraction and comparison, and based on the extraction and comparison of the contour, badges of different forms can be effectively classified, and efficient and concise classification can be achieved.

[0016] The present invention also provides a recognition and classification system, which is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the recognition and classification system can use the image data of the target person at different periods as the material for extraction and comparison, and based on the extraction and comparison of the contours, can effectively classify badges of different forms, thereby achieving efficient and concise classification work.

[0017] The present invention also provides an electronic device, which is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the electronic device can use the image data of the target person at different periods as the material for extraction and comparison, and can effectively classify badges of different forms based on the extraction and comparison of contours, thereby achieving efficient and concise classification work.

[0018] The present invention also provides a readable storage medium, which is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the readable storage medium can use the image data of the target person at different periods as the material for extraction and comparison, and can effectively classify badges of different forms based on the extraction and comparison of contours, thereby achieving efficient and concise classification work.

[0019] The present invention also provides a computer program product, which is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the computer program product can use the image data of the target person at different periods as the material for extraction and comparison, and can effectively classify badges of different forms based on the extraction and comparison of contours, thereby achieving efficient and concise classification work. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a badge identification and classification method provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of a block structure of an electronic device provided by an embodiment of the present invention;

[0022] The accompanying drawings are denoted as follows:

[0023] 101 - processor; 102 - communication interface; 103 - memory; 104 - communication bus; 105 - display. DETAILED DESCRIPTION

[0024] In order to make the purpose, advantages and features of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the drawings are all in a very simplified form and are not drawn to scale, and are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In addition, the structure shown in the drawings is often a part of the actual structure. In particular, the emphasis of each drawing is different, and sometimes different scales are used.

[0025] It should be understood that when an element or layer is referred to as "on...", "connected to" other elements or layers, it can be directly on other elements or layers, connected to other elements or layers, or there can be intervening elements or layers. On the contrary, when an element is referred to as "directly on...", "directly connected to" other elements or layers, there is no intervening element or layer. Although the terms first, second, third, etc. can be used to describe various elements, components, regions, layers and / or parts, these elements, components, regions, layers and / or parts should not be limited by these terms. These terms are only used to distinguish an element, component, region, layer or part from another element, component, region, layer or part. Therefore, without departing from the teachings of the present invention, the first element, component, region, layer or part discussed below can be expressed as a second element, component, region, layer or part. Spatial relationship terms such as "under...", "below", "below", "above...", "above", "above", etc., can be used here for the convenience of description to describe the relationship between an element or feature shown in the figure and other elements or features. It should be understood that, in addition to the orientation shown in the figure, the spatial relationship terms are intended to include different orientations of the devices in use and operation. For example, if the device in the accompanying drawings is turned over, then, the elements or features described as "under...", "below", "below" will be oriented to be "on" other elements or features. The device can be oriented in addition (rotated 90 degrees or other orientations) and the spatial descriptors used herein are interpreted accordingly. The purpose of the terms used herein is only to describe specific embodiments and is not intended to be a limitation of the present invention. When used herein, the singular forms of "one", "one" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the term "include" is used to determine the presence of features, steps, operations, elements and / or parts, but does not exclude the presence or addition of one or more other features, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0026] The object of the present invention is to provide a badge recognition and classification method, system, electronic device, readable storage medium and computer program product to achieve efficient and concise classification of badges.

[0027] To achieve the above-mentioned purpose, the present invention provides a badge recognition and classification method, comprising the following steps: establishing a plurality of different body contour models of the target person according to the historical image data of the target person, and anchoring a classification category corresponding to each of the body contour models according to the historical image data of the target person; acquiring the image pattern of the badge, and acquiring the pattern contour information corresponding to the badge according to the image pattern; matching the pattern contour information with each of the body contour models to obtain the body contour model with the highest matching degree with the badge, and using the classification category corresponding to the body contour model as the classification category of the badge.

[0028] The inventors have found that, since the image of the person on the badge is relatively abstract compared to carriers such as photographs and pictures, its outline can still be used as an effective reference for classification, and since the body shape (mainly the head) of the target person changes over time, the image data of the target person at different periods can be used as the material for extraction and comparison. Based on the extraction and comparison of the outline, badges of different forms can be effectively classified, thereby achieving efficient and concise classification.

[0029] Specifically, the acquiring, according to the image pattern, the pattern outer contour information corresponding to the badge specifically includes:

[0030] According to the image pattern, obtaining a first Fourier descriptor corresponding to the pattern outer contour information of the badge;

[0031] The matching of the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge specifically includes:

[0032] According to the body contour model of the target person, obtaining a second Fourier descriptor corresponding to the body contour model;

[0033] The body contour model having the highest matching degree with the badge is obtained according to the first Fourier descriptor and the second Fourier descriptor.

[0034] The function of the Fourier descriptor is to extract and describe the contour information of the image, and it has the characteristics of translation, rotation, and scale invariance. Its essence is the transformation problem between the space and frequency domains. The contour information of the image is obtained by performing Fourier transform on the pixels in the image. Using the first Fourier descriptor and the second Fourier descriptor to align the frequency domain data dimension can better adapt to the contour adaptation execution logic from the processor's perspective and achieve accurate and efficient matching classification.

[0035] In another exemplary embodiment, the acquiring, according to the image pattern, the pattern outer contour information corresponding to the badge specifically includes:

[0036] Calling a hollowing-out internal point algorithm to obtain a first pattern outer contour image corresponding to the badge;

[0037] The matching of the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge specifically includes:

[0038] Calling a hollowing-out internal point algorithm to obtain a second outer contour image of the body outer contour model;

[0039] The body contour model having the highest matching degree with the badge is acquired according to the first contour image and the second contour image.

[0040] There are differences in the specific algorithms of the hollowing out interior point algorithm and the Fourier descriptor, but their functions are similar. Both of them extract the contour of the target image for research and adaptation. The hollowing out interior point algorithm can also adapt to the contour adaptation execution logic from the processor's perspective to achieve accurate and efficient matching and classification.

[0041] Furthermore, the method of establishing several different body contour models of the target person based on the historical image data of the target person specifically includes: obtaining at least two reconstruction material images of the target task from the historical image data of the target person; and reconstructing the body contour model based on the reconstruction material images. With such an arrangement, the three-dimensional body contour model can be reconstructed based on the obtained image data and the projection transformation calculation in different perspectives using the descriptive geometry principle.

[0042] Furthermore, the body contour model is reconstructed based on the reconstructed material images, specifically including: establishing a standard scale anchor model based on the actual body size data of the target person; scaling multiple reconstructed material images based on the standard scale anchor model so that the image features of the target task in the reconstructed material model are adapted to the standard scale model; and reconstructing the body contour model based on the scaled reconstructed material images. This is set up because the reconstructed material images of the target person may come from different scenes in the image, some are close-ups, some are mid-shots or distant shots, and the images of the target person extracted from different scene images have scale differences. In this case, a unified anchor standard should be established to scale the images of the target person of different sizes to convert them to the same size ratio dimension, thereby laying the foundation for more accurate reconstruction.

[0043] On the basis of classification, the present invention can also perform customized display based on AR scenes. For example, in the current viewing angle interface of a mobile phone or AR glasses, the badge is identified and the corresponding historical image data is displayed by classification. This will be conducive to multimedia display and more effectively applied to explanation or theoretical learning scenes. Based on this, the present invention further provides the following technical solution: there is a corresponding relationship between the classification category and the historical image data, and the corresponding relationship is saved. After confirming the classification category corresponding to the badge, each time the pattern of the badge is captured, the historical image data corresponding to the classification category of the badge is retrieved and displayed.

[0044] To achieve the above-mentioned purpose, the present invention also provides a recognition and classification system, comprising: a first execution module, used to establish a plurality of different body contour models of the target person according to the historical image data of the target person, and anchor a classification category corresponding to each of the body contour models according to the historical image data of the target person; a second execution module, used to obtain the image pattern of the badge, and obtain the pattern contour information corresponding to the badge according to the image pattern; a third execution module, used to match the pattern contour information with each of the body contour models to obtain the body contour model with the highest matching degree with the badge, and use the classification category corresponding to the body contour model as the classification category of the badge.

[0045] Since the identification and classification system is used to execute any of the above-mentioned badge identification and classification methods, the identification and classification system can use the image data of the target person at different periods as the material for extraction and comparison, and based on the extraction and comparison of the contours, can effectively classify badges of different forms, thereby achieving efficient and concise classification work.

[0046] Since the identification and classification system provided by the present invention and the badge identification and classification method described above belong to the same inventive concept, the identification and classification system provided by the present invention has all the advantages of the badge identification and classification method described above, and therefore the beneficial effects of the identification and classification system provided by the present invention will not be described one by one here.

[0047] To achieve the above object, the present invention also provides an electronic device, please refer to Figure 2 , Figure 2 FIG. 1 is a block diagram of an electronic device provided by an embodiment of the present invention. Figure 2 As shown, the electronic device includes:

[0048] A memory 103 storing a computer program;

[0049] A processor 101 is communicatively connected to the memory and executes any one of the above-mentioned badge recognition and classification methods when calling the computer program;

[0050] The display 105 is connected to the processor and the memory for displaying a GUI interaction interface related to the badge identification and classification method.

[0051] like Figure 2 As shown, the electronic device also includes a communication interface 102 and a communication bus 104, wherein the processor 101, the communication interface 102, and the memory 103 communicate with each other through the communication bus 104. The communication bus 104 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 104 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The communication interface 102 is used for communication between the above-mentioned electronic device and other devices.

[0052] The processor 101 referred to in the present invention may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 101 is the control center of the electronic device, and various interfaces and lines are used to connect various parts of the entire electronic device.

[0053] The memory 103 may be used to store the computer program. The processor 101 implements various functions of the electronic device by running or executing the computer program stored in the memory 103 and calling the data stored in the memory 103 .

[0054] The memory 103 may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0055] Since the electronic device is used to execute any of the above-mentioned badge recognition and classification methods, the electronic device can use the image data of the target person at different periods as the material for extraction and comparison, and based on the extraction and comparison of the contours, can effectively classify badges of different forms, thereby achieving efficient and concise classification work.

[0056] Since the electronic device provided by the present invention and the badge recognition and classification method described above belong to the same inventive concept, the electronic device provided by the present invention has all the advantages of the badge recognition and classification method described above, and the beneficial effects of the electronic device provided by the present invention will not be described one by one here.

[0057] To achieve the above-mentioned purpose, the present invention provides a readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-mentioned badge recognition and classification methods. Since the readable storage medium is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the readable storage medium can use the image data of the target person at different periods as the material for extraction and comparison, and based on the extraction and comparison of the contours, can effectively classify badges of different forms, thereby achieving efficient and concise classification work.

[0058] Since the readable storage medium provided by the present invention and the badge recognition and classification method described above belong to the same inventive concept, the readable storage medium provided by the present invention has all the advantages of the badge recognition and classification method described above, and therefore the beneficial effects of the readable storage medium provided by the present invention will not be described one by one here.

[0059] The readable storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer hard disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this article, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a device or a device or used in combination with it.

[0060] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program codes. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0061] The present invention also provides a computer program product, which implements any of the above-mentioned badge recognition and classification methods when executed by a processor.

[0062] The present invention also provides a computer program product, which is used to execute any of the above-mentioned badge recognition and classification methods. Therefore, the computer program product can use the image data of the target person at different periods as the material for extraction and comparison, and can effectively classify badges of different forms based on the extraction and comparison of contours, thereby achieving efficient and concise classification work.

[0063] Since the computer program product provided by the present invention and the badge recognition and classification method described above belong to the same inventive concept, the computer program product provided by the present invention has all the advantages of the badge recognition and classification method described above, and the beneficial effects of the computer program product provided by the present invention will not be described one by one here.

[0064] It should be noted that the various embodiments in this specification are described in a progressive manner, and any embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0065] It should also be noted that, although the present invention has been disclosed as a preferred embodiment, the above embodiment is not intended to limit the present invention. For any technician familiar with the art, without departing from the scope of the technical solution of the present invention, the technical content disclosed above can be used to make many possible changes and modifications to the technical solution of the present invention, or modified into equivalent embodiments of equivalent changes. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of protection of the technical solution of the present invention.

[0066] It should also be understood that, unless otherwise specified or indicated, the terms "first", "second", "third", etc. in the specification are merely used to distinguish between the various components, elements, steps, etc. in the specification, and are not used to indicate the logical relationship or sequential relationship between the various components, elements, steps, etc.

[0067] It should also be recognized that the terms described herein are used only to describe specific embodiments and are not intended to limit the scope of the invention. It should be noted that the singular forms "a" and "an" used herein and in the appended claims include plural references unless the context clearly indicates otherwise. For example, a reference to "a step" or "a device" means a reference to one or more steps or devices, and may include secondary steps and secondary devices. All conjunctions used should be understood in the broadest sense. And, the word "or" should be understood to have the definition of a logical "or", rather than a logical "exclusive or", unless the context clearly indicates otherwise. In addition, the implementation of embodiments of the present invention may include performing selected tasks manually, automatically, or in combination.

Claims

1. A badge recognition and classification method, wherein the badge has an image pattern of a target person, characterized in that: The following steps are involved: According to the historical image data of the target person, a plurality of different body contour models of the target person are established, and according to the historical image data of the target person, a classification category is anchored corresponding to each body contour model; Acquire the image pattern of the badge, and acquire the pattern outer contour information corresponding to the badge according to the image pattern; The pattern outer contour information is matched with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge, and the classification category corresponding to the body outer contour model is used as the classification category of the badge.

2. The badge identification and classification method according to claim 1, characterized in that: The acquiring, according to the image pattern, pattern outer contour information corresponding to the badge specifically includes: According to the image pattern, obtaining a first Fourier descriptor corresponding to the pattern outer contour information of the badge; The matching of the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge specifically includes: According to the body contour model of the target person, obtaining a second Fourier descriptor corresponding to the body contour model; The body contour model having the highest matching degree with the badge is obtained according to the first Fourier descriptor and the second Fourier descriptor.

3. The badge identification and classification method according to claim 1, characterized in that: The acquiring, according to the image pattern, pattern outer contour information corresponding to the badge specifically includes: Calling a hollowing-out internal point algorithm to obtain a first pattern outer contour image corresponding to the badge; The matching of the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge specifically includes: Calling a hollowing-out internal point algorithm to obtain a second outer contour image of the body outer contour model; The body contour model having the highest matching degree with the badge is acquired according to the first contour image and the second contour image.

4. The badge identification and classification method according to claim 1, characterized in that: The step of establishing a plurality of different body contour models of the target person based on the historical image data of the target person specifically includes: In the historical image data of the target person, reconstructed material images of the target task from at least two perspectives are obtained; The body contour model is reconstructed according to the reconstructed material image.

5. The badge identification and classification method according to claim 4, characterized in that: The step of reconstructing the body contour model according to the reconstructed material image specifically includes: Establishing a standard scale anchoring model according to the actual body size data of the target person; According to the standard scale anchor model, scaling the plurality of reconstructed material images so that the image features of the target task in the reconstructed material model are adapted to the standard scale model; The body contour model is reconstructed according to the scaled reconstructed material image.

6. The badge identification and classification method according to claim 1, characterized in that: There is a correspondence between the classification category and the historical image data, and the correspondence is saved. After confirming the classification category corresponding to the badge, each time the pattern of the badge is captured, the historical image data corresponding to the classification category of the badge is retrieved and displayed.

7. A recognition and classification system, characterized in that: include: A first execution module is used to establish a plurality of different body contour models of the target person according to the historical image data of the target person, and anchor a classification category corresponding to each body contour model according to the historical image data of the target person; A second execution module is used to obtain the image pattern of the badge, and obtain the pattern outer contour information corresponding to the badge according to the image pattern; The third execution module is used to match the pattern outer contour information with each of the body outer contour models to obtain the body outer contour model with the highest matching degree with the badge, and use the classification category corresponding to the body outer contour model as the classification category of the badge.

8. An electronic device, characterized in that: The electronic device comprises: a memory storing a computer program; a processor, communicatively connected to the memory, and configured to execute the badge recognition and classification method according to any one of claims 1 to 6 when calling the computer program; A display is communicatively connected to the processor and the memory, and is used to display a GUI interaction interface related to the badge identification and classification method.

9. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the badge recognition and classification method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that When the computer program product is executed by a processor, the badge recognition and classification method according to any one of claims 1 to 6 is implemented.

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