Animal behavior analysis method and device based on animal posture, equipment and medium
By acquiring animal images from multiple perspectives for posture analysis and motion recognition, and combining 3D coordinate system transformation and time information, the problem of inaccurate animal behavior analysis in existing technologies has been solved, enabling efficient judgment and abnormal alarm of animal behavior.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN UNIVERSITY OF ADVANCED TECHNOLOGY
- Filing Date
- 2023-11-24
- Publication Date
- 2026-05-15
AI Technical Summary
In existing technologies, animal behavior analysis cannot accurately determine the behavior and emotional state represented by the postures and movements maintained by animals in different positions, resulting in poor analysis results.
By acquiring animal images from multiple perspectives, we perform posture analysis, extract animal posture feature images, and use a trained action behavior recognition model to perform action recognition. We then combine 3D coordinate system transformation and time information for analysis to determine whether the animal behavior is abnormal.
It improves the accuracy of animal behavior analysis, enabling accurate judgment of whether animal behavior is abnormal, generating alarm signals and taking timely measures.
Smart Images
Figure CN120088840B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of animal behavior analysis technology based on animal posture, and more particularly to a method, apparatus, equipment and medium for animal behavior analysis based on animal posture. Background Technology
[0002] For a long time, the emotional and health status of laboratory animals has been assessed using low-dimensional physical parameters such as movement distance, time spent in the central region, and interaction distance in behavioral tests. However, it is unclear what postures the animals maintain in different positions, what actions they take, and what behavioral and emotional states they represent. For example, staying still could mean sleeping or grooming. Therefore, how to analyze animal behavior more accurately has become an urgent problem to be solved. Summary of the Invention
[0003] Therefore, it is necessary to address the problem that existing technologies for analyzing animal behavior in pairs are not very effective, and to propose a method, device, equipment, and medium for analyzing animal behavior based on animal posture.
[0004] Firstly, a method for analyzing animal behavior based on animal posture is provided, the method comprising:
[0005] Acquire images of various animals from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment;
[0006] Pose analysis is performed on each of the animal images to obtain animal pose feature images. Then, action recognition is performed based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
[0007] Based on the three-dimensional coordinates of the animal posture feature images, a normalized coordinate system transformation is performed to obtain the target position data of each animal posture feature image in the target coordinate system;
[0008] The analysis is performed based on the action type corresponding to each animal image, the time information corresponding to each animal image, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animals in the animal images is abnormal.
[0009] Secondly, an animal behavior analysis device based on animal posture is provided, the device comprising:
[0010] The acquisition module is used to acquire animal images from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment;
[0011] The pose analysis module is used to perform pose analysis on each of the animal images to obtain the pose feature images of each animal, and to perform action recognition based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
[0012] The coordinate transformation module is used to perform normalized coordinate system transformation based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each animal posture feature image in the target coordinate system.
[0013] The anomaly module is used to analyze 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 animals in the animal images is abnormal.
[0014] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described animal behavior analysis method based on animal posture.
[0015] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described animal behavior analysis method based on animal posture.
[0016] This invention proposes an animal behavior analysis method based on animal posture. It acquires animal images from multiple perspectives, where the images are captured by a target camera device in a target environment. Posture analysis is then performed on each animal image to obtain individual animal posture feature images. Action recognition is then performed based on these image images and a trained action behavior recognition model to determine the action type for each animal image. Next, a normalized coordinate system transformation is performed on the three-dimensional coordinates of the animal posture feature images to obtain target position data for each image in the target coordinate system. Finally, analysis is conducted based on the action type, time information, and target position data of each animal image in the target coordinate system to determine whether the animal behavior in the images is abnormal. This method improves the effectiveness of animal behavior analysis by extracting action type, time information, and target position data from each animal posture feature image and accurately analyzing these data. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] in:
[0019] Figure 1 This is a diagram illustrating the application environment of an animal behavior analysis method based on animal posture in one embodiment.
[0020] Figure 2 This is a flowchart of an animal behavior analysis method based on animal posture in one embodiment;
[0021] Figure 3 An image of a white mouse skeleton from an animal state analysis method in one embodiment;
[0022] Figure 4 This is a structural block diagram of an animal behavior analysis device based on animal posture in one embodiment;
[0023] Figure 5 This is a structural block diagram of a computer device in one embodiment;
[0024] Figure 6 This is a structural block diagram of a computer device in another embodiment;
[0025] Figure 7 This is a schematic diagram of a target heatmap for an animal behavior analysis method based on animal posture in one embodiment. Detailed Implementation
[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0027] The animal behavior analysis method based on animal posture provided in this invention can be applied to, for example... Figure 1In the application environment, client 110 communicates with server 120 via the network. The server 120 can receive animal images from multiple perspectives through the client 110. These animal images are captured by a target camera device in a target environment. The server 120 then performs posture analysis on each animal image to obtain individual animal posture feature images. Based on these animal posture feature images and a trained action recognition model, the server 120 performs action recognition to obtain the corresponding action type for each animal image. Next, the server 120 performs a normalized coordinate system transformation based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each animal posture feature image in the target coordinate system. Finally, the server 120 analyzes the corresponding action type, time information, and target position data of each animal image in the target coordinate system to determine whether the animal behavior in the images is abnormal. By extracting the animal posture feature images, the server 120 can obtain the corresponding action type, time information, and target position data, and accurately analyze these data to determine whether the animal behavior in the images is abnormal, thus improving the effectiveness of animal behavior analysis. The client 110 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server 120 can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will now be described in detail through specific embodiments.
[0028] Please see Figure 2 As shown, Figure 2 A flowchart illustrating an animal behavior analysis method based on animal posture according to an embodiment of the present invention includes the following steps:
[0029] Step S101: Acquire animal images from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment;
[0030] In a preferred embodiment, the step of acquiring animal images from multiple perspectives includes: acquiring various captured images, wherein the captured images are obtained by different target camera devices in a target environment; and selecting, from among the captured images, the captured images in which the target object matches the target animal as animal images.
[0031] In a preferred embodiment, multiple cameras are used to photograph the animal from multiple angles in the target environment. For a specific animal posture, the matching images are selected as animal images to quickly locate the time and location of the animal's action.
[0032] The target animals can be animals such as mice, cats, and dogs, and the target environment can be open fields, pet hospitals, or home environments.
[0033] Step S102: Perform pose analysis on each of the animal images to obtain animal pose feature images, and perform action recognition based on the animal pose feature images and the 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, generate an animal pose feature image, and use these animal pose feature images as a set of animal pose feature images. Figure 3 As shown, this is a skeleton image of a white mouse when the animal in the animal pose feature image is a white mouse.
[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. Based on the camera calibration file and the above two-dimensional spatial coordinates, a three-dimensional skeleton of the animal is constructed to obtain an animal posture feature image. The body key points include at least 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 orientation is unified. The animal skeleton in the animal posture feature image is scaled to the same scale. The 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. 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, which can employ an unsupervised algorithm. By inputting animal posture feature images into the trained action behavior recognition model for action recognition, the action behavior recognition model outputs the action type corresponding to each animal image. The action type can include sniffing, grooming, eating, and nest building.
[0037] Step S103: Perform a normalized coordinate system transformation based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each animal posture feature image in the target coordinate system;
[0038] In this embodiment, since animal posture feature images can be obtained by capturing images from different target camera devices, and the camera coordinate systems of each target camera device differ due to variations in angle or position, a normalized coordinate system transformation is performed on the animal posture feature images to obtain target position data for each animal posture feature image in the normalized coordinate system. The normalized coordinate system can be pre-set manually. In one implementation, the camera coordinate system of a target camera device capturing an image is used as the normalized coordinate system. Specifically, the optical center of the camera when capturing an image is taken is used as the origin, the X-axis is horizontal, the Y-axis is vertical, and the Z-axis points in the direction observed by the camera when capturing the image. Once selected, the target coordinate system remains unchanged and unique.
[0039] Further, in a preferred embodiment, the step of performing a normalized coordinate system transformation 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 in the target coordinate system includes:
[0040] Step S201: For each of the animal posture feature images, the three-dimensional coordinates of the animal posture feature image are transformed into a normalized coordinate system to obtain the target position data of the animal posture feature image in the normalized coordinate system.
[0041] For example, the three-dimensional coordinates of an animal posture feature image can be transformed into a normalized coordinate system to obtain the position data of the animal posture feature image in the normalized coordinate system, and this position data can be used as the target position data.
[0042] Further, in a preferred embodiment, the step of transforming the three-dimensional coordinates of each animal posture feature image to a normalized coordinate system to obtain the target position data of the animal posture feature image in 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 to a normalized coordinate system to obtain the target position data of the animal posture feature image in the normalized coordinate system.
[0045] In this embodiment, in order to improve the accuracy of the target position data of the animal posture feature image on the normalized coordinate system, each key point on the animal posture feature image corresponds to a bone position data, which is a three-dimensional coordinate; the bone position data of the key point on the back of the animal in the animal posture feature image is used as the target posture position data.
[0046] Step S104: Analyze 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 animals in the animal images is abnormal.
[0047] The time information refers to the time when the animal image was taken, which can be expressed as a timestamp.
[0048] For example, in an open field environment, rats in the open field have certain specific habits, such as foraging in a certain place at a fixed time. Researchers collect data on the daily behavioral habits of rats in the open field. When the animal in the animal image is a rat in the open field, the daily behavioral habits of rats in the open field can be compared with the daily behavioral habits of rats in the open field by comparing the action type, time information, and target position data of each animal posture feature image on the target coordinate system. This can help determine whether the behavior of the animal in the animal image is abnormal.
[0049] As an example, when an animal in an animal image exhibits abnormal behavior, an alarm signal is generated and sent to the user's terminal to alert the user and allow for timely corresponding measures.
[0050] Further, in a preferred embodiment, the step of analyzing 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:
[0051] Step S401: Generate a heatmap 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 animal posture feature image on the target coordinate system to obtain a target heatmap;
[0052] Step S402: Based on the normalized historical heatmap and the target heatmap, perform comparative analysis to determine whether the behavior of the animal in the animal image is abnormal.
[0053] The target heat map is as follows: Figure 7 As shown.
[0054] This embodiment proposes an animal behavior analysis method based on animal posture. It acquires animal images from multiple perspectives, where the images are captured by a target camera device in a target environment. Posture analysis is then performed on each animal image to obtain individual animal posture feature images. Action recognition is then performed based on these image images and a trained action behavior recognition model to determine the action type for each animal image. Next, a normalized coordinate system transformation is performed on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each image in the target coordinate system. Finally, analysis is conducted based on the action type, time information, and target position data of each animal image to determine whether the animal behavior in the images is abnormal. This method improves the effectiveness of animal behavior analysis by extracting action type, time information, and target position data from each animal posture feature image and accurately analyzing these data to determine whether the animal behavior in the images is abnormal.
[0055] Please see Figure 4 As shown, in one embodiment, an animal behavior analysis device based on animal posture is provided. The device includes: an acquisition module 10, used to acquire various animal images from multiple perspectives, wherein the animal images are obtained by a target camera device capturing images of a target animal in a target environment;
[0056] The posture analysis module 20 is used to perform posture analysis on each of the animal images to obtain each animal posture feature image, and to perform action recognition based on the animal posture feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
[0057] The coordinate transformation module 30 is used to perform normalized coordinate system transformation based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each animal posture feature image in the target coordinate system.
[0058] The anomaly module 40 is used to analyze 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] Furthermore, in one embodiment, the coordinate transformation module 30 is used to: for each of the animal posture feature images, transform the three-dimensional coordinates of the animal posture feature image to a normalized coordinate system to obtain the target position data of the animal posture feature image in the normalized coordinate system.
[0060] Furthermore, in one embodiment, the coordinate transformation module 30 is used to: extract 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 of the animal posture feature images, and use them as target posture position data.
[0061] The target posture position data is converted to a normalized coordinate system to obtain the target position data of the animal posture feature image in the normalized coordinate system.
[0062] Furthermore, in one embodiment, the anomaly module 40 is also used to: generate a heatmap 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 animal posture feature image on the target coordinate system, to obtain a target heatmap; and perform comparative analysis based on the normalized historical heatmap and the target heatmap to determine whether the behavior of the animal in the animal image is abnormal.
[0063] Furthermore, in one embodiment, the acquisition module 10 is also configured to: acquire various captured images, wherein the captured images are obtained by different target camera devices in a target environment;
[0064] Among the captured images, the images in which the target object matches the target animal are selected as animal images.
[0065] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When executed by the processor, the computer program implements the functions or steps of a server-side method for animal behavior analysis based on animal posture.
[0066] In one embodiment, a computer device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements client-side functions or steps of an animal behavior analysis method based on animal posture.
[0067] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps:
[0068] Acquire images of various animals from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment;
[0069] Pose analysis is performed on each of the animal images to obtain animal pose feature images. Then, action recognition is performed based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
[0070] Based on the three-dimensional coordinates of the animal posture feature images, a normalized coordinate system transformation is performed to obtain the target position data of each animal posture feature image in the target coordinate system;
[0071] The analysis is performed based on the action type corresponding to each animal image, the time information corresponding to each animal image, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animals in the animal images is abnormal.
[0072] This embodiment proposes an animal behavior analysis method based on animal posture. It acquires animal images from multiple perspectives, where the images are captured by a target camera device in a target environment. Posture analysis is then performed on each animal image to obtain individual animal posture feature images. Action recognition is then performed based on these image images and a trained action behavior recognition model to determine the action type for each animal image. Next, a normalized coordinate system transformation is performed on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each image in the target coordinate system. Finally, analysis is conducted based on the action type, time information, and target position data of each animal image to determine whether the animal behavior in the images is abnormal. This method improves the effectiveness of animal behavior analysis by extracting action type, time information, and target position data from each animal posture feature image and accurately analyzing these data to determine whether the animal behavior in the images is abnormal.
[0073] In one embodiment, a computer-readable storage medium is provided that stores a computer program, which, when executed by a processor, performs the following steps:
[0074] Acquire images of various animals from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment;
[0075] Pose analysis is performed on each of the animal images to obtain animal pose feature images. Then, action recognition is performed based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
[0076] Based on the three-dimensional coordinates of the animal posture feature images, a normalized coordinate system transformation is performed to obtain the target position data of each animal posture feature image in the target coordinate system;
[0077] The analysis is performed based on the action type corresponding to each animal image, the time information corresponding to each animal image, and the target position data of each animal posture feature image on the target coordinate system to determine whether the behavior of the animals in the animal images is abnormal.
[0078] This embodiment proposes an animal behavior analysis method based on animal posture. It acquires animal images from multiple perspectives, where the images are captured by a target camera device in a target environment. Posture analysis is then performed on each animal image to obtain individual animal posture feature images. Action recognition is then performed based on these image images and a trained action behavior recognition model to determine the action type for each animal image. Next, a normalized coordinate system transformation is performed on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each image in the target coordinate system. Finally, analysis is conducted based on the action type, time information, and target position data of each animal image to determine whether the animal behavior in the images is abnormal. This method improves the effectiveness of animal behavior analysis by extracting action type, time information, and target position data from each animal posture feature image and accurately analyzing these data to determine whether the animal behavior in the images is abnormal.
[0079] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.
[0080] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0081] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.
[0082] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A method for analyzing animal behavior based on animal posture, characterized in that, The animal behavior analysis method based on animal posture includes: Acquire images of various animals from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment; Pose analysis is performed on each of the animal images to obtain animal pose feature images. Then, action recognition is performed based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images. Based on the three-dimensional coordinates of the animal posture feature images, a normalized coordinate system transformation is performed to obtain the target position data of each animal posture feature image in the target coordinate system; Based on the analysis of the action type corresponding to each animal image, the time information corresponding to each animal image, and the target position data of each animal posture feature image on the target coordinate system, it is determined whether the behavior of the animal in the animal image is abnormal. In this context, each key point in the animal posture feature image corresponds to a bone position data; the bone position data of the key point on the back of the animal in the animal posture feature image is used as the target posture position data; the bone position data is in three-dimensional coordinates. The target posture position data is converted to a normalized coordinate system to obtain the target position data of the animal posture feature image in the normalized coordinate system.
2. The animal behavior analysis method based on animal posture according to claim 1, characterized in that, The step of performing a normalized coordinate system transformation based on the three-dimensional coordinates of the animal posture feature images to obtain the target position data of each animal posture feature image in the target coordinate system includes: For each of the animal posture feature images, the three-dimensional coordinates of the animal posture feature images are transformed into a normalized coordinate system to obtain the target position data of the animal posture feature images in the normalized coordinate system.
3. The animal behavior analysis method based on animal posture according to claim 1, characterized in that, The step of analyzing the animal images based on their respective action types, time information, and target position data in the target coordinate system to determine whether the animal behavior in the images is abnormal includes: A heatmap is generated based on the action type corresponding to each animal image, the time information corresponding to each animal image, and the target position data of each animal posture feature image on the target coordinate system to obtain a target heatmap. By comparing and analyzing the normalized historical heatmap with the target heatmap, it can be determined whether the behavior of the animal in the animal image is abnormal.
4. The animal behavior analysis method based on animal posture according to claim 1, characterized in that, The steps for acquiring animal images from multiple perspectives include: Acquire various captured images, wherein the captured images are obtained by different target camera devices in the target environment; Among the captured images, the images in which the target object matches the target animal are selected as animal images.
5. An animal behavior analysis device based on animal posture, characterized in that, Perform the animal behavior analysis method based on animal posture as described in any one of claims 1 to 4; the animal behavior analysis device based on animal posture includes: The acquisition module is used to acquire animal images from multiple perspectives, wherein the animal images are obtained by the target camera device capturing images of the target animal in the target environment; The pose analysis module is used to perform pose analysis on each of the animal images to obtain the pose feature images of each animal, and to perform action recognition based on the animal pose feature images and the trained action behavior recognition model to obtain the action type corresponding to each of the animal images.
6. The animal behavior analysis device based on animal posture according to claim 5, characterized in that, The animal behavior analysis device based on animal posture includes: a coordinate transformation module, used to perform normalized coordinate system transformation according to the three-dimensional coordinates of the animal posture feature image to obtain target position data of each animal posture feature image on the target coordinate system; The anomaly module is used to analyze 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 animals in the animal images is abnormal.
7. 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, it implements the steps of the animal behavior analysis method based on animal posture as described in any one of claims 1 to 4.
8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the animal behavior analysis method based on animal posture as described in any one of claims 1 to 4.