Bird tracking and identification method, device, bird tracking device and readable medium

Abstract

The embodiments of the present disclosure disclose a bird tracking and identification method, apparatus, bird tracking device, and readable medium. A specific implementation of the method includes: collecting ambient light brightness in a circumferential direction; adjusting the direction of video acquisition according to ambient light brightness information; collecting real-time monitoring video along the adjusted video acquisition direction; identifying birds according to the real-time monitoring video to generate bird information; determining the tracking mode type according to the bird position information in response to the bird position information characterizing that the bird deviates from the center of the video; adjusting the direction of the adjusted video acquisition direction according to the bird position information and the tracking mode type to obtain a second adjusted video acquisition direction. This implementation achieves video acquisition under optimal lighting conditions, improves video quality, and thus improves the accuracy of bird tracking and identification.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a bird tracking and identification method, apparatus, bird tracking equipment, and readable media. Background Art

[0002] In the process of bird tracking and identification, in order to ensure the quality of the video collected, especially for video collection under different ambient light conditions, the existing method is usually to identify the ambient light conditions through a single sensor and fill in the light through fill lights. However, the above method can only adapt to limited lighting conditions, which will lead to poor quality of the collected video, thus affecting the accuracy of bird tracking and identification.

[0003] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0004] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0005] Some embodiments of the present disclosure propose bird tracking and identification methods, apparatuses, bird tracking devices, and readable media to solve one or more of the technical problems mentioned in the above background technology section.

[0006] In a first aspect, some embodiments of the present disclosure provide a bird tracking and identification method, the method comprising: circumferentially collecting ambient light brightness to obtain ambient light brightness information; in response to the ambient light brightness information indicating that the ambient light brightness in the video collection direction is greater than a preset brightness threshold, adjusting the video collection direction according to the ambient light brightness information to obtain an adjusted video collection direction; collecting real-time monitoring video along the adjusted video collection direction; identifying birds according to the real-time monitoring video to generate bird information, wherein the bird information comprises: bird position information; in response to the bird position information indicating that the bird deviates from the video center, determining a tracking mode type according to the bird position information, wherein the tracking mode indicates a tracking and identification mode for the bird; adjusting the adjusted video collection direction according to the bird position information and the tracking mode type to obtain a secondary adjusted video collection direction, wherein the bird corresponding to the bird information is located at the video center of the monitoring video collected along the secondary adjusted video collection direction.

[0007] In a second aspect, some embodiments of the present disclosure provide a bird tracking and identification device, the device comprising: a circumferential collection unit, configured to collect ambient light brightness in a circumferential direction to obtain ambient light brightness information; a direction adjustment unit, configured to adjust the video collection direction in response to the ambient light brightness information indicating that the ambient light brightness in the video collection direction is greater than a preset brightness threshold, according to the ambient light brightness information, to obtain an adjusted video collection direction; a video collection unit, configured to collect real-time monitoring video along the adjusted video collection direction; a bird identification unit, configured to identify birds according to the real-time monitoring video to generate bird information, wherein the bird information comprises: bird position information; a determination unit, configured to determine a tracking mode type according to the bird position information in response to the bird position information indicating that the bird deviates from the video center, wherein the tracking mode indicates a tracking and identification mode for the bird; a secondary direction adjustment unit, configured to adjust the adjusted video collection direction in response to the bird position information and the tracking mode type, to obtain a secondary adjusted video collection direction, wherein the bird corresponding to the bird information is located at the video center of the monitoring video collected along the secondary adjusted video collection direction.

[0008] In a third aspect, some embodiments of the present disclosure provide a bird tracking device, which is applied to a bird feeder, comprising: a light intensity detection device, wherein the light intensity detection device comprises a plurality of photosensors arranged in a ring, and the light intensity detection device is configured to collect ambient light brightness in a ring direction; a camera, wherein the camera is configured to collect real-time monitoring video along the adjusted video collection direction; a direction adjustment device, wherein the direction adjustment device is configured to adjust the video collection direction in response to the ambient light brightness information indicating that the ambient light brightness in the video collection direction is greater than a preset brightness threshold, according to the ambient light brightness information, and adjust the adjusted video collection direction according to the bird position information and the tracking mode type; a power supply device and one or more processors; a storage device, on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation of the first aspect.

[0009] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

[0010] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the bird tracking and identification method of some embodiments of the present disclosure, video acquisition under optimal lighting conditions is realized, the video quality is improved, and thus the accuracy of bird tracking and identification is improved. Specifically, the reason for the poor accuracy of tracking and identification is that the existing means usually use a single sensor to identify the ambient light conditions, and use fill light, etc. to fill light. However, the above method can only adapt to limited lighting conditions. Based on this, the bird tracking and identification method of some embodiments of the present disclosure, first, collects the ambient light brightness in a circumferential direction to obtain ambient light brightness information, so as to obtain the ambient light brightness of the surrounding environment. Compared with a single sensor, the collected ambient light brightness is more comprehensive and accurate. Secondly, in response to the ambient light brightness information representing that the ambient light brightness of the video acquisition direction is greater than the preset brightness threshold, the above video acquisition direction is adjusted according to the above ambient light brightness information to obtain the adjusted video acquisition direction. By controlling the adjustment of the video acquisition direction, the problem of overexposure of the video screen caused by strong light is avoided. Then, real-time monitoring video is collected along the above adjusted video acquisition direction. Further, bird identification is performed according to the above-mentioned real-time monitoring video to generate bird information, wherein the above-mentioned bird information includes: bird position information. In this way, real-time identification of birds is performed. In addition, in response to the above-mentioned bird position information representing that the bird deviates from the center of the video, the tracking mode type is determined according to the above-mentioned bird position information, wherein the above-mentioned tracking mode represents the tracking and identification mode for the bird. Considering that when the bird deviates from the center of the video, it may not be possible to observe the bird effectively and comprehensively. At the same time, considering that the movement of birds has different characteristics, such as rapid movement, etc. In order to ensure the accurate tracking of birds and subsequent accurate identification, it is necessary to determine the corresponding tracking mode. Finally, according to the above-mentioned bird position information and the above-mentioned tracking mode type, the direction of the adjusted video acquisition direction is adjusted to obtain the second adjusted video acquisition direction, wherein the bird corresponding to the above-mentioned bird information is located at the video center of the monitoring video collected along the above-mentioned second adjusted video acquisition direction, so as to ensure that the bird is moderately located in the center of the picture. In this way, video acquisition under optimal lighting conditions is achieved, the video quality is improved, and thus the accuracy of bird tracking and identification is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0012] Figure 1 is a flow chart of some embodiments of the bird tracking and identification method according to the present disclosure;

[0013] Figure 2 It is a schematic diagram of the positional relationship between the camera and the light sensor;

[0014] Figure 3 This is a comparison chart of the ambient light brightness values ​​corresponding to different photosensitive sensors;

[0015] Figure 4 It is a schematic diagram of the positions of birds at different positions within the video frame;

[0016] Figure 5 is a flow chart of other embodiments of the bird tracking and identification method according to the present disclosure;

[0017] Figure 6 It is a tree structure diagram of the decision tree model;

[0018] Figure 7 It is a schematic diagram of a video image feature sequence;

[0019] Figure 8 is a schematic diagram of the structure of some embodiments of the bird tracking and identification device according to the present disclosure;

[0020] Fig. 9 is a schematic diagram of the structure of a bird tracking device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0021] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0022] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0023] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0024] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0025] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0026] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0027] refer to Figure 1 , shows a process 100 of some embodiments of the bird tracking and identification method according to the present disclosure. The bird tracking and identification method comprises the following steps:

[0028] Step 101, collect ambient light brightness in a circumferential direction to obtain ambient light brightness information.

[0029] In some embodiments, the execution subject (e.g., a computing device) of the bird tracking and identification method can collect ambient light brightness in a circular direction to obtain ambient light brightness information. The ambient light brightness information represents the ambient light brightness around the camera. In practice, the above-mentioned execution subject can collect ambient light brightness through a light intensity detection device arranged around the camera. Specifically, the light intensity detection device includes a plurality of photosensitive sensors arranged in a circular shape. The plurality of photosensitive sensors are located on the same horizontal collection plane. In practice, the ambient light brightness information may include a plurality of ambient light brightness values ​​collected by a plurality of photosensitive sensors.

[0030] As an example, see Figure 2 The schematic diagram of the positional relationship between the camera and the photosensitive sensor shown in the figure, wherein the light intensity detection device may include: 8 photosensitive sensors 2, which are arranged in a ring around the camera 1 to collect the ambient light brightness around the camera. For example, the ambient light brightness information may be [L1, L2, L3, L4, L5, L6, L7, L8]. Specifically, since the positions of the photosensitive sensors are fixed, the ambient light brightness values ​​collected by different photosensitive sensors in a clockwise direction may be recorded in the ambient light brightness information. In addition, a higher density of photosensitive sensors may also be arranged, for example, 10 photosensitive sensors are arranged in a ring around the camera 1. The specific number of photosensitive sensors is set according to actual needs and is not limited here.

[0031] It should be noted that the above-mentioned computing device can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the computing device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0032] Step 102 , in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, the video acquisition direction is adjusted according to the ambient light brightness information to obtain an adjusted video acquisition direction.

[0033] In some embodiments, the execution subject adjusts the video acquisition direction in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, and obtains the adjusted video acquisition direction according to the ambient light brightness information. In practice, when the ambient light brightness information indicates that the ambient light brightness in the video acquisition direction is greater than the preset brightness threshold, it indicates that there is a risk of overexposure in the video acquisition direction, and therefore, the video acquisition direction needs to be adjusted. For example, the preset brightness threshold may be 800 Lux.

[0034] As an example, see Figure 3 The comparison chart of the ambient light brightness values ​​corresponding to different light sensors is shown, and further see Figure 2 , where the ambient light brightness value "L1" corresponding to the video acquisition direction is greater than the preset brightness threshold, so it is necessary to adjust the video acquisition direction in combination with the ambient light brightness information to obtain the adjusted video acquisition direction. In practice, the direction adjustment must not only ensure that there is no risk of overexposure in the adjusted direction, but also ensure that the camera rotation angle is as small as possible to avoid power consumption. Therefore, the direction corresponding to the ambient brightness value "L3" can be used as the adjusted video acquisition direction.

[0035] Optionally, after collecting the ambient light brightness in the circumferential direction to obtain the ambient light brightness information, the method further includes:

[0036] In response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is less than or equal to a preset dark light brightness threshold, the video acquisition direction is adjusted according to the ambient light brightness information to obtain an adjusted video acquisition direction.

[0037] In practice, when the environment is too dark, the video quality of the real-time monitoring video collected will be poor. Therefore, at this time, it can also be triggered to adjust the direction of the video collection according to the above-mentioned ambient light brightness information to obtain the adjusted video collection direction.

[0038] Step 103: collect real-time monitoring video along the adjusted video collection direction.

[0039] In some embodiments, the above-mentioned execution subject can control the camera to collect real-time monitoring video along the adjusted video collection direction. In practice, since the video collection direction and the adjusted video collection direction are known, the angle change amount for the direction adjustment device can be generated according to the angle difference between the video collection direction and the adjusted video collection direction. Specifically, the direction adjustment device may include a stepper motor and a servo motor. Among them, the stepper motor is used to drive the overall direction of the bird feeder to rotate. The bird feeder may include: a feeding area. The camera faces the feeding area. Therefore, the stepper motor can drive the change in the direction of the bird feeder and the change in the overall direction of the camera at the same time, for example, from the video collection direction to the adjusted video collection direction. The servo motor can drive the fine adjustment of the pitch and left and right angles of the camera.

[0040] Optionally, the real-time monitoring video can be stored in a local storage device. For example, the local storage device can be an SD (Secure Digital Memory Card) card. The real-time monitoring video can also be stored in a cloud server through a wireless module by wireless transmission, so that the user can remotely view the bird's visit record.

[0041] Step 104: Perform bird identification based on the real-time monitoring video to generate bird information.

[0042] In some embodiments, the above-mentioned execution subject can perform bird identification based on the real-time monitoring video to generate bird information. The bird information may include bird location information. The bird location information may characterize the location of the bird within the video screen of the real-time monitoring video. Optionally, the bird information may also include but is not limited to at least one of the following: bird species, bird color, bird body shape, and bird residence time. In practice, the YOLO (You Only Look Once) model can be used to perform bird identification on the real-time monitoring video to generate bird information.

[0043] Step 105 , in response to the bird position information indicating that the bird deviates from the center of the video, determining the type of tracking mode according to the bird position information.

[0044] In some embodiments, the above-mentioned execution subject can respond to the bird position information characterizing the bird's deviation from the center of the video, and determine the tracking mode type according to the bird position information. The above-mentioned tracking mode characterizes the tracking and identification mode for birds. In practice, different types of birds have different movement characteristics and body characteristics. For example, sparrows have a smaller body size and flexible and dynamic movement characteristics. The fixed camera video acquisition method is difficult to guarantee the video quality of the real-time monitoring video collected (the whole picture of the bird can be fully captured). Therefore, in order to ensure the video quality of the real-time monitoring video, it is necessary to determine the corresponding tracking mode type in combination with the bird position information when the bird position information characterizes that the bird deviates from the center of the video.

[0045] As an example, see Figure 4 The schematic diagram of the positions of birds at different positions in the video frame is shown, wherein: Figure 4 -The bird in A is on the left side of the video screen. Figure 4 - The bird in B is on the right side of the video screen. Figure 4 -The bird in C is closer to the top of the video frame. Figure 4 -The birds in D are lower in the video screen. Specifically, since the birds are not stationary, the movement pattern of the birds can be determined by combining the bird position information corresponding to the birds at different times. For example, it is similar to a static type, a relatively active type, etc., and the corresponding tracking and identification mode is obtained by mapping. For example, when the bird is similar to a static type, it indicates that the bird will not have a large position change within a certain period of time. Therefore, the corresponding tracking mode type can be a static tracking mode, that is, increasing the trigger threshold of the direction adjustment device. For another example, when the bird is a relatively active type, it indicates that the bird has a large position change within a certain period of time. Therefore, the corresponding tracking mode type can be a dynamic tracking mode, that is, lowering the trigger threshold of the direction adjustment device.

[0046] Step 106 , adjusting the adjusted video acquisition direction according to the bird position information and the tracking mode type to obtain a second adjusted video acquisition direction.

[0047] In some embodiments, the execution subject may adjust the adjusted video acquisition direction according to the bird position information and the tracking mode type to obtain the second adjusted video acquisition direction. The bird corresponding to the bird information is located at the video center of the surveillance video collected along the second adjusted video acquisition direction. In practice, birds are not completely still, so it is necessary to adjust the video acquisition direction in real time according to the change of the bird's position. For example, when the tracking mode type represents a static tracking mode, since the bird has not undergone a large position change, the servo motor can be controlled to drive the camera to make a small-angle, low-frequency direction adjustment, and the rotation angle can be superimposed as a direction increment to the adjusted video acquisition direction to obtain the second adjusted video acquisition direction. For another example, when the tracking mode type represents a static tracking mode, since the bird has undergone a large position change, the servo motor can be controlled to make a large-angle, high-frequency direction adjustment, and the rotation angle can be superimposed as a direction increment to the adjusted video acquisition direction to obtain the second adjusted video acquisition direction.

[0048] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the bird tracking and identification method of some embodiments of the present disclosure, video acquisition under optimal lighting conditions is realized, the video quality is improved, and thus the accuracy of bird tracking and identification is improved. Specifically, the reason for the poor accuracy of tracking and identification is that the existing means usually use a single sensor to identify the ambient light conditions, and use fill light, etc. to fill light. However, the above method can only adapt to limited lighting conditions. Based on this, the bird tracking and identification method of some embodiments of the present disclosure, first, collects the ambient light brightness in a circumferential direction to obtain ambient light brightness information, so as to obtain the ambient light brightness of the surrounding environment. Compared with a single sensor, the collected ambient light brightness is more comprehensive and accurate. Secondly, in response to the ambient light brightness information representing that the ambient light brightness of the video acquisition direction is greater than the preset brightness threshold, the above video acquisition direction is adjusted according to the above ambient light brightness information to obtain the adjusted video acquisition direction. By controlling the adjustment of the video acquisition direction, the problem of overexposure of the video screen caused by strong light is avoided. Then, real-time monitoring video is collected along the above adjusted video acquisition direction. Further, bird identification is performed according to the above-mentioned real-time monitoring video to generate bird information, wherein the above-mentioned bird information includes: bird position information. In this way, real-time identification of birds is performed. In addition, in response to the above-mentioned bird position information representing that the bird deviates from the center of the video, the tracking mode type is determined according to the above-mentioned bird position information, wherein the above-mentioned tracking mode represents the tracking and identification mode for the bird. Considering that when the bird deviates from the center of the video, it may not be possible to observe the bird effectively and comprehensively. At the same time, considering that the movement of birds has different characteristics, such as rapid movement, etc. In order to ensure the accurate tracking of birds and subsequent accurate identification, it is necessary to determine the corresponding tracking mode. Finally, according to the above-mentioned bird position information and the above-mentioned tracking mode type, the direction of the adjusted video acquisition direction is adjusted to obtain the second adjusted video acquisition direction, wherein the bird corresponding to the above-mentioned bird information is located at the video center of the monitoring video collected along the above-mentioned second adjusted video acquisition direction, so as to ensure that the bird is moderately located in the center of the picture. In this way, video acquisition under optimal lighting conditions is achieved, the video quality is improved, and thus the accuracy of bird tracking and identification is improved.

[0049] Further references Figure 5 , which shows a process 500 of another embodiment of a bird tracking and identification method. The process 500 of the bird tracking and identification method includes the following steps:

[0050] Step 501: Periodically collect ambient light brightness in a circular direction according to a preset collection interval to obtain ambient light brightness information.

[0051] In some embodiments, the execution subject (e.g., computing device) of the bird tracking and identification method can periodically collect ambient light brightness in a circular direction according to a preset collection interval to obtain ambient light brightness information. In practice, the collection frequency can be reduced by setting a preset collection interval, thereby avoiding unnecessary power consumption. For example, the preset collection interval can be a fixed time interval, such as 0.5 hours. It can also be set by the user as needed. Such as 1 hour, 0.5 hours, 0.25 hours, etc.

[0052] As an example, when the light sensor collects ambient brightness, it can simulate a voltage value through a photoresistor, and convert the analog voltage value through an analog-to-digital converter (ADC) to obtain the ambient light brightness value as ambient light brightness information.

[0053] In some optional implementations of some embodiments, the execution subject collects ambient light brightness circumferentially to obtain ambient light brightness information, including:

[0054] The first step is to determine the current time.

[0055] In practice, to ensure the accuracy of the determined current time, the precise current time may be obtained through a wireless network or a wired network.

[0056] The second step is to obtain current weather information in response to the current time being in the first time period.

[0057] In practice, the first time period may be a time period before sunset. Specifically, the execution subject may obtain current weather information corresponding to the current location.

[0058] The third step is to determine the collection interval based on the above current weather information.

[0059] In practice, since the number of known common weather types is fixed and the light intensity of different weather is different, a decision tree model can be trained to determine the collection interval according to the current weather information. For example, when the light intensity corresponding to the current weather information is low, a low-frequency collection interval can be set. When the light intensity corresponding to the current weather information is high, a high-frequency collection interval can be set.

[0060] As an example, in sunny and cloudy weather, the light intensity may change greatly. For example, when the clouds block the light, the light intensity is low, and when the clouds are not blocking the light, the light intensity is high. At this time, a higher collection interval can be set. For another example, in sunny and cloudless weather, the light intensity is high, and a higher collection interval can be set. For another example, in cloudy weather, the light intensity is low, and a lower collection interval can be set.

[0061] As yet another example, see Figure 6 The tree structure diagram of the decision tree model shown, wherein, when the current weather information represents sunny and cloudy, the collection interval is collection interval T1. When the weather information represents sunny and rainy, the collection interval is collection interval T2. When the weather information represents sunny and snowy, the collection interval is collection interval T3. When the weather information represents sunny and foggy, the collection interval is collection interval T4. When the weather information represents sunny and dusty, the collection interval is collection interval T5. When the weather information represents sunny and sandy, the collection interval is collection interval T6. Specifically, according to more detailed weather divisions, a decision tree model with a more complex tree structure can be set to determine the collection interval according to the current weather information.

[0062] The fourth step is to periodically collect the ambient light brightness in a circular direction according to the above-mentioned collection interval to obtain the above-mentioned ambient light brightness information.

[0063] In practice, the execution subject may periodically and synchronously control the light intensity detection device to include a plurality of ring-shaped photosensitive sensors to collect ambient light brightness at a collection interval as the ambient light brightness information.

[0064] Step 502 , in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, the video acquisition direction is adjusted according to the ambient light brightness information to obtain an adjusted video acquisition direction.

[0065] In some embodiments, the execution subject adjusts the video acquisition direction according to the ambient light brightness information in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, and obtains the adjusted video acquisition direction, which may include the following steps:

[0066] The first step is to determine the ambient light brightness curve corresponding to the video acquisition range according to the above ambient light brightness information.

[0067] Among them, the above-mentioned video acquisition range represents the annular video acquisition area. Specifically, the video acquisition range represents the video acquisition range of the camera. For example, the video acquisition range can be 270°. It can also be 360°. In practice, since the light intensity detection device includes a plurality of discrete settings of photosensitive sensors arranged in an annular manner, the light intensity value collected is a discrete value. Therefore, a linear fitting method can be used to fit the ambient light brightness curve corresponding to the video acquisition range.

[0068] In the second step, for each candidate video acquisition direction in the candidate video acquisition direction set, the following first processing step is performed:

[0069] In a first sub-step, a first light intensity score and a second light intensity score corresponding to the candidate video acquisition direction are determined according to the ambient light brightness curve.

[0070] Among them, the candidate video acquisition direction set is at least one acquisition direction obtained by dividing the video acquisition range. The first light intensity score refers to the direct light intensity score of the video acquisition area corresponding to the candidate video acquisition direction. The second light intensity score refers to the oblique light intensity score of the video acquisition area corresponding to the candidate video acquisition direction. In practice, since the size of the photosensitive element (CMOS, Complementary Metal-Oxide-Semiconductor) of the camera is fixed, it can be understood that the camera faces any candidate video acquisition direction corresponding to a photosensitive area of ​​fixed size. In the image generation process, when the light intensity of oblique light and straight light is high, both may cause the problem of overexposure of the video screen. Since the candidate video acquisition direction is a local area within the video acquisition range, the local ambient light brightness curve for the candidate video acquisition direction can be obtained. Specifically, according to the light intensity value of the straight light, the corresponding first light intensity score is mapped. According to the light intensity value and the incident angle of the oblique light, the corresponding second light intensity score is mapped. For example, the light intensity value corresponding to the component vector of the oblique light in the vertical direction is mapped to obtain the corresponding second light intensity score.

[0071] The second sub-step is to obtain a regional light intensity score corresponding to the candidate video acquisition direction according to the first light intensity score and the second light intensity score.

[0072] In practice, the probability of overexposure of video images caused by direct light is higher, so a higher weight can be set. Although the probability of overexposure of video images caused by oblique light is lower than that of direct light, a smaller weight can be set. Therefore, the regional light intensity score = a1×first light intensity score+a2×second light intensity score, where a1+a2=1, a1>a2.

[0073] In the third step, according to the regional light intensity scores corresponding to the candidate video acquisition directions, the candidate video acquisition directions that meet the screening conditions are screened out from the above-mentioned candidate video acquisition direction set as the above-mentioned adjusted video acquisition directions.

[0074] The screening condition may be: the regional light intensity score corresponding to the candidate video acquisition direction is the minimum regional light intensity score.

[0075] Step 503: collect real-time monitoring video along the adjusted video collection direction.

[0076] In some embodiments, the specific implementation of step 503 and the technical effects thereof can be referred to in Figure 1The corresponding step 103 in the embodiment will not be described in detail here.

[0077] Step 504: perform bird identification based on the real-time monitoring video to generate bird information.

[0078] In some embodiments, the execution subject performs bird identification based on real-time surveillance video to generate bird information, which may include the following steps:

[0079] The first step is to extract video image features from the above real-time monitoring video to generate a video image feature sequence.

[0080] In practice, the above execution entity can extract video image features from real-time surveillance videos through a convolutional neural network consisting of five convolutional layers. The convolution kernel sizes of the five convolutional layers are: 1×1, 3×3, 5×5, 3×3, 1×1. Specifically, a shorter network layer can avoid the problem of feature forgetting. At the same time, since video image feature extraction is only used for subsequent video image feature grouping, too deep feature extraction will increase the number of feature processing.

[0081] In the second step, the video image features in the above video image feature sequence are grouped according to the inter-frame feature differences between the video image features to obtain a video image feature group sequence.

[0082] Among them, the inter-frame feature difference between any two video image features in the video image feature group is less than the preset difference value, and the average inter-frame feature difference between any two video image feature groups in the video image feature group sequence is greater than or equal to the above preset difference value.

[0083] As an example, see Figure 7 The schematic diagram of the video image feature sequence shown in FIG. 1 shows that the execution subject can characterize the feature difference between two frames of video image features by calculating the feature similarity between the features of two frames of video image features. When the feature difference between the frames is less than the preset difference value, the video image features are classified into a video image feature group. Figure 7 ,in, Figure 7It may include a video image feature group A and a video image feature group B. The video image feature group A includes: the first frame video image feature, the second frame video image feature, the third frame video image feature, the fourth frame video image feature, the fifth frame video image feature, and the sixth frame video image feature. Among the six video image features included in the video image feature group A, the inter-frame feature difference between any two video image features is less than a preset difference value. The video image feature group B includes: the seventh frame video image feature, the eighth frame video image feature, the ninth frame video image feature, and the tenth frame video image feature. Among the four video image features included in the video image feature group B, the inter-frame feature difference between any two video image features is less than a preset difference value. The average inter-frame feature difference between the video image feature group A and the video image feature group B is greater than or equal to the above-mentioned preset difference value. The average inter-frame feature is the average value of the video image features included in the video image feature group. The average inter-frame feature difference is the feature similarity between the average inter-frame feature corresponding to the video image feature group A and the average inter-frame feature corresponding to the video image feature group B.

[0084] In the third step, for each video image feature group in the above video image feature group sequence, the following second processing step is performed:

[0085] The first sub-step is to determine the downsampling ratio corresponding to the above-mentioned video image feature group.

[0086] In practice, the number interval into which the number of video image features included in the video image feature group falls can be used to map the corresponding downsampling ratio. For example, when the number of video image features included in the video image feature group is in the first number interval, the corresponding downsampling ratio may be R1. When the number of video image features included in the video image feature group is in the second number interval, the corresponding downsampling ratio may be R2. When the number of video image features included in the video image feature group is in the second number interval, the corresponding downsampling ratio may be R3. Among them, the higher the number of video image features included in the video image feature group, the higher the downsampling ratio. Among them, the downsampling ratio represents the proportion of downsampling. In addition, in order to avoid feature loss due to excessive downsampling, the downsampling ratio is set with maximum threshold and minimum threshold limits.

[0087] The second sub-step is to downsample the video image feature group according to the downsampling ratio to obtain a downsampled video image feature group.

[0088] In practice, the execution subject may perform average downsampling on the video image feature group according to the downsampling ratio to obtain a downsampled video image feature group.

[0089] The fourth step is to generate the above-mentioned bird information according to the obtained downsampled video image feature group sequence and the pre-built target bird recognition model.

[0090] In practice, the target bird recognition model may adopt a one-stage recognition model to achieve rapid target recognition. Specifically, the one-stage recognition model may be a YOLO v7 model.

[0091] Step 505 , in response to the bird position information indicating that the bird deviates from the center of the video, the tracking mode type is determined according to the bird position information.

[0092] In some embodiments, the execution subject determines the tracking mode type according to the bird position information in response to the bird position information indicating that the bird deviates from the center of the video, which may include:

[0093] The first step is to determine the bird's moving speed based on the above bird position coordinate sequence.

[0094] Among them, the bird position information includes: a bird position coordinate sequence. The above-mentioned bird position coordinate sequence represents the bird position in a continuous time period. Tracking mode types include: a static tracking mode type and a dynamic tracking mode type. In practice, when the bird is similar to a static type, it represents that the bird will not have a large position change in a certain period of time, so the corresponding tracking mode type may be a static tracking mode type. For example, when the bird is relatively active, it represents that the bird has a large position change in a certain period of time, so the corresponding tracking mode type may be a dynamic tracking mode type. Specifically, since the image acquisition frequency of the real-time monitoring video is known, the bird's movement speed can be determined based on the coordinate change of the bird's position coordinates and the image acquisition frequency.

[0095] In the second step, in response to the bird moving speed being less than or equal to a preset moving speed, the static tracking mode type is determined as the tracking mode type.

[0096] In a third step, in response to the bird's moving speed being greater than the preset moving speed, the dynamic tracking mode type is determined as the tracking mode type.

[0097] Step 506 , in response to the tracking mode type being a dynamic tracking mode type, extracting optical flow features from the bird position coordinate sequence to generate optical flow features.

[0098] In some embodiments, in response to the tracking mode type being a dynamic tracking mode type, the execution subject may extract optical flow features from the bird position coordinate sequence to generate optical flow features. In practice, optical flow features may be extracted from the bird position coordinate sequence using the Lucas-Kanade method to generate optical flow features.

[0099] Step 507: Determine the predicted position according to the optical flow features.

[0100] In some embodiments, the predicted position is determined according to the optical flow features by a position predictor, wherein the position predictor may adopt an RNN (Recurrent Neural Network) model.

[0101] Step 508: Taking the adjusted video acquisition direction as a reference direction, determine the direction offset according to the predicted position.

[0102] In some embodiments, the above-mentioned execution subject can use the adjusted video acquisition direction as the reference direction and determine the direction offset according to the predicted position. In practice, the rotation direction of the minimum angle can be used as the direction, the adjusted video acquisition direction can be used as the reference direction, and the direction offset can be determined according to the predicted position. Specifically, when the camera rotates clockwise, the corresponding direction offset increment is a positive number. When the camera rotates counterclockwise, the corresponding direction offset increment is a negative number, so that the direction of the direction adjustment can be determined according to the positive or negative direction offset.

[0103] Step 509: adjust the adjusted video acquisition direction by taking the direction offset as an increment to obtain a second adjusted video acquisition direction.

[0104] In some embodiments, the execution subject may adjust the direction of the adjusted video capture direction by taking the direction offset as an increment to obtain a second adjusted video capture direction.

[0105] from Figure 5 It can be seen that Figure 1 Compared with the description of some corresponding embodiments, the present disclosure further optimizes the processing flow of video image features, reduces the amount of data processing while maintaining recognition accuracy, and optimizes the tracking method to improve the success rate of bird tracking.

[0106] Further references Figure 8 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a bird tracking and identification device. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the bird tracking and identification device can be specifically applied to various bird tracking devices.

[0107] like Figure 8As shown, a bird tracking and identifying device 800 of some embodiments includes: a circumferential direction acquisition unit 801, a direction adjustment unit 802, a video acquisition unit 803, a bird identification unit 804, a determination unit 805 and a secondary direction adjustment unit 806. Among them, the circumferential collection unit 801 is configured to collect ambient light brightness in a circumferential direction to obtain ambient light brightness information; the direction adjustment unit 802 is configured to adjust the direction of the video collection direction according to the ambient light brightness information in response to the ambient light brightness information indicating that the ambient light brightness in the video collection direction is greater than a preset brightness threshold, and obtain an adjusted video collection direction; the video collection unit 803 is configured to collect real-time monitoring video along the adjusted video collection direction; the bird identification unit 804 is configured to identify birds according to the real-time monitoring video to generate bird information, wherein the bird information includes: bird position information; the determination unit 805 is configured to determine the tracking mode type according to the bird position information in response to the bird position information indicating that the bird deviates from the video center, wherein the tracking mode indicates a tracking and identification mode for the bird; the secondary direction adjustment unit 806 is configured to adjust the direction of the adjusted video collection direction according to the bird position information and the tracking mode type, and obtain a secondary adjusted video collection direction, wherein the bird corresponding to the bird information is located at the video center of the monitoring video collected along the secondary adjusted video collection direction.

[0108] It is understandable that the units described in the bird tracking and identification device 800 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the bird tracking and identification device 800 and the units included therein, and will not be described in detail here.

[0109] Reference below Fig. 9 , which shows a schematic structural diagram of a bird tracking device (eg, a computing device) 900 suitable for implementing some embodiments of the present disclosure. Fig. 9 The bird tracking device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure. The bird tracking device is applied to a bird feeder.

[0110] like Fig. 9As shown, the bird tracking device 900 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 901, which can perform various appropriate actions and processes according to the program stored in the read-only memory 902 or the program loaded from the storage device 908 to the random access memory 903. In the random access memory 903, various programs and data required for the operation of the bird tracking device 900 are also stored. The processing device 901, the read-only memory 902 and the random access memory 903 are connected to each other through the bus 904. The input / output interface 905 is also connected to the bus 904. In addition, the bird tracking device 900 may also include: a light intensity detection device, a camera and a direction adjustment device. Among them, the light intensity detection device, wherein the above-mentioned light intensity detection device includes a plurality of photosensitive sensors arranged in an annular manner, and the above-mentioned light intensity detection device is configured to collect the ambient light brightness in an annular direction. Camera, wherein the above-mentioned camera is configured to collect real-time monitoring video along the above-mentioned adjusted video collection direction. A direction adjustment device, wherein the direction adjustment device is configured to adjust the direction of the video acquisition direction according to the ambient light brightness information in response to the ambient light brightness information representing that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, and adjust the direction of the adjusted video acquisition direction according to the bird position information and the tracking mode type. In practice, the direction adjustment device can be composed of a stepper motor, a servo motor and a corresponding control circuit. The stepper motor is used to drive the overall direction of the bird feeder to rotate. The bird feeder may include: a feeding area. The camera is facing the feeding area. Therefore, the stepper motor can drive the change in the direction of the bird feeder and the change in the overall direction of the camera at the same time, for example, from the video acquisition direction to the adjusted video acquisition direction. The servo motor can drive the fine adjustment of the pitch and left and right angles of the camera. The power supply device can be powered by a lithium battery or a solar panel battery to provide all-weather stable power supply capability.

[0111] Typically, the following devices may be connected to the input / output interface 905: input devices 906 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 907 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 908 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 909. The communication device 909 may allow the bird tracking device 900 to communicate with other devices wirelessly or by wire to exchange data. Although Fig. 9 The bird tracking device 900 is shown with various devices, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead. Fig. 9 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0112] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 909, or installed from the storage device 908, or installed from the read-only memory 902. When the computer program is executed by the processing device 901, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0113] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer 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 some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. 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 computer readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0114] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0115] The computer-readable medium may be included in the bird tracking device; or it may exist independently without being assembled into the bird tracking device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the bird tracking device, the bird tracking device: collects ambient light brightness in a circumferential direction to obtain ambient light brightness information; in response to the ambient light brightness information indicating that the ambient light brightness in the video collection direction is greater than a preset brightness threshold, adjusts the video collection direction according to the ambient light brightness information to obtain an adjusted video collection direction; collects real-time monitoring video along the adjusted video collection direction; identifies birds according to the real-time monitoring video to generate bird information, wherein the bird information includes: bird position information; in response to the bird position information indicating that the bird deviates from the video center, determines the tracking mode type according to the bird position information, wherein the tracking mode indicates a tracking and identification mode for birds; adjusts the adjusted video collection direction according to the bird position information and the tracking mode type to obtain a secondary adjusted video collection direction, wherein the bird corresponding to the bird information is located at the video center of the monitoring video collected along the secondary adjusted video collection direction.

[0116] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0117] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0118] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including a circumferential acquisition unit, a direction adjustment unit, a video acquisition unit, a bird recognition unit, a determination unit, and a secondary direction adjustment unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the circumferential acquisition unit may also be described as a "unit for circumferentially acquiring ambient light brightness and obtaining ambient light brightness information".

[0119] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0120] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A bird tracking and identification method, comprising: According to the preset collection interval, the light intensity detection device arranged around the camera periodically collects the ambient light brightness in a circular direction to obtain the ambient light brightness information, and the light intensity detection device includes a plurality of photosensitive sensors arranged in a circular direction; In response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, the video acquisition direction is adjusted according to the ambient light brightness information to obtain an adjusted video acquisition direction; Collecting real-time monitoring video along the adjusted video collection direction; Perform bird identification according to the real-time monitoring video to generate bird information, wherein the bird information includes: bird location information; In response to the bird position information indicating that the bird deviates from the center of the video, determining a tracking mode type according to the bird position information, wherein the tracking mode indicates a tracking and identification mode for the bird; According to the bird position information and the tracking mode type, the adjusted video acquisition direction is adjusted to obtain a second adjusted video acquisition direction, wherein the bird corresponding to the bird information is located at the video center of the surveillance video acquired along the second adjusted video acquisition direction.

2. The method according to claim 1, wherein: The circumferentially collecting ambient light brightness to obtain ambient light brightness information includes: Determine the current time; In response to the current time being in the first time period, obtaining current weather information; Determine a collection interval according to the current weather information; According to the collection interval, periodically and circumferentially collect the ambient light brightness to obtain the ambient light brightness information; In response to the current time being within the second time period, the ambient light brightness is periodically collected in a circular direction according to a preset collection interval to obtain the ambient light brightness information.

3. The method according to claim 1, wherein: In response to the ambient light brightness information indicating that the ambient light brightness of the video acquisition direction is greater than a preset brightness threshold, adjusting the video acquisition direction according to the ambient light brightness information to obtain an adjusted video acquisition direction includes: Determine an ambient light brightness curve corresponding to a video acquisition range according to the ambient light brightness information, wherein the video acquisition range represents a circular video acquisition area; For each candidate video acquisition direction in the set of candidate video acquisition directions, the following first processing step is performed: Determine a first light intensity score and a second light intensity score corresponding to the candidate video acquisition direction according to the ambient light brightness curve, wherein the candidate video acquisition direction set is at least one acquisition direction obtained by averaging the video acquisition range, the first light intensity score refers to a direct light intensity score for the video acquisition area corresponding to the candidate video acquisition direction, and the second light intensity score refers to an oblique light intensity score for the video acquisition area corresponding to the candidate video acquisition direction; Obtaining a regional light intensity score corresponding to the candidate video acquisition direction according to the first light intensity score and the second light intensity score; According to the regional light intensity scores corresponding to the candidate video acquisition directions, the candidate video acquisition directions that meet the screening conditions are screened out from the candidate video acquisition direction set as the adjusted video acquisition directions.

4. The method according to claim 1, wherein: The step of identifying birds according to the real-time monitoring video to generate bird information includes: Extracting video image features from the real-time monitoring video to generate a video image feature sequence; According to the inter-frame feature differences between the video image features, the video image features in the video image feature sequence are grouped to obtain a video image feature group sequence, wherein the inter-frame feature difference between any two video image features in the video image feature group is less than a preset difference value, and the average inter-frame feature difference between any two video image feature groups in the video image feature group sequence is greater than or equal to the preset difference value; For each video image feature group in the video image feature group sequence, the following second processing step is performed: Determining a downsampling ratio corresponding to the video image feature group; Downsampling the video image feature group according to the downsampling ratio to obtain a downsampled video image feature group; The bird information is generated according to the obtained downsampled video image feature group sequence and a pre-built target bird recognition model.

5. The method according to claim 1, wherein: The bird position information includes: a bird position coordinate sequence, the bird position coordinate sequence represents the bird position in a continuous time period, and the tracking mode type includes: a static tracking mode type and a dynamic tracking mode type; and In response to the bird position information indicating that the bird deviates from the center of the video, determining the tracking mode type according to the bird position information includes: Determining the bird's moving speed according to the bird's position coordinate sequence; In response to the bird moving speed being less than or equal to a preset moving speed, determining a static tracking mode type as the tracking mode type; In response to the bird moving speed being greater than the preset moving speed, the dynamic tracking mode type is determined as the tracking mode type.

6. The method according to claim 5, wherein: The step of adjusting the adjusted video acquisition direction according to the bird position information and the tracking mode type to obtain a second adjusted video acquisition direction includes: In response to the tracking mode type being a dynamic tracking mode type, performing optical flow feature extraction on the bird position coordinate sequence to generate an optical flow feature; Determining a predicted position according to the optical flow feature; Taking the adjusted video acquisition direction as a reference direction, determining a direction offset according to the predicted position; The adjusted video acquisition direction is adjusted with the direction offset as an increment to obtain the second-adjusted video acquisition direction.

7. A bird tracking and identification device, comprising: The circumferential collection unit is configured to periodically collect ambient light brightness in a circular direction according to a preset collection interval, and obtain ambient light brightness information by using a light intensity detection device arranged around the camera, wherein the light intensity detection device includes a plurality of photosensitive sensors arranged in a circular direction; A direction adjustment unit is configured to adjust the video acquisition direction according to the ambient light brightness information in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, to obtain an adjusted video acquisition direction; A video acquisition unit configured to acquire real-time monitoring video along the adjusted video acquisition direction; A bird identification unit is configured to perform bird identification according to the real-time monitoring video to generate bird information, wherein the bird information includes: bird location information; a determination unit configured to determine a tracking mode type in response to the bird position information indicating that the bird deviates from the center of the video, according to the bird position information, wherein the tracking mode indicates a tracking and identification mode for the bird; The secondary direction adjustment unit is configured to adjust the adjusted video acquisition direction according to the bird position information and the tracking mode type to obtain a secondary adjusted video acquisition direction, wherein the bird corresponding to the bird information is located at the video center of the surveillance video collected along the secondary adjusted video acquisition direction.

8. A bird tracking device, applied to a bird feeder, comprising: A light intensity detection device, wherein the light intensity detection device comprises a plurality of photosensitive sensors arranged in a ring shape, and the light intensity detection device is configured to collect ambient light brightness in a ring direction; A camera, wherein the camera is configured to capture real-time monitoring video along the adjusted video capture direction; A direction adjustment device, wherein the direction adjustment device is configured to adjust the video acquisition direction according to the ambient light brightness information in response to the ambient light brightness information indicating that the ambient light brightness in the video acquisition direction is greater than a preset brightness threshold, and to adjust the direction of the adjusted video acquisition direction according to the bird position information and the tracking mode type; Power supply device; one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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