Method, device, electronic device and readable medium for adjusting surveillance video frame rate

Abstract

The embodiments of the present disclosure disclose a surveillance video frame rate adjustment method, device, electronic device and readable medium. A specific implementation of the method includes: segmenting the previous surveillance video frame and the current surveillance video frame to obtain a previous surveillance image block set and a current surveillance image block set; subtracting the current surveillance image block from the previous surveillance image block to obtain an image block difference; accumulating the image block differences to obtain an image block total difference; in response to determining that the image block total difference is greater than a preset second image block total difference threshold, generating motion vector information; in response to determining that the image block total difference is greater than a preset first image block total difference threshold, or the motion vector information meets a preset motion vector condition, controlling the video acquisition device to perform a surveillance video frame rate adjustment operation. This implementation can achieve a low frame rate when no critical event occurs while maintaining low power consumption, and take into account the recovery to a normal frame rate when an event occurs, thereby reducing resource waste.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of security monitoring technology, and more particularly to a method, device, electronic device, and readable medium for adjusting the frame rate of surveillance video. Background Art

[0002] In security monitoring, to maintain a low frame rate when no critical events occur, while also ensuring a quick return to normal frame rate when an event (such as a moving object) occurs, some critical event detection methods are run simultaneously with low-frame-rate recording. Currently, the commonly used detection method is to run a program on the SoC (System on a Chip) or an algorithm on the NPU (Neural Processing Unit) to determine whether a critical event has occurred.

[0003] However, when using the above-mentioned key event detection method to adjust the surveillance video frame rate, the following technical problems often occur:

[0004] SoC and NPU integrate a large number of functions and performance, such as processors, memory, graphics processors, communication interfaces, etc. These components consume electricity during operation, resulting in high power consumption of SoC and NPU and waste of resources.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the Invention

[0006] The content of this disclosure is used to briefly introduce concepts that will be described in detail in the detailed description section below. The content of this disclosure is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0007] Some embodiments of the present disclosure provide a method, device, electronic device, and computer-readable medium for adjusting the frame rate of surveillance video to solve one or more of the technical problems mentioned in the background technology section above.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for adjusting the frame rate of surveillance video recording, the method comprising: acquiring a current surveillance video frame through an associated video acquisition device; obtaining a previous surveillance video frame corresponding to the above-mentioned current surveillance video frame; segmenting the above-mentioned previous surveillance video frame and the above-mentioned current surveillance video frame respectively to obtain a previous surveillance image block set corresponding to the above-mentioned previous surveillance video frame and a current surveillance image block set corresponding to the above-mentioned current surveillance video frame; performing a difference processing on each current surveillance image block in the above-mentioned current surveillance image block set and a previous surveillance image block corresponding to the above-mentioned current surveillance image block in the above-mentioned previous surveillance image block set to obtain an image block difference; accumulating the obtained image block differences to obtain a total image block difference. ; Determine whether the total difference of the above-mentioned image blocks is greater than a preset first image block total difference threshold; in response to determining that the total difference of the above-mentioned image blocks is less than or equal to the above-mentioned preset first image block total difference threshold, determine whether the total difference of the above-mentioned image blocks is greater than a preset second image block total difference threshold; in response to determining that the total difference of the above-mentioned image blocks is greater than the above-mentioned preset second image block total difference threshold, generate motion vector information corresponding to the above-mentioned current monitoring video frame according to the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame; determine whether the above-mentioned motion vector information meets the preset motion vector condition; in response to determining that the total difference of the above-mentioned image blocks is greater than the above-mentioned preset first image block total difference threshold, or the above-mentioned motion vector information meets the preset motion vector condition, control the above-mentioned video acquisition device to perform a monitoring video frame rate adjustment operation.

[0009] In a second aspect, some embodiments of the present disclosure provide a surveillance video frame rate adjustment device, the device comprising: an acquisition unit configured to acquire a current surveillance video frame through an associated video acquisition device; an acquisition unit configured to acquire a previous surveillance video frame corresponding to the current surveillance video frame; a segmentation processing unit configured to perform segmentation processing on the previous surveillance video frame and the current surveillance video frame, respectively, to obtain a previous surveillance image block set corresponding to the previous surveillance video frame and a current surveillance image block set corresponding to the current surveillance video frame; a difference processing unit configured to perform difference processing on each current surveillance image block in the current surveillance image block set with the previous surveillance image block corresponding to the current surveillance image block in the previous surveillance image block set, to obtain an image block difference; and an accumulation processing unit configured to accumulate the obtained image block differences to obtain a total image block difference. The first determination unit is configured to determine whether the above-mentioned image block total difference is greater than a preset first image block total difference threshold; the second determination unit is configured to determine whether the above-mentioned image block total difference is greater than a preset second image block total difference threshold in response to determining that the above-mentioned image block total difference is less than or equal to the above-mentioned preset first image block total difference threshold; the generation unit is configured to generate motion vector information corresponding to the above-mentioned current monitoring video frame based on the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame in response to determining that the above-mentioned image block total difference is greater than the above-mentioned preset second image block total difference threshold; the third determination unit is configured to determine whether the above-mentioned motion vector information meets a preset motion vector condition; the control unit is configured to control the above-mentioned video acquisition device to perform a monitoring video frame rate adjustment operation in response to determining that the above-mentioned image block total difference is greater than the above-mentioned preset first image block total difference threshold, or the above-mentioned motion vector information meets the preset motion vector condition.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: 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 above.

[0011] 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 of the first aspect is implemented.

[0012] The above-described embodiments of the present disclosure have the following beneficial effects: The surveillance video frame rate adjustment method of some embodiments of the present disclosure can achieve a low frame rate when no critical events occur while maintaining low power consumption, while also allowing for recovery to a normal frame rate when an event occurs, thereby reducing resource waste. Specifically, the reason for resource waste is that the SoC and NPU integrate a large number of functions and performance features, such as processors, memory, graphics processors, and communication interfaces. These components require power consumption during operation, resulting in high power consumption of the SoC and NPU. Based on this, the surveillance video frame rate adjustment method of some embodiments of the present disclosure first captures a current surveillance video frame using an associated video capture device. Next, a previous surveillance video frame corresponding to the current surveillance video frame is obtained. Thus, the obtained previous surveillance video frame can be used for comparison with the current surveillance video frame to determine whether a critical event has occurred. Then, the previous surveillance video frame and the current surveillance video frame are segmented to obtain a previous surveillance image block set corresponding to the previous surveillance video frame and a current surveillance image block set corresponding to the current surveillance video frame. Thus, the previous surveillance video frame and the current surveillance video frame can be divided into multiple image blocks for individual block comparison. Subsequently, each current surveillance image block in the current surveillance image block set is subtracted from the previous surveillance image block corresponding to the current surveillance image block in the previous surveillance image block set to obtain an image block difference. Thus, by subtracting two image blocks corresponding to the same position, the degree of distinction between the two image blocks can be determined. The obtained image block differences are then accumulated to obtain a total image block difference. Thus, by accumulating the differences between each two image blocks, the overall difference between the previous surveillance video frame and the current surveillance video frame can be determined. Subsequently, it is determined whether the total image block difference is greater than a preset first image block total difference threshold. If the total image block difference is greater than the preset first image block total difference threshold, it is determined that the overall difference between the previous surveillance video frame and the current surveillance video frame is significant, indicating that a critical event has occurred. Then, in response to determining that the total image block difference is less than or equal to the preset first image block total difference threshold, it is determined whether the total image block difference is greater than a preset second image block total difference threshold. Thus, if the occurrence of a critical event is not currently determined, the total image block difference is again determined to be greater than a preset second image block total difference threshold. If the total image block difference is determined to be greater than the preset second image block total difference threshold, a determination is made that a certain overall difference exists between the previous surveillance video frame and the current surveillance video frame, i.e., a suspected critical event is currently occurring. Subsequently, in response to determining that the total image block difference is greater than the preset second image block total difference threshold, motion vector information corresponding to the current surveillance video frame is generated based on the previous surveillance video frame and the current surveillance video frame.Thus, when a critical event is suspected, the encoder can determine the motion vector corresponding to the current surveillance video frame, and based on the motion vector, re-evaluate the degree of difference between the previous surveillance video frame and the current surveillance video frame. Then, a determination is made as to whether the motion vector information satisfies a preset motion vector condition. Therefore, when it is determined that the motion vector corresponding to the motion vector information satisfies the preset motion vector condition, it can be determined that the previous surveillance video frame and the current surveillance video frame differ significantly, thus confirming the occurrence of a critical event. Finally, in response to determining that the total image block difference is greater than the preset first image block total difference threshold, or that the motion vector information satisfies the preset motion vector condition, the video capture device is controlled to perform a surveillance video frame rate adjustment operation. Thus, when a critical event is determined to have occurred, the frame rate can be increased to obtain a clearer image. Because image signal processor (ISP) adjustment and encoding are mandatory components during video recording, regardless of whether the motion detection algorithm is running, adding some simple logic to the image ISP adjustment and encoding operations has virtually no impact on power consumption. Therefore, the surveillance video frame rate adjustment method of some embodiments of the present disclosure can run the motion detection algorithm during image ISP adjustment and encoding without relying on SoC or NPU, thereby achieving a low frame rate when no critical events occur while maintaining low power consumption, and taking into account the recovery to a normal frame rate when an event occurs, thereby reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the 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.

[0014] Figure 1 is a flowchart of some embodiments of the surveillance video frame rate adjustment method according to the present disclosure;

[0015] Figure 2 1 is a schematic structural diagram of some embodiments of the surveillance video frame rate adjustment device according to the present disclosure;

[0016] Figure 3 It is a structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] 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 described 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 for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0018] 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 may be combined with each other.

[0019] It should be noted that the concepts of "first" and "second" mentioned in this 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.

[0020] It should be noted that the modifications of "one" and "multiple" 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, they should be understood as "one or more".

[0021] 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.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] refer to Figure 1 , shows a process 100 of some embodiments of the monitoring video frame rate adjustment method according to the present disclosure. The monitoring video frame rate adjustment method includes the following steps:

[0024] Step 101: Capture the current monitoring video frame through the associated video capture device.

[0025] In some embodiments, the execution entity (e.g., an electronic device) of the surveillance video frame rate adjustment method may capture the current surveillance video frame via an associated video capture device. The video capture device may be a camera. In practice, the execution entity may capture the current surveillance video frame via the associated video capture device.

[0026] Step 102: Acquire a previous surveillance video frame corresponding to the current surveillance video frame.

[0027] In some embodiments, the execution entity may obtain a previous surveillance video frame corresponding to the current surveillance video frame. The previous surveillance video frame may be the most recently captured surveillance video frame. In practice, the execution entity may obtain the previous surveillance video frame corresponding to the current surveillance video frame from a storage device. The storage device may be a memory card. In practice, each surveillance video frame captured by the video capture device may be stored in the storage device.

[0028] Step 103 : Segment the previous monitoring video frame and the current monitoring video frame respectively to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame.

[0029] In some embodiments, the execution entity may perform segmentation processing on the previous monitoring video frame and the current monitoring video frame, respectively, to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame. The execution entity may perform average segmentation processing on the previous monitoring video frame and the current monitoring video frame, respectively, to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame. The number of previous monitoring image blocks included in the previous monitoring image block set is the same as the number of current monitoring image blocks included in the current monitoring image block set.

[0030] Optionally, the above execution entity may further perform the following steps:

[0031] In the first step, infrared radiation from the environment is detected using an associated infrared detection sensor to obtain current infrared radiation information. The infrared detection sensor can be located on one side of the video capture device. The current infrared radiation information can be infrared radiation energy representative of the detected object.

[0032] The second step is to obtain the previous environmental infrared radiation information corresponding to the current environmental infrared radiation information. The previous environmental infrared radiation information may be the infrared radiation energy in the most recent collected environment. In practice, the execution entity may obtain the previous environmental infrared radiation information corresponding to the current environmental infrared radiation information from a storage device.

[0033] In the third step, the absolute value of the difference between the current ambient infrared radiation energy corresponding to the current ambient infrared radiation information and the previous ambient infrared radiation energy corresponding to the previous ambient infrared radiation information is determined as the ambient infrared radiation difference.

[0034] The fourth step is to determine whether the ambient infrared radiation difference is greater than a preset ambient infrared radiation difference threshold. The preset ambient infrared radiation difference threshold may be a pre-set ambient infrared radiation difference threshold. Specifically, in response to determining that the ambient infrared radiation difference is greater than the preset ambient infrared radiation difference threshold, it may be determined that an event has occurred in the environment.

[0035] Step 5: In response to determining that the ambient infrared radiation difference is greater than the preset ambient infrared radiation difference threshold, controlling the video capture device to adjust the surveillance video frame rate. In practice, in response to determining that an event has occurred in the environment, the execution entity may increase the frame rate of the video captured by the video capture device to a preset frame rate. The preset frame rate may be a preset frame rate of a camera. Specifically, the preset frame rate may be the preset frame rate of the camera used to capture images of the environment at the time of the event.

[0036] In some optional implementations of some embodiments, the execution subject may segment the previous monitoring video frame and the current monitoring video frame separately to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame by performing the following steps: In response to determining that the environmental infrared radiation difference is less than or equal to the preset environmental infrared radiation difference threshold, segment the previous monitoring video frame and the current monitoring video frame separately to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame. It can be understood that when the infrared detection sensor does not detect the occurrence of an event, it can be detected again through image ISP adjustment and encoding.

[0037] Step 104 : performing a difference process between each current monitoring image block in the current monitoring image block set and a previous monitoring image block corresponding to the current monitoring image block in the previous monitoring image block set to obtain an image block difference value.

[0038] In some embodiments, the execution entity may perform a difference process on each current monitoring image block in the current monitoring image block set and a previous monitoring image block in the previous monitoring image block set corresponding to the current monitoring image block to obtain an image block difference.

[0039] In some optional implementations of some embodiments, the execution entity may perform subtraction processing on each current monitoring image block in the current monitoring image block set and a previous monitoring image block in the previous monitoring image block set corresponding to the current monitoring image block to obtain an image block difference value by performing the following steps:

[0040] For each current monitoring image block in the current monitoring image block set, the following determination steps are performed:

[0041] The first step is to determine the image block position information corresponding to the current monitoring image block. In practice, the execution entity may determine the coordinates of the current monitoring image block in the current monitoring video frame as the image block position information corresponding to the current monitoring image block.

[0042] In a second step, a preceding monitoring image block whose corresponding image block position in the preceding monitoring image block set is identical to the image block position information is determined as the target preceding monitoring image block. The image block position corresponding to the target preceding monitoring image block may be the coordinates of the target preceding monitoring image block in the preceding monitoring video frame.

[0043] In the third step, the pixel difference between the current monitoring image block and the previous monitoring image of the target is determined as the image block difference.

[0044] Step 105 , performing accumulation processing on the obtained difference values ​​of each image block to obtain the total difference of the image blocks.

[0045] In some embodiments, the execution entity may accumulate the obtained image block differences to obtain a total image block difference. In practice, the execution entity may determine the total image block difference as the sum of the image block differences.

[0046] Step 106: Determine whether the total image block difference is greater than a preset first total image block difference threshold.

[0047] In some embodiments, the execution entity may determine whether the total image block difference is greater than a preset first image block total difference threshold. The preset first image block total difference threshold may be a pre-set total image block difference. In practice, in response to determining that the total image block difference is greater than the preset first image block total difference threshold, the execution entity may determine that a critical event has occurred.

[0048] Step 107 : In response to determining that the image block total difference is less than or equal to a preset first image block total difference threshold, determine whether the image block total difference is greater than a preset second image block total difference threshold.

[0049] In some embodiments, the execution entity may determine whether the image block total difference is greater than a preset second image block total difference threshold in response to determining that the image block total difference is less than or equal to the preset first image block total difference threshold. The preset second image block total difference threshold is less than the preset first image block total difference threshold. The preset second image block total difference threshold may be a preset coded image block total difference.

[0050] Step 108 : In response to determining that the total image block difference is greater than a preset second total image block difference threshold, motion vector information corresponding to the current monitoring video frame is generated according to the previous monitoring video frame and the current monitoring video frame.

[0051] In some embodiments, the execution entity may generate motion vector information corresponding to the current monitoring video frame based on the previous monitoring video frame and the current monitoring video frame in response to determining that the total image block difference is greater than the preset second image block total difference threshold.

[0052] In some optional implementations of some embodiments, based on the previous surveillance video frame and the current surveillance video frame, the execution entity may generate motion vector information corresponding to the current surveillance video frame by performing the following steps:

[0053] The following steps are performed for each current monitoring image block in the current monitoring image block set corresponding to the current monitoring video frame:

[0054] The first step is to perform matching processing on the previous monitoring image blocks in the previous monitoring image block set corresponding to the previous monitoring video frame based on the current monitoring image block to obtain an image block matching value set. In practice, first, for each previous monitoring image block in the previous monitoring image block set corresponding to the previous monitoring video frame, the execution entity may determine the image block similarity between the previous monitoring image block and the current monitoring image block. As an example, the execution entity may determine the minimum mean square error between the previous monitoring image block and the current monitoring image block as the image block similarity. Then, the execution entity may determine each determined image block similarity as an image block matching value to obtain an image block matching value set.

[0055] In the second step, based on the image block matching value set, a previous monitoring image block that meets a preset matching condition is selected from the previous monitoring image block set as the target previous monitoring image block. The preset matching condition may be that the image block matching value corresponding to the previous monitoring image block is the largest.

[0056] The third step is to determine the motion vector between the target's previous monitoring image block and the current monitoring image block, obtaining motion vector information. The motion vector can be used to describe the displacement from the coordinates of the target's previous monitoring image block in the previous monitoring image to the coordinates of the current monitoring image block in the current monitoring image. In practice, the execution entity can determine the motion vector between the target's previous monitoring image block and the current monitoring image block using an encoder, and use the determined motion vector as the motion vector information.

[0057] In some optional implementations of some embodiments, based on the current monitoring image block, the execution entity may perform matching processing on the previous monitoring image block in the previous monitoring image block set corresponding to the previous monitoring video frame by performing the following steps to obtain an image block matching value set:

[0058] The first step is to determine the matching area corresponding to the previous monitoring image block based on the current monitoring video frame and the current monitoring image block. The matching area can be an image area that represents the previous monitoring image block that needs to be matched with the current monitoring image block. In practice, the execution entity can determine the matching area of ​​the previous monitoring image block based on the size of the current monitoring video frame and the size of the current monitoring image block. Specifically, the execution entity can determine the matching area of ​​the previous monitoring video frame based on a preset matching area correspondence table. The preset matching area correspondence table can be used to represent the correspondence between the size of the current monitoring video frame and the size of the current monitoring image block and the matching area.

[0059] The second step is to determine the matching step length corresponding to the previous monitoring image block based on the current monitoring image block. The matching step length can be an image distance that represents the need for a single matching between the previous monitoring image block and the current monitoring image block. In practice, the execution entity can determine the matching step length of the previous monitoring image block based on the size of the current monitoring image block. Specifically, the execution entity can determine the matching step length of the previous monitoring video frame based on a preset matching step length corresponding table. The preset matching step length corresponding table can be used to represent the corresponding relationship between the size of the current monitoring image block and the matching step length. For example, the matching step length of the previous monitoring image block can be the width of the current monitoring image block.

[0060] The third step is to determine the set of previously monitored image blocks to be matched based on the matching area and the matching step. In practice, the execution entity may determine the set of previously monitored image blocks to be matched by dividing the image within the matching area according to the matching step.

[0061] In the fourth step, for each of the preceding monitoring image blocks to be matched in the preceding monitoring image block set, the following steps are performed:

[0062] The first sub-step is: for each pixel of the previous monitoring image block in the previous monitoring image block to be matched, determining the absolute value of the pixel difference between the pixel of the previous monitoring image block and the pixel of the current monitoring image block corresponding to the pixel of the previous monitoring image block in the current monitoring image block.

[0063] Second sub-step: determining the sum of the determined absolute values ​​of the pixel differences as the image block matching value.

[0064] Step 109: Determine whether the motion vector information meets a preset motion vector condition.

[0065] In some embodiments, the execution entity may determine whether the motion vector information satisfies a preset motion vector condition. The preset motion vector condition may be that the motion vector corresponding to the motion vector information is greater than a preset motion vector threshold. The preset motion vector threshold may be a pre-set motion vector threshold. It can be understood that, in response to determining that the motion vector corresponding to the motion vector information is greater than the preset motion vector threshold, it is determined that a key event has occurred.

[0066] Step 110 : In response to determining that the total image block difference is greater than a preset first image block total difference threshold, or the motion vector information satisfies a preset motion vector condition, controlling the video capture device to perform a surveillance video frame rate adjustment operation.

[0067] In some embodiments, the execution entity may control the video capture device to perform a surveillance video frame rate adjustment operation in response to determining that the total image block difference is greater than the preset first image block total difference threshold, or that the motion vector information satisfies a preset motion vector condition. In practice, in response to determining that the total image block difference is greater than the preset first image block total difference threshold, or that the motion vector information satisfies a preset motion vector condition, the execution entity may increase the frame rate of the video captured by the video capture device to a preset frame rate. The preset frame rate may be a pre-set frame rate set when a key event occurs.

[0068] In the process of adopting technical solutions to solve the above technical problems, the following technical problem 2 is often accompanied: when the video recorded by the surveillance video is sent to the relevant terminal equipment, it needs to be encoded and compressed to reduce the transmission pressure. The current encoding method is to use the same encoding algorithm in the surveillance video process. When the compression of the adopted encoding algorithm is relatively high, the image quality is poor. When a critical event occurs, the image clarity is poor, which easily causes the loss of key images and leads to poor security effects. When the adopted encoding algorithm has a low compression rate and high image quality, the pressure of video transmission is greater, resulting in high power consumption and waste of resources. In response to the above technical problem 2, the conventional solution is generally to encode the surveillance video using an encoding algorithm with a high compression rate and high image quality. However, the above conventional solution still has the following problems: the algorithm with a high compression rate and high image quality is highly complex and consumes more computing resources.

[0069] Considering the problems of the above conventional solutions, facing the second technical problem mentioned above: when the video recorded by the surveillance camera is sent to the relevant terminal equipment, it needs to be encoded and compressed to reduce the transmission pressure. The current encoding method is to use the same encoding algorithm in the surveillance video process. When the compression ratio of the encoding algorithm used is relatively high, the image quality is poor. When a critical event occurs, the image clarity is poor, which easily causes the loss of key images and leads to poor security effects. When the compression ratio of the encoding algorithm used is low and the image quality is high, the pressure of video transmission is greater, resulting in higher power consumption and waste of resources. In combination with the current technical status, it can be decided to adopt the following solutions:

[0070] Optionally, the execution entity may further perform the following sending steps:

[0071] In a first step, in response to determining that the motion vector information does not satisfy the preset motion vector condition, determining whether the motion vector corresponding to the motion vector information is less than a preset lossy motion vector threshold. The preset lossy motion vector threshold may be a pre-set motion vector threshold. The preset lossy motion vector threshold may be less than a preset motion vector threshold.

[0072] In the second step, in response to determining that the motion vector corresponding to the above motion vector information is less than the preset lossy motion vector threshold, the lossy video frame encoding method corresponding to the above motion vector information is filtered out from the preset lossy video frame encoding method matching information set based on the above motion vector information. Wherein, each preset lossy video frame encoding method matching information in the above preset lossy video frame encoding method matching information set may include a preset lossy video frame encoding method and a preset motion vector range. In practice, the above execution entity may determine the preset motion vector range corresponding to the motion vector corresponding to the above motion vector information. Then, the above execution entity may determine the preset lossy video frame encoding method corresponding to the preset motion vector range corresponding to the above motion vector information as the lossy video frame encoding method.

[0073] In the third step, the motion vector information is encoded using the lossy video frame encoding method to obtain first video frame encoding information. The lossy video frame encoding method may be differential coding or predictive coding. Thus, when the motion vector of the current video frame is smaller (i.e., the change is smaller) than that of the previous video frame, the execution entity may encode the current video frame using a coding method with relatively high compression and less data duplication.

[0074] The fourth step is to determine the compression rate according to the motion vector information in response to determining that the motion vector corresponding to the motion vector information is greater than or equal to the preset lossy motion vector threshold. The compression rate can represent the degree of compression of the video frame. For example, the compression rate can be the coding length corresponding to the Huffman coding. In practice, the execution subject can determine the compression rate according to the preset compression rate matching information set. The preset compression rate matching information in the preset compression rate matching information set can include a preset compression rate and a preset motion vector range. Then, the execution subject can determine the preset compression rate matching information including the preset motion vector range corresponding to the motion vector information in the preset compression rate matching information set as the target compression rate matching information. Afterwards, the execution subject can determine the preset compression rate included in the target compression rate matching information as the compression rate corresponding to the motion vector information.

[0075] In step 5, the current surveillance video frame is encoded according to the compression ratio to obtain second video frame encoding information. As an example, the execution entity may encode the current surveillance video frame using Huffman coding according to the encoding length represented by the compression ratio to obtain second video frame encoding information.

[0076] In step 6, in response to determining that the image block total difference is greater than the preset first image block total difference threshold, or the motion vector information satisfies a preset motion vector condition, the current surveillance video frame is encoded using a lossless video frame encoding method to obtain third video frame encoding information. The lossless video frame encoding method may be arithmetic coding or run-length coding.

[0077] In the seventh step, the first video frame coding information, the second video frame coding information or the third video frame coding information is determined as target video frame coding information.

[0078] In the eighth step, the target video frame encoding information is sent to a related terminal device, which may be a computer or a mobile phone.

[0079] The above-mentioned content related to video frame encoding and transmission is an inventive point of an embodiment of the present disclosure, which solves the second technical problem: "When the video recorded by the surveillance video is sent to the relevant terminal device, it needs to be encoded and compressed to reduce the transmission pressure. The current encoding method is to use the same encoding algorithm during the surveillance video recording process. When the compression ratio of the encoding algorithm used is relatively high, the image quality is poor. When a critical event occurs, the image clarity is poor, which easily causes the loss of key images, resulting in poor security effects; when the compression ratio of the encoding algorithm used is relatively low and the image quality is relatively high, the pressure on video transmission is relatively high, resulting in high power consumption and waste of resources." The reasons for the waste of resources or poor security effects are as follows: When the video recorded by the surveillance video is sent to the relevant terminal device, it needs to be encoded and compressed to reduce the transmission pressure. The current encoding method is to use the same encoding algorithm during the surveillance video recording process. When the compression ratio of the encoding algorithm used is relatively high, the image quality is poor. When a critical event occurs, the image clarity is poor, which easily causes the loss of key images, resulting in poor security effects; when the compression ratio of the encoding algorithm used is relatively low and the image quality is relatively high, the pressure on video transmission is relatively high, resulting in high power consumption and waste of resources. If the above factors are solved, the security effect can be improved, power consumption can be reduced, and resources can be saved. In order to achieve this effect, the monitoring video frame rate adjustment method disclosed in the present invention can determine the difference between the current image frame and the previous image frame based on the motion vector information. When the difference is very small, it can be determined that the environment has not changed, and a coding method with a higher coding compression ratio can be used for encoding; when the difference is small, it can be determined that the degree of environmental change is small, and the compression ratio can be determined based on the motion vector, and a coding method with a lower coding compression ratio can be used for encoding; when the difference is large, it can be determined that the degree of environmental change is large, that is, a critical event has occurred, and a coding method with a lower compression ratio and more complete image retention can be used for encoding. As a result, when the environmental changes within the monitoring range are small, a coding method with a high compression ratio can be used for encoding, thereby reducing transmission pressure. When the environmental changes within the monitoring range are large, a coding method with a low compression ratio and complete image retention can be used for encoding, thereby improving image quality and improving security effects.

[0080] The above-described embodiments of the present disclosure have the following beneficial effects: The surveillance video frame rate adjustment method of some embodiments of the present disclosure can achieve a low frame rate when no critical events occur while maintaining low power consumption, while also allowing for recovery to a normal frame rate when an event occurs, thereby reducing resource waste. Specifically, the reason for resource waste is that the SoC and NPU integrate a large number of functions and performance features, such as processors, memory, graphics processors, and communication interfaces. These components require power consumption during operation, resulting in high power consumption of the SoC and NPU. Based on this, the surveillance video frame rate adjustment method of some embodiments of the present disclosure first captures a current surveillance video frame using an associated video capture device. Next, a previous surveillance video frame corresponding to the current surveillance video frame is obtained. Thus, the obtained previous surveillance video frame can be used for comparison with the current surveillance video frame to determine whether a critical event has occurred. Then, the previous surveillance video frame and the current surveillance video frame are segmented to obtain a previous surveillance image block set corresponding to the previous surveillance video frame and a current surveillance image block set corresponding to the current surveillance video frame. Thus, the previous surveillance video frame and the current surveillance video frame can be divided into multiple image blocks for individual block comparison. Subsequently, each current surveillance image block in the current surveillance image block set is subtracted from the previous surveillance image block corresponding to the current surveillance image block in the previous surveillance image block set to obtain an image block difference. Thus, by subtracting two image blocks corresponding to the same position, the degree of distinction between the two image blocks can be determined. The obtained image block differences are then accumulated to obtain a total image block difference. Thus, by accumulating the differences between each two image blocks, the overall difference between the previous surveillance video frame and the current surveillance video frame can be determined. Subsequently, it is determined whether the total image block difference is greater than a preset first image block total difference threshold. If the total image block difference is greater than the preset first image block total difference threshold, it is determined that the overall difference between the previous surveillance video frame and the current surveillance video frame is significant, indicating that a critical event has occurred. Then, in response to determining that the total image block difference is less than or equal to the preset first image block total difference threshold, it is determined whether the total image block difference is greater than a preset second image block total difference threshold. Thus, if the occurrence of a critical event is not currently determined, the total image block difference is again determined to be greater than a preset second image block total difference threshold. If the total image block difference is determined to be greater than the preset second image block total difference threshold, a determination is made that a certain overall difference exists between the previous surveillance video frame and the current surveillance video frame, i.e., a suspected critical event is currently occurring. Subsequently, in response to determining that the total image block difference is greater than the preset second image block total difference threshold, motion vector information corresponding to the current surveillance video frame is generated based on the previous surveillance video frame and the current surveillance video frame.Thus, when a critical event is suspected, the encoder can determine the motion vector corresponding to the current surveillance video frame, and based on the motion vector, re-evaluate the degree of difference between the previous surveillance video frame and the current surveillance video frame. Then, a determination is made as to whether the motion vector information satisfies a preset motion vector condition. Therefore, when it is determined that the motion vector corresponding to the motion vector information satisfies the preset motion vector condition, it can be determined that the previous surveillance video frame and the current surveillance video frame differ significantly, thus confirming the occurrence of a critical event. Finally, in response to determining that the total image block difference is greater than the preset first image block total difference threshold, or that the motion vector information satisfies the preset motion vector condition, the video capture device is controlled to perform a surveillance video frame rate adjustment operation. Thus, when a critical event is determined to have occurred, the frame rate can be increased to obtain a clearer image. Because image signal processor (ISP) adjustment and encoding are mandatory components during video recording, regardless of whether the motion detection algorithm is running, adding some simple logic to the image ISP adjustment and encoding operations has virtually no impact on power consumption. Therefore, the surveillance video frame rate adjustment method of some embodiments of the present disclosure can run the motion detection algorithm during image ISP adjustment and encoding without relying on SoC or NPU, thereby achieving a low frame rate when no critical events occur while maintaining low power consumption, and taking into account the recovery to a normal frame rate when an event occurs, thereby reducing resource waste.

[0081] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a surveillance video frame rate adjustment device. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0082] like Figure 2As shown, the surveillance video frame rate adjustment device 200 of some embodiments includes: an acquisition unit 201, an acquisition unit 202, a segmentation processing unit 203, a difference processing unit 204, an accumulation processing unit 205, a first determination unit 206, a second determination unit 207, a generation unit 208, a third determination unit 209 and a control unit 210. Among them, the acquisition unit 201 is configured to acquire the current monitoring video frame through the associated video acquisition device; the acquisition unit 202 is configured to acquire the previous monitoring video frame corresponding to the above-mentioned current monitoring video frame; the segmentation processing unit 203 is configured to perform segmentation processing on the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame respectively, and obtain the previous monitoring image block set corresponding to the above-mentioned previous monitoring video frame and the current monitoring image block set corresponding to the above-mentioned current monitoring video frame; the difference processing unit 204 is configured to perform difference processing on each current monitoring image block in the above-mentioned current monitoring image block set and the previous monitoring image block corresponding to the above-mentioned current monitoring image block in the above-mentioned previous monitoring image block set to obtain image block difference; the accumulation processing unit 205 is configured to accumulate the obtained image block differences to obtain the total image block difference; the first determination unit 206 is configured to determine Whether the total difference of the above-mentioned image blocks is greater than the preset first total difference threshold of the above-mentioned image blocks; the second determining unit 207 is configured to determine whether the total difference of the above-mentioned image blocks is greater than the preset second total difference threshold of the above-mentioned image blocks in response to determining that the total difference of the above-mentioned image blocks is less than or equal to the above-mentioned preset first total difference threshold of the above-mentioned image blocks; the generating unit 208 is configured to generate the motion vector information corresponding to the above-mentioned current monitoring video frame according to the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame in response to determining that the total difference of the above-mentioned image blocks is greater than the above-mentioned preset second total difference threshold of the above-mentioned image blocks; the third determining unit 209 is configured to determine whether the above-mentioned motion vector information meets the preset motion vector condition; the control unit 210 is configured to control the above-mentioned video acquisition device to perform the monitoring video frame rate adjustment operation in response to determining that the total difference of the above-mentioned image blocks is greater than the above-mentioned preset first total difference threshold of the above-mentioned image blocks, or the above-mentioned motion vector information meets the preset motion vector condition.

[0083] It is understood that the units described in the device 200 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 device 200 and the units included therein, and will not be repeated here.

[0084] Reference below Figure 3 , which shows a structural diagram of an electronic device 300 (eg, a computing device) suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic 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.

[0085] like Figure 3 As shown, the electronic device 300 may include a processing device 301 (e.g., a processor included in a camera device, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. Various programs and data required for the operation of the electronic device 300 are also stored in the RAM 303. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0086] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0087] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network via the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are performed.

[0088] It should be noted that the computer-readable medium described 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 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, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport 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 suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0089] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can 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.

[0090] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist independently without being assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: acquires the current monitoring video frame through the associated video acquisition device; obtains the previous monitoring video frame corresponding to the above-mentioned current monitoring video frame; performs segmentation processing on the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame respectively to obtain the previous monitoring image block set corresponding to the above-mentioned previous monitoring video frame and the current monitoring image block set corresponding to the above-mentioned current monitoring video frame; performs difference processing on each current monitoring image block in the above-mentioned current monitoring image block set and the previous monitoring image block corresponding to the above-mentioned current monitoring image block in the above-mentioned previous monitoring image block set to obtain the image block difference; performs accumulation processing on the obtained image block differences, Obtaining a total image block difference; determining whether the above-mentioned total image block difference is greater than a preset first image block total difference threshold; in response to determining that the above-mentioned total image block difference is less than or equal to the above-mentioned preset first image block total difference threshold, determining whether the above-mentioned total image block difference is greater than a preset second image block total difference threshold; in response to determining that the above-mentioned total image block difference is greater than the above-mentioned preset second image block total difference threshold, generating motion vector information corresponding to the above-mentioned current monitoring video frame based on the above-mentioned previous monitoring video frame and the above-mentioned current monitoring video frame; determining whether the above-mentioned motion vector information satisfies a preset motion vector condition; in response to determining that the above-mentioned total image block difference is greater than the above-mentioned preset first image block total difference threshold, or the above-mentioned motion vector information satisfies the preset motion vector condition, controlling the above-mentioned video acquisition device to perform a monitoring video frame rate adjustment operation.

[0091] 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 stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving 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., through the Internet using an Internet service provider).

[0092] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two 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 box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0093] The units described in some embodiments of the present disclosure may be implemented in software or hardware. The units described may also be provided in a processor. For example, they may be described as follows: a processor including an acquisition unit, an acquisition unit, a segmentation processing unit, a difference processing unit, an accumulation processing unit, a first determination unit, a second determination unit, a generation unit, a third determination unit, and a control unit. The names of these units do not, in some cases, constitute limitations on the units themselves. For example, the acquisition unit may also be described as a "unit that acquires the current monitoring video frame through an associated video acquisition device."

[0094] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and 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 chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0095] The above description is only an illustration of some preferred embodiments of the present disclosure and 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 the specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for adjusting the frame rate of a surveillance video, comprising: Capture the current surveillance video frame through the associated video capture device; Obtaining a previous surveillance video frame corresponding to the current surveillance video frame; Performing segmentation processing on the previous monitoring video frame and the current monitoring video frame respectively to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame; performing a difference process on each current monitoring image block in the current monitoring image block set and a previous monitoring image block in the previous monitoring image block set that corresponds to the current monitoring image block, to obtain an image block difference; The obtained differences of each image block are accumulated to obtain the total difference of the image block; Determining whether the total difference of the image block is greater than a preset first total difference threshold of the image block; In response to determining that the image block total difference is less than or equal to the preset first image block total difference threshold, determining whether the image block total difference is greater than a preset second image block total difference threshold, and when it is determined that the image block total difference is greater than the preset second image block total difference threshold, determining that a critical event is currently suspected to have occurred; In response to determining that the image block total difference is greater than the preset second image block total difference threshold, generating motion vector information corresponding to the current monitoring video frame according to the previous monitoring video frame and the current monitoring video frame; determining whether the motion vector information satisfies a preset motion vector condition, the preset motion vector condition being that a motion vector corresponding to the motion vector information is greater than a preset motion vector threshold, and in response to determining that the motion vector corresponding to the motion vector information is greater than the preset motion vector threshold, determining that a key event is currently occurring; In response to determining that the total image block difference is greater than the preset first image block total difference threshold, or the motion vector information satisfies a preset motion vector condition, controlling the video acquisition device to perform a surveillance video frame rate adjustment operation; In response to determining that the motion vector information does not satisfy the preset motion vector condition, determining whether a motion vector corresponding to the motion vector information is less than a preset lossy motion vector threshold; In response to determining that the motion vector corresponding to the motion vector information is less than a preset lossy motion vector threshold, filtering out, based on the motion vector information, a lossy video frame encoding mode corresponding to the motion vector information from a preset lossy video frame encoding mode matching information set; Encoding the motion vector information using the lossy video frame encoding method to obtain first video frame encoding information; In response to determining that the motion vector corresponding to the motion vector information is greater than or equal to the preset lossy motion vector threshold, determining a compression ratio according to the motion vector information; encoding the current surveillance video frame according to the compression rate to obtain second video frame encoding information; In response to determining that the total image block difference is greater than the preset first image block total difference threshold, or the motion vector information satisfies a preset motion vector condition, encoding the current monitoring video frame using a lossless video frame encoding method to obtain third video frame encoding information; determining the first video frame encoding information, the second video frame encoding information, or the third video frame encoding information as target video frame encoding information; The target video frame encoding information is sent to an associated terminal device.

2. The method according to claim 1, wherein The step of performing a difference process on each current monitoring image block in the current monitoring image block set and a previous monitoring image block in the previous monitoring image block set corresponding to the current monitoring image block to obtain an image block difference value includes: The following determination steps are performed for each current monitoring image block in the current monitoring image block set: Determining image block position information corresponding to the currently monitored image block; Determining a previous monitoring image block in the previous monitoring image block set whose corresponding image block position is identical to the image block position information as a target previous monitoring image block; The pixel difference between the current monitoring image block and the previous monitoring image of the target is determined as the image block difference value.

3. The method according to claim 1, wherein The step of generating motion vector information corresponding to the current monitoring video frame according to the previous monitoring video frame and the current monitoring video frame includes: The following steps are performed on each current monitoring image block in the current monitoring image block set corresponding to the current monitoring video frame: According to the current monitoring image block, matching processing is performed on a previous monitoring image block in a previous monitoring image block set corresponding to the previous monitoring video frame to obtain an image block matching value set; According to the image block matching value set, a previous monitoring image block that meets a preset matching condition is selected from the previous monitoring image block set as a target previous monitoring image block; Determine motion vector information between the target previous monitoring image block and the current monitoring image block.

4. The method according to claim 3, wherein: The matching process is performed on a previous monitoring image block in a previous monitoring image block set corresponding to the previous monitoring video frame according to the current monitoring image block to obtain an image block matching value set, including: Determining a matching area corresponding to the previous monitoring image block according to the current monitoring video frame and the current monitoring image block; Determining, according to the current monitoring image block, a matching step size corresponding to the previous monitoring image block; Determining a set of previous monitored image blocks to be matched according to the matching area and the matching step size; For each previous monitoring image block to be matched in the set of previous monitoring image blocks to be matched, perform the following steps: For each pixel of the previous monitoring image block in the to-be-matched previous monitoring image block, determining an absolute value of a pixel difference between the pixel of the previous monitoring image block and a pixel of the current monitoring image block corresponding to the pixel of the previous monitoring image block in the current monitoring image block; The sum of the determined absolute values ​​of the pixel differences is determined as the image block matching value.

5. The method according to claim 1, wherein The method further comprises: The infrared radiation of the environment is detected by the associated infrared detection sensor to obtain the infrared radiation information of the current environment; Acquiring previous environmental infrared radiation information corresponding to the current environmental infrared radiation information; determining an absolute value of a difference between the current ambient infrared radiation energy corresponding to the current ambient infrared radiation information and the previous ambient infrared radiation energy corresponding to the previous ambient infrared radiation information as an ambient infrared radiation difference; Determining whether the ambient infrared radiation difference is greater than a preset ambient infrared radiation difference threshold; In response to determining that the ambient infrared radiation difference is greater than the preset ambient infrared radiation difference threshold, the video acquisition device is controlled to perform a monitoring video frame rate adjustment operation.

6. The method according to claim 5, wherein: The segmentation processing is performed on the previous monitoring video frame and the current monitoring video frame respectively to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame, including: In response to determining that the ambient infrared radiation difference is less than or equal to the preset ambient infrared radiation difference threshold, the previous monitoring video frame and the current monitoring video frame are segmented and processed respectively to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame.

7. A surveillance video frame rate adjustment device, comprising: A collection unit is configured to collect the current monitoring video frame through an associated video collection device; an acquisition unit, configured to acquire a previous surveillance video frame corresponding to the current surveillance video frame; a segmentation processing unit configured to perform segmentation processing on the previous monitoring video frame and the current monitoring video frame respectively to obtain a previous monitoring image block set corresponding to the previous monitoring video frame and a current monitoring image block set corresponding to the current monitoring video frame; a difference processing unit configured to perform a difference processing on each current monitoring image block in the current monitoring image block set and a previous monitoring image block in the previous monitoring image block set that corresponds to the current monitoring image block, to obtain an image block difference value; an accumulation processing unit configured to accumulate the obtained differences of the image blocks to obtain a total difference of the image blocks; A first determining unit is configured to determine whether the total difference of the image block is greater than a preset first total difference threshold of the image block; a second determining unit configured to, in response to determining that the image block total difference is less than or equal to the preset first image block total difference threshold, determine whether the image block total difference is greater than a preset second image block total difference threshold, and when determining that the image block total difference is greater than the preset second image block total difference threshold, determine that a critical event is currently suspected to have occurred; a generating unit configured to, in response to determining that the image block total difference is greater than the preset second image block total difference threshold, generate motion vector information corresponding to the current monitoring video frame based on the previous monitoring video frame and the current monitoring video frame; a third determining unit configured to determine whether the motion vector information satisfies a preset motion vector condition, the preset motion vector condition being that a motion vector corresponding to the motion vector information is greater than a preset motion vector threshold, and in response to determining that the motion vector corresponding to the motion vector information is greater than the preset motion vector threshold, determining that a key event is currently occurring; a control unit configured to, in response to determining that the total image block difference is greater than the preset first image block total difference threshold, or that the motion vector information satisfies a preset motion vector condition, control the video capture device to perform a surveillance video frame rate adjustment operation; In response to determining that the motion vector information does not satisfy the preset motion vector condition, determining whether a motion vector corresponding to the motion vector information is less than a preset lossy motion vector threshold; In response to determining that the motion vector corresponding to the motion vector information is less than a preset lossy motion vector threshold, filtering out, based on the motion vector information, a lossy video frame encoding mode corresponding to the motion vector information from a preset lossy video frame encoding mode matching information set; Encoding the motion vector information using the lossy video frame encoding method to obtain first video frame encoding information; In response to determining that the motion vector corresponding to the motion vector information is greater than or equal to the preset lossy motion vector threshold, determining a compression ratio according to the motion vector information; encoding the current surveillance video frame according to the compression rate to obtain second video frame encoding information; In response to determining that the total image block difference is greater than the preset first image block total difference threshold, or the motion vector information satisfies a preset motion vector condition, encoding the current monitoring video frame using a lossless video frame encoding method to obtain third video frame encoding information; determining the first video frame encoding information, the second video frame encoding information, or the third video frame encoding information as target video frame encoding information; The target video frame encoding information is sent to an associated terminal device.

8. An electronic device comprising: 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 program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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