Video data transmission method and apparatus, electronic device, and medium

Abstract

Embodiments of the present application disclose a video data transmission method and device, electronic equipment and storage medium, comprising: performing real-time feature detection on an object in a current camera shooting area, generating a candidate target list and pushing to a monitoring device; receiving a target confirmation instruction issued by the monitoring device, locking the corresponding target object according to the instruction and extracting the real-time moving track of the target object; after hierarchical code rate encoding of the video data of the current camera according to the target tracking priority, transmitting to the monitoring device; according to the real-time moving track of the target object, predicting a pre-associated area that the target object is about to enter; sending target feature data and a pre-locking instruction to a pre-associated camera corresponding to the pre-associated area, so that the pre-associated camera completes the pre-recognition and tracking preparation of the target object in advance.

Description

Technical Field

[0001] This application relates to the field of image processing technology, specifically to a video data transmission method, apparatus, electronic device, and storage medium. Background Technology

[0002] In high-traffic areas such as shopping malls, industrial parks, communities, and transportation hubs, multiple network cameras are commonly deployed to build a comprehensive monitoring network. The cameras collect video data in real time and transmit it to the monitoring backend, where security personnel can view the video footage through the monitoring equipment to monitor and track suspicious persons, illegal targets, and other objects.

[0003] In existing surveillance systems, target tracking primarily relies on manual operation: after security personnel spot a target on a multi-view monitoring terminal, they manually lock onto the corresponding camera's view. If the target moves out of the current camera's field of view, they must manually relocate the target across multiple video feeds and switch between view feeds. This tracking process is cumbersome and slow. Furthermore, all cameras transmit video data at a fixed bitrate, with no priority distinction between target-tracking feeds and regular monitoring feeds. This leads to wasted bandwidth resources, and high-priority tracking feeds experience stuttering and delays.

[0004] Some related technologies propose cross-camera relay tracking schemes, which only initiate the tracking process of the next camera after the target enters the overlapping coverage area of ​​the cameras. This passive relay approach suffers from tracking gaps and disjointed image transitions. Furthermore, it fails to predict the target's movement trajectory in advance, preventing the next camera from completing target pre-identification and tracking preparation, resulting in a high probability of target loss during relay tracking. In addition, existing technologies do not incorporate tracking priority to achieve hierarchical encoding and transmission of video data, leading to low bandwidth utilization. They also fail to achieve synchronous acquisition and storage of associated objects within the target's independent area, resulting in insufficient information completeness for post-event tracing. Summary of the Invention

[0005] This application provides a video data transmission method, electronic device, apparatus, and storage medium to solve the technical problems of passive relay in traditional monitoring and tracking, lack of transmission priority, easy interruption in tracking, and low bandwidth utilization.

[0006] In a first aspect, embodiments of this application provide a video data transmission method, including: Real-time feature detection is performed on objects within the current camera's field of view, a candidate target list is generated, and the list is pushed to the monitoring equipment. Receive target confirmation instructions from monitoring equipment, lock the corresponding target object according to the instructions, and extract the real-time movement trajectory of the target object; The video data from the current camera is encoded according to the target tracking priority and then transmitted to the monitoring equipment. Based on the real-time movement trajectory of the target object, predict the pre-associated area that the target object will soon enter; Send target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance.

[0007] Optionally, in some embodiments of this application, the step of predicting the pre-associated area that the target object is about to enter based on the real-time movement trajectory of the target object includes: Based on the current camera's shooting area, pre-mark the pre-association area that has coverage connection with other cameras; Based on the target object's moving speed, moving direction, and real-time position, the target object's moving path is calculated using a trajectory fitting algorithm; Based on the movement path and the pre-defined pre-associated area, determine the target pre-associated area that the target object is about to enter.

[0008] Optionally, in some embodiments of this application, sending target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area includes: If there is only one pre-association camera corresponding to the pre-association area, when it is predicted that the target object is about to enter the pre-association area, the target feature data and pre-locking command are directly sent to the pre-association camera. After the pre-association camera completes target pre-identification, it sends a pre-lock success signal to the current camera, which continues to transmit video until the target object moves out of the shooting area.

[0009] Optionally, in some embodiments of this application, the method further includes: If there are at least two pre-association cameras corresponding to a pre-association area, the target feature data will be sent to all pre-association cameras. Obtain the pre-identification feedback results of each pre-associated camera, wherein the pre-identification feedback results include the feature matching degree of the target object and the image clarity; The optimal pre-association camera is selected based on feature matching degree and image clarity, and pre-locking commands are only issued to the optimal pre-association camera.

[0010] Optionally, in some embodiments of this application, the step of performing real-time feature detection on objects within the current camera's shooting area, generating a candidate target list, and pushing it to the monitoring device includes: Acquire the real-time video stream captured by the current camera, extract key frames at fixed intervals; perform human detection and feature extraction on the key frames to obtain the feature information of each object; The feature information and location information of each object are integrated into a candidate target list, which is then pushed to the monitoring equipment for staff to screen and confirm.

[0011] Optionally, in some embodiments of this application, the step of performing human detection and feature extraction on keyframes to obtain feature information of each object includes: Identify human body contours and facial regions in keyframes; extract global human body features and core facial features, and use the fused feature data as feature information for the corresponding object.

[0012] Optionally, in some embodiments of this application, the method further includes: If it is predicted that the target object will remain in the current camera's independent shooting area, stop trajectory prediction and pre-association command sending; collect information on surrounding associated objects in real time, and synchronously upload the associated object features and video data to the monitoring equipment for storage.

[0013] Secondly, embodiments of this application provide a video data transmission apparatus, including: The generation module is used to perform real-time feature detection on objects within the current camera's shooting area, generate a candidate target list, and push it to the monitoring equipment. The receiving module is used to receive target confirmation instructions sent by the monitoring equipment, lock the corresponding target object according to the instructions, and extract the real-time movement trajectory of the target object; The transmission module is used to encode the video data of the current camera according to the target tracking priority and then transmit it to the monitoring equipment. The prediction module is used to predict the pre-associated area that the target object will enter based on the real-time movement trajectory of the target object; The sending module is used to send target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area, so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance.

[0014] Accordingly, this application also provides an electronic device, including a memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as described in any of the methods above.

[0015] This application also provides a storage medium storing a processor program that, when executed by a processor, implements any of the methods described above.

[0016] This application provides a video data transmission method, apparatus, electronic device, and storage medium. The method involves real-time feature detection of objects within the current camera's shooting area, generating a candidate target list and pushing it to a monitoring device; receiving a target confirmation command from the monitoring device, locking onto the corresponding target object according to the command, and extracting the target object's real-time movement trajectory; encoding the video data from the current camera according to target tracking priority using hierarchical bitrate encoding, and then transmitting it to the monitoring device; predicting the pre-association area the target object will enter based on its real-time movement trajectory; and sending target feature data and a pre-lock command to the pre-association camera corresponding to the pre-association area, enabling the pre-association camera to complete pre-identification and tracking preparation of the target object in advance. In the video data transmission scheme provided in this application, the pre-association area the target will enter is determined in advance through trajectory prediction, and the pre-association camera is instructed to pre-identify the target in advance, achieving seamless cross-camera relay and solving the problem of easy target loss in traditional passive tracking. Simultaneously, hierarchical bitrate encoding of video data according to tracking priority ensures high-definition and smooth transmission of tracking footage, reduces bandwidth usage for non-critical footage, and improves overall bandwidth utilization. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the video data transmission method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of the video data transmission device provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0021] This application discloses a video data transmission method, apparatus, camera, and storage medium, applicable to multi-camera full-area monitoring scenarios such as large shopping malls, industrial parks, transportation hubs, and smart communities. The core of this method is to achieve seamless cross-camera tracking and efficient video data transmission by actively detecting targets, predicting trajectories, transmitting data in a tiered manner, and pre-linking cameras to lock onto targets in advance. This improves the intelligence level of the monitoring system and the ease of operation for security personnel. Before implementing the method described in this application, the basic deployment and parameter calibration of the monitoring network must be completed: Camera Deployment: Deploy multiple intelligent network cameras in the target monitoring area according to coverage requirements. All cameras establish communication connections with the monitoring backend and monitoring equipment through a local area network or 5G network. The cameras support human detection, feature extraction, trajectory calculation, hierarchical coding, and cross-machine command interaction functions. Area calibration: Each camera pre-defines its shooting area, dividing it into independent shooting areas (covered only by the current camera) and pre-associated areas (transitional areas that connect with the coverage of other cameras and are where the target is about to enter). A binding relationship is established between the pre-associated areas and the corresponding pre-associated cameras, and the calibration data is stored in the camera's local memory. Parameter configuration: preset keyframe extraction interval, graded bitrate standards (tracking priority: HD 4K bitrate; normal priority: SD 1080P bitrate; low priority: smooth 720P bitrate), trajectory fitting algorithm parameters, feature matching degree threshold, and image clarity threshold.

[0022] See Figure 1 The video data transmission method provided in this application includes steps S101 to S105, and the specific implementation is as follows: Step S101: Real-time feature detection and candidate target list push The camera continuously captures real-time video streams within the shooting area. The video stream consists of continuous image frames. To reduce computational pressure, the camera extracts key frames at preset fixed intervals. In this embodiment, the extraction interval is set to 1 second, that is, 1 key frame is extracted from the video stream every second.

[0023] After acquiring keyframes, the camera activates a human detection algorithm to identify all human targets in the keyframes and exclude non-target interference such as background, objects, and animals. The human detection algorithm can employ lightweight target detection models such as the YOLO series and SSD, adapting to the camera's on-device computing resources to achieve real-time detection.

[0024] After completing the human detection, feature extraction is performed on each detected human object: first, the human body contour boundary is identified to determine the object's position coordinates in the image; second, the core facial region is located to extract facial features such as facial features and facial contours; finally, the global human body contour features and the core facial features are fused to generate unique object feature information, which is stored in vector form for easy matching and transmission later.

[0025] The camera integrates all detected object feature information, real-time location coordinates, and timestamps into a candidate target list, which is then synchronously pushed to the monitoring equipment via the network. The monitoring equipment's display interface shows the candidate targets in thumbnail format, with each thumbnail corresponding to an object and labeled with its location and number, facilitating quick browsing and filtering by security personnel.

[0026] The core difference between this step and traditional technology is that traditional cameras only passively transmit video, and the target is searched for by humans in the picture; in this application, the camera actively completes object detection, feature extraction and candidate list push, transforming manual search into machine active screening, which greatly reduces the workload of security personnel, and is especially suitable for scenes with large traffic and complex scenes.

[0027] Step S102: Receive target confirmation command, lock the target and extract the movement trajectory. Security personnel select the target object (such as a suspicious person) to be tracked from the candidate target list of the monitoring equipment. After clicking confirm, the monitoring equipment generates a target confirmation instruction, which includes the target object's feature vector, number, and initial location information, and sends it to the current camera.

[0028] Upon receiving a target confirmation command, the camera immediately locks onto the corresponding target object and continuously tracks it in the video stream to prevent confusion with other objects. Simultaneously, the camera acquires the target object's position coordinates in real time, records position changes over time, and calculates the target's real-time trajectory using a trajectory fitting algorithm.

[0029] The specific process of trajectory calculation is as follows: the position coordinates of the target are collected in 5 consecutive key frames, and the target's moving speed (pixels / second) and moving direction (angle) are calculated in combination with the time interval. Linear fitting or Kalman filtering algorithm is used to remove abnormal data caused by position jitter and occlusion, and a smooth moving trajectory is generated. The trajectory data includes real-time position, moving speed, moving direction and predicted dwell time.

[0030] The purpose of extracting the movement trajectory is to provide data support for subsequent regional prediction. Compared with traditional techniques that only determine the current position of the target, this application uses trajectory data to achieve quantitative analysis of the target's movement trend, providing a basis for early pre-locking.

[0031] Step S103: Hierarchical bitrate encoding and video data transmission The camera determines the tracking priority of video data based on the target lock status: once the target is locked, the current camera's video data is set to high tracking priority; otherwise, it is set to normal or low priority.

[0032] Tiered bitrate encoding is initiated according to priority: high-priority videos use high-definition 4K bitrate encoding to ensure clear picture details, smooth transmission, and meet the needs of accurate tracking; normal priority videos use standard-definition 1080P bitrate to balance picture quality and bandwidth; low priority videos use smooth 720P bitrate to minimize bandwidth usage.

[0033] After encoding, the camera synchronously transmits the hierarchically encoded video data, the real-time trajectory of the target object, and feature information to the monitoring equipment. The monitoring equipment automatically magnifies and highlights the high-priority tracking footage, distinguishing it from other ordinary monitoring footage. Security personnel can continuously monitor the target's movements without manually switching between these feeds.

[0034] This step solves the bandwidth waste problem of traditional technology's full fixed bitrate transmission. In scenarios where monitoring network bandwidth is limited, it prioritizes the transmission quality of tracking images, avoids target loss due to image stuttering and delay, and at the same time reduces bandwidth consumption of non-critical images, thereby improving the overall transmission efficiency of the monitoring system.

[0035] Step S104: Predict the pre-association region based on real-time trajectory The camera retrieves pre-calibrated area data locally, matches the real-time movement trajectory with pre-associated areas and independent shooting areas, and determines the area the target is about to enter.

[0036] The specific prediction process is as follows: First, obtain the target's real-time location, speed, and direction of movement, and calculate the time it takes for the target to reach each pre-associated area from its current location; second, predict the target's movement path in the next 3-5 seconds using a trajectory fitting algorithm, and determine the pre-associated areas covered by the movement path; finally, determine the pre-associated areas that are completely covered by the movement path and that the target is about to enter as the target's pre-associated areas.

[0037] If the prediction indicates that the target will remain in the independent shooting area, trajectory prediction and pre-association command transmission will cease to avoid invalid command interactions. Simultaneously, the camera will detect related objects around the target in real time (objects that have physical contact with the target, walk alongside it, or remain at close range for more than 3 seconds), extract feature information and image data of these related objects, and synchronously upload the related object information, target object information, and video data to the monitoring equipment for storage, providing complete data for post-event tracing.

[0038] If the prediction indicates that the target is about to enter the pre-associated area, the next cross-machine pre-locking operation is executed. The trajectory prediction function transforms the traditional "relay after entry" into "pre-entry prediction," upgrading from passive response to proactive scheduling, and fundamentally avoiding tracking gaps.

[0039] Step S105: Send target data and pre-lock command to the pre-associated camera Based on the number of cameras bound to the pre-associated area, execution is divided into two scenarios: Scenario 1: With one pre-associated camera, when a target is predicted to enter the corresponding pre-associated area, the current camera directly sends the target feature data, target number, and pre-lock command to the pre-associated camera. Upon receiving the data, the pre-associated camera immediately initiates target pre-identification on its local camera feed, matching the real-time collected object features with the target feature data. When the feature matching degree reaches a preset threshold (90%), the pre-lock is deemed successful, and a pre-lock success signal is sent back to the current camera.

[0040] After receiving the pre-lock success signal, the current camera continues to transmit high-definition video until the target object completely moves out of the current camera's shooting area. Once the target moves out, the current camera automatically releases the target lock, resumes normal bitrate transmission, and the pre-associated camera automatically becomes the new current camera, continuing the tracking process to achieve seamless handover.

[0041] Scenario 2: The number of pre-associated cameras is at least 2. The current camera sends the target feature data to all pre-associated cameras. Each pre-associated camera simultaneously starts target pre-identification, calculates the feature matching degree and image clarity, and sends the pre-identification feedback results back to the current camera.

[0042] The current camera selects the optimal pre-association camera based on the feedback results: priority is given to cameras with a feature matching degree of 100% and an image clarity of ≥85%, which can capture the front of the target or a clear outline, and have the best tracking effect; if there are multiple cameras that meet the conditions, the camera with the earliest target entry time is selected.

[0043] Once the optimal pre-association camera is determined, the current camera only issues a pre-lock command to that camera, while other pre-association cameras cancel their pre-identification, saving computational resources. After the optimal pre-association camera completes its pre-lock, it takes over the tracking process, ensuring the continuity of target tracking.

[0044] This step uses a pre-locking mechanism to allow the next camera to complete target recognition preparation in advance, so that tracking can be started immediately when the target enters the shooting area.

[0045] This application provides a video data transmission method that performs real-time feature detection on objects within the current camera's shooting area, generates a candidate target list, and pushes it to the monitoring device; receives a target confirmation command from the monitoring device, locks the corresponding target object according to the command, and extracts the target object's real-time movement trajectory; encodes the video data of the current camera according to target tracking priority using hierarchical bitrate encoding, and then transmits it to the monitoring device; predicts the pre-association area that the target object will enter based on the target object's real-time movement trajectory; and sends target feature data and a pre-lock command to the pre-association camera corresponding to the pre-association area, so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance. In the video data transmission scheme provided in this application, the pre-association area that the target will enter is determined in advance through trajectory prediction, and the pre-association camera is instructed to pre-identify the target in advance, realizing seamless cross-machine relay and solving the problem of easy loss of targets in traditional passive tracking. At the same time, hierarchical bitrate encoding of video data according to tracking priority ensures high-definition and smooth transmission of tracking images, reduces bandwidth occupation of non-critical images, and improves overall bandwidth utilization.

[0046] To facilitate better implementation of the video data transmission method of this application embodiment, this application embodiment also provides a video data transmission device, wherein the meanings of the terms are the same as those in the video data transmission method described above, and specific implementation details can be found in the description of the system embodiment.

[0047] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a video data transmission device provided in an embodiment of this application. Specifically, the video data transmission device may include a generation module 201, a receiving module 202, a transmission module 203, a prediction module 204, and a sending module 205, as follows: The generation module 201 is used to perform real-time feature detection on objects within the current camera's shooting area, generate a candidate target list, and push it to the monitoring equipment. The receiving module 202 is used to receive the target confirmation command sent by the monitoring equipment, lock the corresponding target object according to the command, and extract the real-time movement trajectory of the target object; The transmission module 203 is used to perform hierarchical bitrate encoding on the video data of the current camera according to the target tracking priority and then transmit it to the monitoring equipment; Prediction module 204 is used to predict the pre-associated area that the target object will enter based on the real-time movement trajectory of the target object; The sending module 205 is used to send target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area, so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance.

[0048] This application provides a video data transmission device. A generation module 201 performs real-time feature detection on objects within the current camera's shooting area, generates a candidate target list, and pushes it to the monitoring device. A receiving module 202 receives a target confirmation command from the monitoring device, locks the corresponding target object according to the command, and extracts the target object's real-time movement trajectory. A transmission module 203 performs hierarchical bitrate encoding on the current camera's video data according to target tracking priority and transmits it to the monitoring device. A prediction module 204 predicts the pre-association area the target object will enter based on the target object's real-time movement trajectory. A sending module 205 sends target feature data and a pre-lock command to the pre-association camera corresponding to the pre-association area, enabling the pre-association camera to complete pre-identification and tracking preparation of the target object in advance. In the video data transmission scheme provided in this application, the pre-association area the target is about to enter is determined in advance through trajectory prediction, and the pre-association camera is instructed to pre-identify the target in advance, achieving seamless cross-camera relay and solving the problem of easy target loss in traditional passive tracking. Simultaneously, hierarchical bitrate encoding of video data according to tracking priority ensures high-definition and smooth transmission of tracking footage, reduces bandwidth usage of non-critical footage, and improves overall bandwidth utilization. Furthermore, embodiments of this application also provide an electronic device, such as... Figure 3 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically: The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more processor-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will understand that... Figure 3 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: Processor 301 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 302, and by calling data stored in memory 302, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, processor 301 may include one or more processing cores; preferably, processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless video data transmission. It is understood that the modem processor may not be integrated into processor 301.

[0049] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and video data transmission methods by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0050] The electronic device also includes a power supply 303 that supplies power to various components. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 303 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0051] The electronic device may also include an input unit 304, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0052] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in the embodiments of this application, the processing 301 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 302 according to the following instructions, and the processing 301 runs the applications stored in the memory 302 to realize various functions, as follows: The system performs real-time feature detection on objects within the current camera's field of view, generates a candidate target list, and pushes it to the monitoring equipment. It receives target confirmation commands from the monitoring equipment, locks onto the corresponding target object based on the command, and extracts the target object's real-time movement trajectory. It then performs hierarchical bitrate encoding on the current camera's video data according to target tracking priority and transmits it to the monitoring equipment. Based on the target object's real-time movement trajectory, it predicts the pre-association area the target object will soon enter. Finally, it sends target feature data and pre-lock commands to the pre-association cameras corresponding to the pre-association areas, enabling the pre-association cameras to complete pre-identification and tracking preparations for the target object in advance.

[0053] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0054] This application embodiment determines the pre-associated area that the target is about to enter in advance through trajectory prediction, and instructs the pre-associated camera to pre-identify the target in advance, realizing seamless cross-camera relay and solving the problem of easy target loss in traditional passive tracking. At the same time, the video data is graded and bitrate encoded according to tracking priority, ensuring high-definition and smooth transmission of tracking images, reducing bandwidth occupation of non-critical images, and improving overall bandwidth utilization.

[0055] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a processor-readable storage medium and loaded and executed by a processor.

[0056] Therefore, embodiments of this application provide a storage medium storing a plurality of instructions that can be loaded by a processor to execute steps in any of the video data transmission methods provided in embodiments of this application. For example, the instructions can execute the following steps: The system performs real-time feature detection on objects within the current camera's field of view, generates a candidate target list, and pushes it to the monitoring equipment. It receives target confirmation commands from the monitoring equipment, locks onto the corresponding target object based on the command, and extracts the target object's real-time movement trajectory. It then performs hierarchical bitrate encoding on the current camera's video data according to target tracking priority and transmits it to the monitoring equipment. Based on the target object's real-time movement trajectory, it predicts the pre-association area the target object will soon enter. Finally, it sends target feature data and pre-lock commands to the pre-association cameras corresponding to the pre-association areas, enabling the pre-association cameras to complete pre-identification and tracking preparations for the target object in advance.

[0057] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0058] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0059] Since the instructions stored in the storage medium can execute the steps of any of the video data transmission methods provided in the embodiments of this application, the beneficial effects that any of the video data transmission methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0060] The foregoing has provided a detailed description of a video data transmission method, apparatus, electronic device, and storage medium provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A video data transmission method, characterized in that, include: Real-time feature detection is performed on objects within the current camera's field of view, a candidate target list is generated, and the list is pushed to the monitoring equipment. Receive target confirmation instructions from monitoring equipment, lock the corresponding target object according to the instructions, and extract the real-time movement trajectory of the target object; The video data from the current camera is encoded according to the target tracking priority and then transmitted to the monitoring equipment. Based on the real-time movement trajectory of the target object, predict the pre-associated area that the target object will soon enter; Send target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance.

2. The method according to claim 1, characterized in that, The step of predicting the pre-associated area that the target object will soon enter based on the real-time movement trajectory of the target object includes: Based on the current camera's shooting area, pre-mark the pre-association area that has coverage connection with other cameras; Based on the target object's moving speed, moving direction, and real-time position, the target object's moving path is calculated using a trajectory fitting algorithm; Based on the movement path and the pre-defined pre-associated area, determine the target pre-associated area that the target object is about to enter.

3. The method according to claim 1, characterized in that, Sending target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area includes: If there is only one pre-association camera corresponding to the pre-association area, when it is predicted that the target object is about to enter the pre-association area, the target feature data and pre-locking command are directly sent to the pre-association camera. After the pre-association camera completes target pre-identification, it sends a pre-lock success signal to the current camera, which continues to transmit video until the target object moves out of the shooting area.

4. The method according to claim 1, characterized in that, The method further includes: If there are at least two pre-association cameras corresponding to a pre-association area, the target feature data will be sent to all pre-association cameras. Obtain the pre-identification feedback results of each pre-associated camera, wherein the pre-identification feedback results include the feature matching degree of the target object and the image clarity; The optimal pre-association camera is selected based on feature matching degree and image clarity, and pre-locking commands are only issued to the optimal pre-association camera.

5. The method according to claim 1, characterized in that, The step of performing real-time feature detection on objects within the current camera's field of view, generating a candidate target list, and pushing it to the monitoring equipment includes: Acquire the real-time video stream captured by the current camera, extract key frames at fixed intervals; perform human detection and feature extraction on the key frames to obtain the feature information of each object; The feature information and location information of each object are integrated into a candidate target list, which is then pushed to the monitoring equipment for staff to screen and confirm.

6. The method according to claim 5, characterized in that, The process of performing human detection and feature extraction on keyframes to obtain feature information for each object includes: Identify human body contours and facial regions in keyframes; extract global human body features and core facial features, and use the fused feature data as feature information for the corresponding object.

7. The method according to claim 1, characterized in that, The method further includes: If it is predicted that the target object will remain in the current camera's independent shooting area, stop trajectory prediction and pre-association command sending; collect information on surrounding associated objects in real time, and synchronously upload the associated object features and video data to the monitoring equipment for storage.

8. A video data transmission device, characterized in that, include: The generation module is used to perform real-time feature detection on objects within the current camera's shooting area, generate a candidate target list, and push it to the monitoring equipment. The receiving module is used to receive target confirmation instructions sent by the monitoring equipment, lock the corresponding target object according to the instructions, and extract the real-time movement trajectory of the target object; The transmission module is used to encode the video data of the current camera according to the target tracking priority and then transmit it to the monitoring equipment. The prediction module is used to predict the pre-associated area that the target object will enter based on the real-time movement trajectory of the target object; The sending module is used to send target feature data and pre-locking instructions to the pre-association camera corresponding to the pre-association area, so that the pre-association camera can complete the pre-identification and tracking preparation of the target object in advance.

9. An electronic device, characterized in that, include: A memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as steps of the video data transmission method according to any one of claims 1 to 7.

10. A storage medium, characterized in that, The computer processing program is stored and can be loaded by a processor and executed according to any one of claims 1 to 7.

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