Animal behavior analysis method, device and equipment based on animal postures and medium

Abstract

The invention relates to the technical field of animal behavior analysis, and discloses an animal behavior analysis method and device based on animal postures, equipment and a medium, and the method comprises the steps: obtaining animal images under a plurality of visual angles; performing attitude analysis on each animal image to obtain an animal attitude feature image, and performing action recognition according to the animal attitude feature image to obtain an action type; performing normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain target position data; and analyzing according to the action type, the time information corresponding to each animal image and the target position data, and determining whether the behavior of the animal in the animal image is abnormal or not, so that accurate analysis can be performed through the extracted action type, time information and target position data of each animal posture feature image. Therefore, whether the behavior of the animal in the animal image is abnormal or not is judged, and the effect of analyzing the behavior of the animal is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of animal behavior analysis based on animal postures, and in particular to a method, device, equipment and medium for animal behavior analysis based on animal postures. Background Art

[0002] For a long time, the emotions and health status of experimental animals have usually been evaluated using low-dimensional physical parameters such as movement distance, residence time in the central area, and interaction distance in behavioral tests. However, it is not clear what postures animals maintain at different positions, what actions they perform, and what behaviors and emotional states they represent. For example, staying in place may be sleeping or grooming, so how to more accurately analyze animal behavior has become an urgent problem to be solved. Summary of the Invention

[0003] Based on this, in view of the technical problem of poor animal behavior analysis effect in the prior art, a method, device, equipment and medium for animal behavior analysis based on animal postures are proposed.

[0004] In a first aspect, a method for animal behavior analysis based on animal postures is provided. The method includes:

[0005] Obtaining each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment;

[0006] Performing posture analysis on each of the animal images to obtain each animal posture feature image, and performing action recognition according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images;

[0007] Performing normalization coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system;

[0008] Analyzing according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0009] In a second aspect, a device for animal behavior analysis based on animal postures is provided. The device includes:

[0010] An obtaining module, configured to obtain each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment;

[0011] A posture analysis module, configured to perform posture analysis on each of the animal images to obtain respective animal posture feature images, and perform action recognition based on the animal posture feature images and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images;

[0012] A coordinate conversion module, configured to perform normalized coordinate system conversion based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each of the animal posture feature images on the target coordinate system;

[0013] An anomaly module, configured to analyze based on the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal posture feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0014] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where when the processor executes the computer program, the steps of the above-mentioned animal behavior analysis method based on animal postures are implemented.

[0015] In a fourth aspect, a computer-readable storage medium is provided, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned animal behavior analysis method based on animal postures are implemented.

[0016] The animal behavior analysis method based on animal postures proposed by the present invention obtains each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment, then performs posture analysis on each of the animal images to obtain respective animal posture feature images, and performs action recognition based on the animal posture feature images and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images, then performs normalized coordinate system conversion based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each of the animal posture feature images on the target coordinate system, and finally analyzes based on the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal posture feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal. It can obtain the action type, time information, and target position data corresponding to the animal posture feature image through the extracted animal posture feature images, and accurately analyze the action type, time information, and target position data, so as to judge whether the behavior of the animal in the animal image is abnormal, and improve the effect of analyzing the behavior of animals. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Among them:

[0019] Figure 1 It is an application environment diagram of an animal behavior analysis method based on animal postures in an embodiment;

[0020] Figure 2 It is a flowchart of an animal behavior analysis method based on animal postures in an embodiment;

[0021] Figure 3 It is a white rat skeleton image of an animal state analysis method in an embodiment;

[0022] Figure 4 It is a structural block diagram of an animal behavior analysis device based on animal postures in an embodiment;

[0023] Figure 5 It is a structural block diagram of a computer device in an embodiment;

[0024] Figure 6 It is a structural block diagram of a computer device in another embodiment;

[0025] Figure 7 It is a schematic diagram of a target heat map of an animal behavior analysis method based on animal postures in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0027] The animal behavior analysis method based on animal postures provided by the embodiments of the present invention can be applied, for example, in Figure 1In the application environment, the client 110 communicates with the server 120 via a network. The server 120 can receive various animal images from multiple perspectives through the client 110. The animal images are captured by a target imaging device for a target animal in a target environment. Then, the server 120 performs pose analysis on each of the animal images to obtain respective animal pose feature images, and performs action recognition based on the animal pose feature images and a trained action behavior recognition model to obtain the action types corresponding to each of the animal images. Then, the server 120 performs normalized coordinate system conversion based on the three-dimensional coordinates of the animal pose feature images to obtain the target position data of each of the animal pose feature images on the target coordinate system. Finally, the server 120 analyzes based on the action types corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal. It is possible to obtain the action type, time information, and target position data corresponding to the animal pose feature image through each extracted animal pose feature image, and accurately analyze the action type, time information, and target position data, thereby determining whether the behavior of the animal in the animal image is abnormal, improving the effect of analyzing the behavior of animals. Among them, the client 110 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, and portable wearable devices. The server 120 can be implemented by an independent server or a server cluster composed of multiple servers. The present invention will be described in detail below through specific embodiments.

[0028] Please refer to Figure 2 as shown in Figure 2 A flowchart of a method for analyzing animal behavior based on animal poses provided by an embodiment of the present invention includes the following steps:

[0029] Step S101: Obtain various animal images from multiple perspectives, where the animal images are captured by a target imaging device for a target animal in a target environment;

[0030] In a preferred embodiment, the step of obtaining various animal images from multiple perspectives includes: obtaining each captured image, where the captured images are captured by different target imaging devices in a target environment; among each of the captured images, selecting the captured image whose target object in the captured image matches the target animal as the animal image.

[0031] In a preferred embodiment, multiple cameras are used to photograph an animal from multiple angles in a target environment. For a specific animal posture, the matching captured images are screened out as animal images, so as to quickly locate the time and position when the animal exhibits this action.

[0032] Among them, the target animal can be an animal such as a mouse, a cat, a dog, etc., and the target environment can be an open field, a pet hospital, a home environment, etc.

[0033] Step S102: Perform posture analysis on each of the animal images to obtain respective animal posture feature images, and perform action recognition according to the animal posture feature images and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images;

[0034] For example, for each animal image in the animal image set, an animal posture feature image is generated, and each of the animal posture feature images is used as an animal posture feature image set. As Figure 3 shown, it is the white rat skeleton image when the animal in the animal posture feature image is a white rat.

[0035] As an example, for each animal image, the two-dimensional spatial coordinates of 16 body key points of each frame of the animal image are extracted. According to the camera calibration file and the above two-dimensional spatial coordinates, an animal three-dimensional skeleton is constructed to obtain an animal posture feature image, where the body key points at least include the four paws of the animal in the animal image; then, the animal posture feature images corresponding to each animal image are aligned and the body orientations are unified; the animal skeleton in the animal posture feature image is scaled to the same scale size; the activity horizontal plane of the animal skeleton in the animal posture feature image is corrected so that the animal skeleton in the proposed animal posture feature image moves on the same horizontal base plane, and each corrected animal posture feature image is used as an animal posture feature image set.

[0036] For example, the action behavior recognition model can be a classification model trained based on a convolutional neural network, and this classification model can adopt an unsupervised algorithm. By inputting the animal posture feature image into the trained action behavior recognition model for action recognition, the action behavior recognition model outputs the action type corresponding to each of the animal images, where the action type can include sniffing, grooming, eating, and nesting.

[0037] Step S103: Perform normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system;

[0038] In this embodiment, since the animal posture feature images can be captured by different target imaging devices, the camera coordinate systems of each target imaging device are different due to different angles or positions, so the animal posture feature images are subjected to a normalized coordinate system conversion to obtain the target position data of each of the animal posture feature images on the normalized coordinate system. The normalized coordinate system can be preset artificially. In one implementation, the camera coordinate system when a target imaging device captures an image is used as the normalized coordinate system, that is, the optical center of the camera when capturing an image is used as the origin, the X-axis is the horizontal direction, the Y-axis is the vertical direction, and the Z-axis points to the direction observed by the camera when capturing an image. After selection, the target coordinate system will no longer change, that is, it is invariant and unique.

[0039] Further, in a preferred embodiment, the step of performing a normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each of the animal posture feature images on the target coordinate system includes:

[0040] Step S201: For each of the animal posture feature images, convert the three-dimensional coordinates of the animal posture feature image into the normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system.

[0041] For example, convert the three-dimensional coordinates of the animal posture feature image into the normalized coordinate system to obtain the position data of the animal posture feature image on the normalized coordinate system, and use this position data as the target position data.

[0042] Further, in a preferred embodiment, the step of, for each of the animal posture feature images, converting the three-dimensional coordinates of the animal posture feature image into the normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system includes:

[0043] Step S301: In the three-dimensional coordinates of each of the animal posture feature images, extract the three-dimensional coordinates of the key points corresponding to the back of the animal in the animal posture feature image as the target posture position data;

[0044] Step S302: Convert the target posture position data into the normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system.

[0045] In this embodiment, in order to improve the accuracy of the target position data of the animal pose feature image on the normalized coordinate system, each key point on the animal pose feature image corresponds to a bone position data, which is a three-dimensional coordinate; the bone position data where the key points corresponding to the back of the animal in the animal pose feature image are located is used as the target pose position data.

[0046] Step S104: Analyze according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0047] Among them, the time information refers to the time when the animal image is taken, and this time can adopt a time stamp.

[0048] For example, in an open field environment, the mice in the open field have some specific habits, such as foraging at a fixed time and place. The experimental personnel collect data on the daily behavior habits of the mice in the open field; when the animal in the animal image is a mouse in the open field, it can be determined whether the behavior of the animal in the animal image is abnormal by comparing the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system with the daily behavior habits of the mice in the open field.

[0049] As an example, when the behavior of the animal in the animal image is abnormal, an alarm signal is generated and sent to the user terminal to alert the user and prompt corresponding measures to be taken in a timely manner.

[0050] Further, in a preferred embodiment, the step of analyzing according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal includes:

[0051] Step S401: Generate a target heat map according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system;

[0052] Step S402: Based on the normalized historical heat map and the target heat map, perform a comparative analysis to determine whether the behavior of the animal in the animal image is abnormal.

[0053] Among them, the target heat map is as Figure 7 shown.

[0054] The animal behavior analysis method based on animal postures proposed in this embodiment obtains each animal image from multiple perspectives. Among them, the animal image is obtained by a target imaging device photographing a target animal in a target environment. Then, posture analysis is performed on each of the animal images to obtain each animal posture feature image, and action recognition is performed according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images. Then, normalization coordinate system conversion is performed according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system. Finally, analysis is performed according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal. It is possible to obtain the action type, time information, and target position data corresponding to the animal posture feature image through each extracted animal posture feature image, and accurately analyze the action type, time information, and target position data, thereby determining whether the behavior of the animal in the animal image is abnormal and improving the effect of analyzing the behavior of the animal.

[0055] Please refer to Figure 4 As shown, in one embodiment, an animal behavior analysis device based on animal postures is provided. The device includes: an acquisition module 10 for acquiring each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment;

[0056] A posture analysis module 20 for performing posture analysis on each of the animal images to obtain each animal posture feature image, and performing action recognition according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images.

[0057] A coordinate conversion module 30 for performing normalization coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system;

[0058] An abnormality module 40 for analyzing according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0059] Further, in one embodiment, the coordinate conversion module 30 is configured to: for each of the animal pose feature images, convert the three-dimensional coordinates of the animal pose feature image into a normalized coordinate system to obtain the target position data of the animal pose feature image on the normalized coordinate system.

[0060] Further, in one embodiment, the coordinate conversion module 30 is configured to: in the three-dimensional coordinates of each of the animal pose feature images, extract the three-dimensional coordinates of the key points corresponding to the back of the animal in the animal pose feature image as the target pose position data;

[0061] Convert the target pose position data into a normalized coordinate system to obtain the target position data of the animal pose feature image on the normalized coordinate system.

[0062] Further, in one embodiment, the anomaly module 40 is further configured to: generate a target heat map according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal pose feature images on the target coordinate system; perform comparative analysis based on the normalized historical heat map and the target heat map to determine whether the behavior of the animal in the animal image is abnormal.

[0063] Further, in one embodiment, the acquisition module 10 is further configured to: acquire each of the captured images, where the captured images are captured by different target imaging devices in a target environment;

[0064] In each of the captured images, select the captured image in which the target object in the captured image matches the target animal as the animal image.

[0065] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 5 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of the server side of an animal behavior analysis method based on animal poses.

[0066] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as shown in Figure 6 . The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the client side of an animal behavior analysis method based on animal postures.

[0067] In one embodiment, a computer device is proposed, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are realized:

[0068] Obtain each animal image from multiple perspectives, where the animal image is obtained by a target camera device taking pictures of a target animal in a target environment;

[0069] Perform posture analysis on each of the animal images to obtain each animal posture feature image, and perform action recognition based on the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images;

[0070] Perform normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system;

[0071] Analyze according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0072] The animal behavior analysis method based on animal postures proposed in this embodiment obtains each animal image from multiple perspectives. Among them, the animal image is obtained by a target imaging device photographing a target animal in a target environment. Then, posture analysis is performed on each of the animal images to obtain each animal posture feature image, and action recognition is performed according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images. Then, normalization coordinate system conversion is performed according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system. Finally, analysis is performed according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal. It can obtain the action type, time information, and target position data corresponding to the animal posture feature image through each extracted animal posture feature image, and accurately analyze the action type, time information, and target position data, so as to judge whether the behavior of the animal in the animal image is abnormal, improving the effect of analyzing the behavior of animals.

[0073] In one embodiment, a computer-readable storage medium is proposed. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0074] Obtain each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment;

[0075] Perform posture analysis on each of the animal images to obtain each animal posture feature image, and perform action recognition according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images;

[0076] Perform normalization coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system;

[0077] Perform analysis according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

[0078] The animal behavior analysis method based on animal postures proposed in this embodiment obtains various animal images from multiple perspectives. Among them, the animal images are obtained by a target imaging device photographing a target animal in a target environment. Then, posture analysis is performed on each of the animal images to obtain respective animal posture feature images, and action recognition is performed according to the animal posture feature images and a trained action behavior recognition model to obtain the action types corresponding to each of the animal images. Then, normalization coordinate system conversion is performed according to the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each of the animal posture feature images on the target coordinate system. Finally, analysis is performed according to the action types corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each of the animal posture feature images on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal. It is possible to obtain the action type, time information, and target position data corresponding to the animal posture feature image through the extracted animal posture feature images, and accurately analyze the action type, time information, and target position data, thereby determining whether the behavior of the animal in the animal image is abnormal, and improving the effect of analyzing the behavior of animals.

[0079] It should be noted that for the functions or steps that can be realized by the above computer-readable storage medium or computer device, reference can be made to the relevant descriptions on the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described in detail here.

[0080] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of 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 (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0081] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0082] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An animal behavior analysis method based on animal postures, characterized in that, the animal behavior analysis method based on animal postures includes: obtaining each animal image from multiple perspectives, where the animal image is obtained by a target imaging device photographing a target animal in a target environment; performing posture analysis on each of the animal images to obtain each animal posture feature image, and performing action recognition according to the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images; performing normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system; analyzing according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

2. The animal behavior analysis method based on animal postures according to claim 1, characterized in that, the step of performing normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system includes: for each animal posture feature image, converting the three-dimensional coordinates of the animal posture feature image into a normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system.

3. The animal behavior analysis method based on animal postures according to claim 2, characterized in that, the step of for each animal posture feature image, converting the three-dimensional coordinates of the animal posture feature image into a normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system includes: extracting the three-dimensional coordinates of the key points corresponding to the back of the animal in the animal posture feature image from the three-dimensional coordinates of each animal posture feature image as the target posture position data; converting the target posture position data into a normalized coordinate system to obtain the target position data of the animal posture feature image on the normalized coordinate system.

4. The animal behavior analysis method based on animal postures according to claim 1, characterized in that, the step of analyzing according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal includes: generating a target heat map according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system; performing comparative analysis based on the normalized historical heat map and the target heat map to determine whether the behavior of the animal in the animal image is abnormal.

5. The method for analyzing animal behavior based on animal posture according to claim 1, characterized in that, the step of obtaining each animal image from multiple perspectives includes: obtaining each captured image, wherein the captured image is captured by each different target imaging device in a target environment; in each of the captured images, selecting the captured image in which the target object in the captured image matches the target animal as the animal image.

6. An apparatus for analyzing animal behavior based on animal posture, characterized in that, the apparatus for analyzing animal behavior based on animal posture includes: an acquisition module, configured to obtain each animal image from multiple perspectives, wherein the animal image is captured by a target imaging device for a target animal in a target environment; a posture analysis module, configured to perform posture analysis on each of the animal images to obtain each animal posture feature image, and perform action recognition based on the animal posture feature image and a trained action behavior recognition model to obtain the action type corresponding to each of the animal images.

7. The apparatus for analyzing animal behavior based on animal posture according to claim 6, characterized in that, the apparatus for analyzing animal behavior based on animal posture includes: a coordinate conversion module, configured to perform normalized coordinate system conversion according to the three-dimensional coordinates of the animal posture feature image to obtain the target position data of each animal posture feature image on the target coordinate system; an abnormality module, configured to analyze according to the action type corresponding to each of the animal images, the time information corresponding to each of the animal images, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animal in the animal image is abnormal.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, the steps of the method for analyzing animal behavior based on animal posture according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method for analyzing animal behavior based on animal posture according to any one of claims 1 to 5 are implemented.

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