Multi-camera synchronous data acquisition method and system

Abstract

The invention relates to the technical field of synchronous acquisition, in particular to a multi-camera synchronous data acquisition method and system, and the method comprises the following steps: based on a real-time video stream of a camera, analyzing a video frame, recognizing a moving object in a differentiated video stream, and carrying out the recognition of the moving object in the differentiated video stream; and synchronously recording the occurrence time and position change of the moving object in the differentiated camera to obtain view angle change data. According to the invention, the angle and focal length of the camera are synchronously adjusted to cope with the view angle change of different scenes, and the trigger time of the camera is uniformly configured and is synchronously started through the network, so that the time deviation is reduced, the analysis of the synchronous trigger data set and the timestamp adjustment are synchronously triggered, and the synchronization between the cameras is optimized; the consistency and synchronism of the video streams obtained from different angles are ensured, the data transmission parameters are dynamically adjusted according to the network condition, the efficiency and synchronization precision in the data transmission process are improved, and the influence of network delay and bandwidth change is effectively dealt with.

Description

Technical Field

[0001] The present invention relates to the field of synchronous acquisition technology, and in particular to a multi-camera synchronous data acquisition method and system thereof. Background Art

[0002] Synchronous acquisition technology involves the coordinated acquisition of multiple data sources to ensure the consistency and accuracy of data in time. This technology is widely used in image processing, video surveillance, and machine vision, and mainly solves the problem of time synchronization when multiple sensor devices collect data. In synchronous acquisition technology, the key is to synchronize data acquisition from multiple devices by adjusting the timestamp of the data. Synchronous acquisition technology can significantly improve the efficiency and accuracy of data processing, especially in application scenarios that require rapid processing of large amounts of real-time data.

[0003] Among them, the multi-camera synchronous data acquisition method is a method of using multiple cameras to collect video data simultaneously. The main purpose of this method is to provide synchronized video streams for occasions that require a wide viewing angle and high dynamic range coverage, such as public safety monitoring, traffic management, and high-end film and television production. Through the synchronous acquisition of multiple cameras, temporally consistent image data can be obtained from different viewing angles, which can then be used for three-dimensional reconstruction, environmental monitoring, or multi-view video analysis, providing data support for subsequent image analysis and decision support.

[0004] Traditional acquisition methods mainly focus on timestamp synchronization, but fail to fully address the impact of perspective deviation and ambient light changes on synchronization quality. This limitation is particularly evident in multi-cameras, where different cameras capturing the same scene will result in different image quality due to different angles and lighting, affecting subsequent image analysis and decision support. In addition, traditional methods do not consider real-time changes in network conditions when processing large-scale data stream synchronization, which can easily cause data transmission delays and packet loss in a highly dynamic network environment, thus affecting the overall data acquisition effect. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a multi-camera synchronous data acquisition method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for synchronous data acquisition of multiple cameras, comprising the following steps:

[0007] S1: Based on the real-time video stream of the camera, by analyzing the video frames, identifying the moving objects in the differentiated video stream, synchronously recording the appearance time and position changes of the moving objects in the differentiated camera, and obtaining the perspective change data;

[0008] S2: Based on the perspective change data, by comparing the positions of the same moving object in the differentiated camera images, identifying the angle deviation of each camera capturing the same scene, adjusting the angle and focal length of each camera, and obtaining a camera angle adjustment parameter;

[0009] S3: Based on the camera angle adjustment parameters, the ISO and exposure parameters of each camera are adjusted according to the ambient light intensity of each camera to obtain optimized shooting parameters;

[0010] S4: Based on the optimized shooting parameters, uniformly configure the trigger time of each camera, synchronously trigger each camera through the network, start image shooting, and obtain a synchronous trigger data set;

[0011] S5: Based on the synchronization trigger data set, compare and analyze the timestamp difference and frame rate inconsistency between each camera, and correct the synchronization error by adjusting the timestamp of the data packet to generate a synchronization error correction result;

[0012] S6: Based on the synchronization error correction result, dynamically adjust the camera video stream data transmission process, adjust the data packet sending time and receiving buffer parameters according to network delay and bandwidth changes, and obtain optimized synchronization acquisition results.

[0013] As a further solution of the present invention, the perspective change data includes the position coordinates, timestamp and relative speed of the moving object captured by the camera, the camera angle adjustment parameters include the focal length adjustment value and the perspective alignment index of the camera, the optimized shooting parameters include the adjusted ISO value, exposure compensation value and dynamic range information, the synchronization trigger data set includes the time setting of the synchronization trigger, the shooting parameter configuration of the camera and the start timestamp, the synchronization error correction result includes the accuracy value of the timestamp alignment, the frame rate consistency adjustment result and the synchronization accuracy index between cameras, and the optimized synchronization acquisition result includes the data transmission delay optimization value, the receiving buffer adjustment parameter and the network bandwidth utilization.

[0014] As a further solution of the present invention, based on the real-time video stream of the camera, by analyzing the video frames, identifying the moving objects in the differentiated video stream, and synchronously recording the appearance time and position change of the moving objects in the differentiated camera, the steps of obtaining the perspective change data are specifically as follows:

[0015] S101: Based on the real-time video stream of the camera, time-stamp each frame of the video stream, record the position coordinates and the time point of appearance of each moving object, and obtain basic position time data;

[0016] S102: Based on the basic position time data, compare the time stamps and position coordinates of the same moving object in multiple camera viewing angles, identify the appearance sequence of the moving object in each viewing angle, and obtain a moving object recognition record;

[0017] S103: Based on the mobile object recognition record, analyzing the position and time changes of the mobile object in the differentiated camera viewing angle, synchronously recording the changed position and the corresponding time, and obtaining viewing angle change data.

[0018] As a further solution of the present invention, based on the perspective change data, by comparing the positions of the same moving object in the differentiated camera images, identifying the angle deviation of each camera capturing the same scene, adjusting the angle and focal length of each camera, and obtaining the camera angle adjustment parameters are specifically as follows:

[0019] S201: Analyze the spatial coordinate position of the moving object in the picture captured by the differential camera based on the perspective change data, identify the angle deviation and capture direction values ​​corresponding to each camera, and obtain the perspective deviation analysis result;

[0020] S202: Analyze the adjustment target value of each camera angle and focal length based on the view angle deviation analysis result, and adjust the camera to adjust the angle and focal length of the camera to obtain a camera adjustment log;

[0021] S203: Based on the camera adjustment log, verify the effect of the adjusted camera settings, capture video data, analyze the perspective difference and the performance of the object in the adjusted picture, evaluate whether the perspective error is corrected, and obtain the camera angle adjustment parameters.

[0022] As a further solution of the present invention, based on the camera angle adjustment parameters, the ISO and exposure parameters of each camera are adjusted according to the ambient light intensity of each camera, and the steps of obtaining optimized shooting parameters are specifically as follows:

[0023] S301: Based on the camera angle adjustment parameter, the ambient light intensity at each camera position is measured by a light sensor, and the light intensity value at each camera position is recorded to obtain an ambient light data record;

[0024] S302: Based on the ambient light data record, adjust the ISO setting and exposure time of each camera to match the ambient light intensity, optimize the quality and consistency of image capture under differentiated lighting conditions, and obtain adjusted shooting parameters;

[0025] S303: Based on the adjusted shooting parameters, the image quality of each camera is evaluated by testing the image capture effect, and according to the evaluation results, ISO and exposure settings are adjusted to optimize the image quality and obtain optimized shooting parameters.

[0026] As a further solution of the present invention, based on the optimized shooting parameters, the trigger time of each camera is uniformly configured, each camera is synchronously triggered through the network, and image shooting is started. The steps of obtaining the synchronous trigger data set are specifically:

[0027] S401: Based on the optimized shooting parameters, a unified trigger time of each camera is set, and a network communication protocol is configured to adjust the camera to receive a trigger signal within a predetermined time to obtain a unified trigger configuration;

[0028] S402: Based on the unified trigger configuration, when data collection is required, a synchronous trigger signal is sent to each camera, the cameras are controlled to start shooting simultaneously according to the unified trigger configuration, and the actual trigger time of each camera is recorded to obtain a trigger time record;

[0029] S403: Based on the trigger time record, check the time synchronization accuracy, analyze the cause of the time deviation, adjust the network delay setting, reconfigure the trigger mechanism of the camera, avoid the startup deviation, and obtain a synchronous trigger data set.

[0030] As a further solution of the present invention, based on the synchronous trigger data set, the timestamp difference and frame rate inconsistency between each camera are compared and analyzed, and the synchronization error is corrected by adjusting the timestamp of the data packet. The steps of generating the synchronization error correction result are specifically as follows:

[0031] S501: extracting video stream data output by each camera based on the synchronous trigger data set, recording the timestamp and the number of frames per second of each video stream, and obtaining a time frame rate data table;

[0032] S502: Based on the time frame rate data table, compare the timestamp and frame rate of each camera, calculate the time offset and frame rate change, analyze the cameras with synchronization errors, and obtain the time frame rate difference analysis results;

[0033] S503: Based on the time frame rate difference analysis result, adjust the timestamp of the camera video stream with time deviation, synchronize the data stream, verify the temporal consistency of each camera output video, and obtain the synchronization error correction result.

[0034] As a further solution of the present invention, based on the synchronization error correction result, the camera video stream data transmission process is dynamically adjusted, and the sending time and receiving buffer parameters of the data packet are adjusted according to the network delay and bandwidth changes. The steps of obtaining the optimized synchronization acquisition result are specifically as follows:

[0035] S601: Based on the synchronization error correction result, monitor the delay and bandwidth status of the current network in real time, record the network performance indicators at different time points, and obtain real-time network monitoring information;

[0036] S602: Based on the real-time network monitoring information, adjusting the sending time of each camera data stream and the buffer parameters of the receiving end, matching the network fluctuation, optimizing the synchronization of the data packets between the camera and the server, and obtaining the adjusted data stream configuration information;

[0037] S603: Based on the adjusted data stream configuration information, detect the synchronization accuracy of the video stream output by each camera, verify the transmission effect of the video data in the network, and obtain an optimized synchronization acquisition result.

[0038] As a further solution of the present invention, the calculation formulas for adjusting the sending time of each camera data stream and the buffer parameter of the receiving end are respectively:

[0039]

[0040] and

[0041]

[0042] Among them, T adj is the adjusted sending time, T base represents the benchmark sending time, Δt represents the average network delay time, k 1 is the adjustment coefficient, BW curr Represents the current bandwidth, BW base represents the base bandwidth, k 2 is the weight parameter, k 3 is the buffer coefficient, B size is the adjusted buffer size, k 4 is the conversion factor.

[0043] A multi-camera synchronous data acquisition system, the multi-camera synchronous data acquisition system is used to execute the multi-camera synchronous data acquisition method, the system comprises:

[0044] The moving object recognition module is based on the real-time video stream of the camera. By analyzing the video frames, it identifies the moving objects in the differentiated video stream, and synchronously records the appearance time and position changes of the moving objects in the differentiated camera to obtain the view angle change data;

[0045] The shooting parameter adjustment module analyzes the angle deviation of each camera capturing the same scene based on the perspective change data, adjusts the angle and focal length of each camera, and adjusts the ISO and exposure parameters of each camera according to the ambient light intensity of each camera to obtain optimized shooting parameters;

[0046] The shooting trigger control module uniformly configures the trigger time of each camera based on the optimized shooting parameters, controls the cameras to capture the scene at the same time, synchronously triggers each camera through the network, starts image shooting, and obtains a synchronous trigger data set;

[0047] The synchronization error correction module compares and analyzes the timestamp difference and frame rate inconsistency between each camera based on the synchronization trigger data set, corrects the synchronization error by adjusting the timestamp of the data packet, and generates a synchronization error correction result;

[0048] The network fluctuation compensation module dynamically adjusts the camera video stream data transmission process based on the synchronization error correction result, and adjusts the data packet sending time and receiving buffer parameters according to network delay and bandwidth changes to obtain optimized synchronization acquisition results.

[0049] Compared with the prior art, the advantages and positive effects of the present invention are:

[0050] In the present invention, by synchronously adjusting the angle and focal length of the camera, the change of viewing angle of different scenes is coped with, the image deviation caused by the viewing angle error is effectively compensated, the image quality is optimized by real-time adjustment of the ambient light, and the clarity and quality of the image data are improved by adjusting the ISO and exposure parameters to adapt to various lighting conditions. By uniformly configuring the trigger time of the camera and starting it synchronously through the network, the time deviation is reduced and the time consistency of the scene capture is enhanced. The analysis and timestamp adjustment of the synchronously triggered data set are optimized to optimize the synchronization between cameras, reduce the impact of inconsistent frame rates and time offsets, ensure the consistency and synchronization of video streams acquired from different angles, and dynamically adjust data transmission parameters according to network conditions to improve the efficiency and synchronization accuracy during data transmission, and effectively cope with the impact of network delays and bandwidth changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0052] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0053] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0054] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0055] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0056] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0057] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0058] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0060] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0061] See also Figure 1 The present invention provides a technical solution: a method for synchronous data acquisition of multiple cameras, comprising the following steps:

[0062] S1: Based on the real-time video stream of the camera, by analyzing the video frames, identifying the moving objects in the differentiated video stream, synchronously recording the appearance time and position changes of the moving objects in the differentiated camera, and obtaining the perspective change data;

[0063] S2: Based on the perspective change data, the differences in the perspectives of multiple cameras are analyzed. By comparing the positions of the same moving object in the differentiated camera images, the angle deviation of each camera capturing the same scene is identified, and the angle and focal length of each camera are adjusted to compensate for the perspective error and obtain the camera angle adjustment parameters.

[0064] S3: adjusting parameters based on the camera angle, adjusting the ISO and exposure parameters of each camera according to the ambient light intensity of each camera, optimizing the image data capture quality, and obtaining optimized shooting parameters;

[0065] S4: Based on the optimized shooting parameters, the trigger time of each camera is uniformly configured, the cameras are controlled to capture the scene at the same time, each camera is synchronously triggered through the network, image shooting is started, time deviation during shooting is avoided, the time consistency of the scene is optimized, and a synchronous triggering data set is obtained;

[0066] S5: Based on the synchronization trigger data set, extract the timestamp and frame rate data of the current video stream of each camera, compare and analyze the timestamp difference and frame rate inconsistency between each camera, correct the synchronization error by adjusting the timestamp of the data packet, and generate the synchronization error correction result;

[0067] S6: Based on the synchronization error correction result, dynamically adjust the camera video stream data transmission process, adjust the data packet sending time and receiving buffer parameters according to the network delay and bandwidth changes, optimize the synchronization accuracy and efficiency of the video stream data during network transmission, and obtain the optimized synchronization acquisition result;

[0068] The view change data includes the position coordinates, timestamp and relative speed of the moving object captured by the camera. The camera angle adjustment parameters include the focal length adjustment value and view alignment index of the camera. The optimized shooting parameters include the adjusted ISO value, exposure compensation value and dynamic range information. The synchronization trigger data set includes the time setting of the synchronization trigger, the shooting parameter configuration of the camera and the start timestamp. The synchronization error correction results include the accuracy value of the timestamp alignment, the frame rate consistency adjustment results and the synchronization accuracy index between cameras. The optimized synchronization acquisition results include the data transmission delay optimization value, the receiving buffer adjustment parameters and the network bandwidth utilization.

[0069] See also Figure 2 Based on the real-time video stream of the camera, by analyzing the video frames, identifying the moving objects in the differentiated video stream, and synchronously recording the appearance time and position changes of the moving objects in the differentiated camera, the specific steps of obtaining the perspective change data are as follows:

[0070] S101: Based on the real-time video stream of the camera, time-stamp each frame of the video stream, record the position coordinates and the time point of appearance of each moving object, and obtain basic position time data;

[0071] Based on the real-time video stream of the camera, each frame of the video stream is time-stamped and a unique timestamp is assigned to each frame. The clock synchronization technology ensures the accuracy of the timestamp. The image processing technology is used to detect the moving objects in the video, and the target tracking algorithm is used to maintain the consistency of the identification of the object in the continuous frames. For each detected moving object, its position coordinates in each frame are recorded, and the timestamp of the frame is recorded at the same time to form a basic position time data set.

[0072] S102: Based on the basic position time data, compare the time stamps and position coordinates of the same moving object in multiple camera view angles, identify the appearance sequence of the moving object in each view angle, and obtain a moving object recognition record;

[0073] Based on the basic position and time data, by comparing the time stamps and position coordinates of the same moving object in different camera perspectives, the appearance sequence of the moving object in each perspective is identified. By accessing the data input of multiple cameras and performing the same object detection and time marking process as S101 on the video stream of each camera perspective, by comparing the position and time data sets from different cameras, the data association algorithm is used to match the position and time data of the same moving object recorded in each camera. By calculating the geometric transformation of the object position in different camera perspectives and the synchronous comparison of the timestamps, it is ensured that the sequence of the object in different perspectives can be accurately identified, and the moving object recognition record is obtained, which lists the appearance order and time of each object in each camera perspective.

[0074] S103: Based on the mobile object recognition record, analyze the position and time changes of the mobile object in the differentiated camera view, synchronously record the change position and corresponding time, and obtain the view change data.

[0075] Based on the mobile object recognition records, the position and time changes of the mobile object in the differentiated camera perspectives are analyzed. By integrating the position and time data of the mobile object under multiple perspectives, statistical analysis methods are used to evaluate the position change trend and time fluctuations. The position changes of each mobile object under different camera perspectives are mapped to a unified reference coordinate system, and the position offset and time difference are calculated to synchronously record the change position and corresponding time. Each change in position or time is recorded as an event. The event data includes the position coordinates before and after the change, the timestamp, and the change amount, and the perspective change data is generated. The data reflects the motion trajectory and time characteristics of the mobile object under different camera perspectives.

[0076] See also Figure 3 , based on the perspective change data, the differences in the perspectives of multiple cameras are analyzed. By comparing the positions of the same moving object in the differentiated camera images, the angle deviation of each camera capturing the same scene is identified, and the angle and focal length of each camera are adjusted to compensate for the perspective error. The specific steps for obtaining the camera angle adjustment parameters are as follows:

[0077] S201: Analyze the spatial coordinate position of the moving object in the picture captured by the differential camera based on the view angle change data, identify the angle deviation and capture direction values ​​corresponding to each camera, and obtain the view angle deviation analysis result;

[0078] Based on the perspective change data, the position data of moving objects obtained from different cameras are integrated and analyzed to determine the spatial coordinate position of the moving object in the picture captured by each camera. Using the spatial geometric transformation method, the data of each camera is mapped to a common three-dimensional space model for comparison and analysis. By calculating the coordinate differences under the perspective of each camera, the angle deviation and capture direction of each camera relative to the reference perspective are identified. The values ​​of the angle deviation and direction are recorded, and the optimization calculation is performed through the statistical analysis method to generate the perspective deviation analysis results, and the results list the angle error and direction deviation of each camera.

[0079] S202: Based on the view angle deviation analysis result, analyzing the adjustment target value of each camera angle and focal length, and adjusting the camera, adjusting the camera angle and focal length, and obtaining a camera adjustment log;

[0080] Based on the results of the perspective deviation analysis, the angle and focal length of each camera are analyzed to determine the target adjustment value. By extracting the angle deviation and focal length error of the camera that needs to be adjusted, the target adjustment value of the angle and focal length of each camera is set. By collaborating with the focus adjustment system interface of the equipment manufacturer, adjustment instructions are sent to each camera to accurately adjust the angle and focal length. During the adjustment process, the status feedback of each camera is monitored in real time to ensure that the adjustment action is accurately executed. After the adjustment is completed, the final angle and focal length settings of each camera are recorded, and a camera adjustment log is generated. The log records the adjustment process and final status of each camera in detail, providing a basis for subsequent verification.

[0081] S203: Based on the camera adjustment log, verify the effect of the adjusted camera settings, capture video data, analyze the perspective difference and the performance of the object in the adjusted picture, evaluate whether the perspective error is corrected, and obtain the camera angle adjustment parameter;

[0082] Based on the camera adjustment log, the effect of the adjusted camera settings is verified, new video data is captured from the adjusted camera, and image analysis technology is used to compare the difference in viewing angles and the performance of moving objects in the video images before and after the adjustment. Through comparative analysis, it is evaluated whether the viewing angle error of each camera has been effectively corrected, and the positioning accuracy and performance continuity of the moving objects in the adjusted images are checked to obtain the camera angle adjustment parameters.

[0083] See also Figure 4 , based on the camera angle adjustment parameters, according to the ambient light intensity of each camera, adjust the ISO and exposure parameters of each camera to optimize the image data capture quality. The specific steps for optimizing the shooting parameters are:

[0084] S301: Based on the camera angle adjustment parameters, the ambient light intensity at each camera position is measured by a light sensor, and the light intensity value at each camera position is recorded to obtain ambient light data records;

[0085] Adjust parameters based on camera angles and use light sensors to determine the ambient light intensity at each camera location. Light sensors installed near each camera regularly measure the ambient light intensity and record the data. The data includes light intensity values ​​at different time points to ensure that the effects of changes in sunlight or artificial light sources can be captured. These light intensity values ​​are associated with camera positions and timestamps to generate ambient light data records. The records provide the necessary input for adjusting the camera's shooting settings to ensure that the camera can achieve the best image quality under the lighting conditions of its environment.

[0086] S302: Based on the ambient light data record, adjust the ISO setting and exposure time of each camera to match the ambient light intensity, optimize the quality and consistency of image capture under differentiated lighting conditions, and obtain adjusted shooting parameters;

[0087] Based on the ambient light data record, adjust the ISO setting and exposure time of each camera to match the light intensity of the current environment. By analyzing the ambient light data record, identify the average light intensity and its fluctuation range at the camera location, and calculate the recommended ISO value and exposure time based on the data to optimize the quality and consistency of image capture. The adjustment is completed automatically through the software to ensure that the settings of each camera can respond quickly to changes in ambient light. After the adjustment is completed, record the adjusted shooting parameters of each camera to obtain the adjusted shooting parameters.

[0088] S303: Based on the adjusted shooting parameters, the image quality of each camera is evaluated by testing the image capture effect, and according to the evaluation result, ISO and exposure settings are adjusted to optimize the image quality and obtain optimized shooting parameters;

[0089] Based on the adjusted shooting parameters, the image quality of each camera is evaluated by testing the image capture effect. Test images are captured from each adjusted camera, and the image clarity, exposure level, and color accuracy are analyzed using image processing software. Based on the image quality indicators, the performance of each camera is evaluated, and the ISO and exposure time settings that need further adjustment are identified. Based on the evaluation results, the camera shooting parameters are optimized again, and the ISO and exposure time are adjusted to achieve the best image capture effect, generating optimized shooting parameters.

[0090] See also Figure 5,Based on optimizing shooting parameters, uniformly configuring the trigger time of each camera,controlling the cameras to capture the scene at the same time,synchronously triggering each camera through the network,starting image shooting,avoiding the time deviation during shooting,optimizing the time consistency of the scene, and obtaining the steps of synchronous triggering data set are as follows:

[0091] S401: Based on the optimized shooting parameters, a unified trigger time of each camera is set, and a network communication protocol is configured to adjust the camera to receive a trigger signal within a predetermined time to obtain a unified trigger configuration;

[0092] Based on the optimized shooting parameters, a unified trigger time is set for each camera, and the corresponding network communication protocol is configured to ensure that all cameras can correctly receive the trigger signal within the predetermined time. The unified trigger time is set through the central control software, which usually matches the specific event or monitoring requirements. The network communication protocol is configured for each camera, including the setting of the IP address and port number, and ensuring that each camera can be accurately identified within the local area network. In addition, the configuration includes setting the quality service parameters of the network to prioritize the transmission of the trigger signal and reduce the risk of network delay and packet loss. After completing the configuration, a unified trigger configuration is generated to record the trigger settings and network configuration details of all cameras.

[0093] S402: Based on the unified trigger configuration, when data collection is required, a synchronous trigger signal is sent to each camera, the cameras are controlled to start shooting simultaneously according to the unified trigger configuration, and the actual trigger time of each camera is recorded to obtain a trigger time record;

[0094] Based on the unified trigger configuration, when data collection is required, a synchronous trigger signal is sent to each camera through the central control unit. The signal ensures that all cameras can start shooting at the same time according to the preset trigger time. The trigger signal is sent on time through the configured network protocol. Each camera starts shooting immediately after receiving the signal to ensure the synchronization and consistency of the data. At the same time, the system records the actual trigger time of each camera, and the time data is then collected and stored to form a trigger time record.

[0095] S403: Based on the trigger time record, check the time synchronization accuracy, analyze the cause of the time deviation, adjust the network delay setting, reconfigure the trigger mechanism of the camera, avoid the startup deviation, and obtain a synchronous trigger data set;

[0096] Based on the trigger time record, check the time synchronization accuracy and analyze the reasons for time deviation. Evaluate the accuracy of time synchronization by comparing the difference between the actual trigger time and the scheduled trigger time. If a significant time deviation is found, analyze the data to determine whether there is network delay or configuration error. Based on the analysis results, adjust the network delay settings, such as adjusting QOS parameters or improving network infrastructure, to reduce future time deviations. After the adjustment is completed, reconfigure the camera's trigger mechanism to ensure that all cameras can start more accurately and synchronously, generate a synchronous trigger data set, record the camera's start time and synchronization accuracy after each adjustment, and provide data support for continuous optimization.

[0097] See also Figure 6 ,Based on the synchronous trigger data set, extract the timestamp and frame rate data of the current video stream of each camera, compare and analyze the timestamp differences and frame rate inconsistencies between each camera, and correct the synchronization error by adjusting the timestamp of the data packet. The specific steps to generate the synchronization error correction result are:

[0098] S501: extracting video stream data output by each camera based on a synchronous trigger data set, recording a timestamp and a number of frames per second of each video stream, and obtaining a time frame rate data table;

[0099] Based on the synchronous trigger data set, extract the video stream data output by each camera and record the key information of each video stream. Extract data from the stored or real-time transmitted video stream, including the video file or stream of each camera. For each video stream, use the video analysis tool to read and record the timestamp and number of frames per second of the video. The timestamp ensures the consistency of the video data with the actual shooting time, while the frame rate reflects the quality and smoothness of the video. The data is organized into a time frame rate data table, listing the timestamp and frame rate of the video stream of each camera for further analysis.

[0100] S502: Based on the time frame rate data table, compare the timestamp and frame rate of each camera, calculate the time offset and frame rate change, analyze the cameras with synchronization errors, and obtain the time frame rate difference analysis results;

[0101] Based on the time frame rate data table, compare and analyze the timestamps and frame rates of the video streams of each camera. Calculate the offset between the timestamps of each camera's video stream and the change in frame rate. By calculating the difference in timestamps of different video streams and the statistical average and standard deviation of the frame rate, identify the cameras with synchronization errors, that is, those devices with large timestamp offsets or unstable frame rates, obtain the results of the time frame rate difference analysis, and list the time and frame rate data of each camera, as well as the differences between cameras.

[0102] S503: Based on the time frame rate difference analysis result, adjust the timestamp of the camera video stream with time deviation, synchronize the data stream, verify the temporal consistency of each camera output video, and obtain the synchronization error correction result;

[0103] Based on the results of the time frame rate difference analysis, the cameras with time deviations are adjusted, the video stream timestamps of each camera with deviations are adjusted, and the time synchronization technology is used to ensure the consistency of the timestamps of all camera video streams. This includes adjusting the system clock or modifying the metadata of the video data. After the adjustment, the temporal consistency of the video stream output by each camera is re-verified, and the synchronization of all cameras is ensured by comparing the timestamps and frame rates again, generating the synchronization error correction results.

[0104] See also Figure 7 ,Based on the synchronization error correction results, the camera video stream data transmission process is dynamically adjusted. According to the network delay and bandwidth changes, the sending time and receiving buffer parameters of the data packet are adjusted to optimize the synchronization accuracy and efficiency of the video stream data during network transmission. The specific steps to obtain the optimized synchronization acquisition results are as follows:

[0105] S601: Based on the synchronization error correction result, monitor the delay and bandwidth status of the current network in real time, record the network performance indicators at different time points, and obtain real-time network monitoring information;

[0106] Based on the synchronization error correction results, the current network delay and bandwidth status are monitored in real time to ensure the continuous synchronization of the video data stream. By deploying network performance monitoring tools, key performance indicators such as network delay, bandwidth utilization, and data packet loss rate are collected and analyzed in real time. The monitoring tool is configured to automatically record the network status at different time points to capture any network fluctuations that may affect the synchronization of video data. The collected data is organized into real-time network monitoring information.

[0107] S602: Based on the real-time network monitoring information, the sending time of each camera data stream and the buffer parameters of the receiving end are adjusted to match the network fluctuation, optimize the synchronization of the data packets between the camera and the server, and obtain the adjusted data stream configuration information;

[0108] The calculation formulas for adjusting the sending time of each camera data stream and the buffer parameters of the receiving end are:

[0109]

[0110] and

[0111]

[0112] Among them, T adj is the adjusted sending time, T baserepresents the benchmark sending time, Δt represents the average network delay time, k 1 is the adjustment coefficient, BW curr Represents the current bandwidth, BW base represents the base bandwidth, k 2 is the weight parameter, k 3 is the buffer coefficient, B size is the adjusted buffer size, k 4 is the conversion factor.

[0113] formula:

[0114]

[0115] and

[0116]

[0117] Parameter meaning and acquisition method:

[0118] T base : Baseline sending time, usually set to the default sending time interval when the system is initialized. It is a fixed value. For example, each camera sends 30 frames per second, then T base It is 33.33 milliseconds.

[0119] Δt: average network delay, which is obtained by measuring the round-trip time of network requests in real time through network monitoring tools. For example, in a stable network environment, the average network delay is 50 milliseconds.

[0120] k 1 : Adjustment coefficient, used to adjust the impact of delay time on sending time. It is an empirical value, set according to the stability of the network environment, such as k 1 =0.5, indicating that the effect of delay time on sending time is halved.

[0121] BW curr and BW base :Current bandwidth and baseline bandwidth are obtained through real-time measurement by network monitoring tools and preset system baseline bandwidth values. For example, if the baseline bandwidth is 100Mbps and the current bandwidth is 85Mbps, the network status has slightly decreased.

[0122] k 2 : Weight parameter, used to adjust the impact of bandwidth changes on the sending time. 1 Similarly, it is an empirical value obtained based on system performance testing, such as k 2 =0.3, which means that the impact of bandwidth change is more significant.

[0123] k 3: Buffer coefficient, which determines the proportion of buffer size relative to bandwidth and time. It is a value derived from experience in system performance optimization. For example, it is set to k 3 =1.2.

[0124] k 4 : Conversion factor, which reduces the impact of buffering and is used for numerical conversion. For example, it is set to 1000 to adjust the unit from Mbps to MB.

[0125] Calculation example:

[0126] Set the following parameter values:

[0127] T base =33.33 ms, Δt=50 ms, k 1 =0.5, BW curr =85Mbps, BW base

[0128] =100Mbps, k 2 =0.3, k 3 =1.2, k 4 =1000.

[0129] Calculate according to the formula:

[0130] Calculate the bandwidth change ratio:

[0131]

[0132] Apply adjustment factors and weights:

[0133] 0.3×0.387=0.1161

[0134] Calculate the send time adjustment:

[0135]

[0136] Calculation result T adj =52.26 ms, which indicates the adjusted sending time, meaning that, due to network delay and bandwidth reduction, the camera’s sending time interval is increased from the original 33.33 ms to 52.26 ms to adapt to the current network conditions and reduce packet loss and video streaming delay.

[0137] Calculate buffer parameters:

[0138]

[0139] =5.326MB

[0140] Calculation result B size=5.326MB, indicating the adjusted buffer size. This means that in order to adapt to the changes in sending time and bandwidth under current network conditions, the buffer should be configured to about 5.326MB to optimize data reception and caching, and reduce data flow interruption or packet loss caused by network delays or fluctuations.

[0141] S603: Based on the adjusted data stream configuration information, detect the synchronization accuracy of the video stream output by each camera, verify the transmission effect of the video data in the network, and obtain the optimized synchronization acquisition result;

[0142] Based on the adjusted data stream configuration information, detect the synchronization accuracy of the video stream output by each camera, and use the synchronization detection tool to test the video stream of each camera, paying special attention to the timestamp and frame rate synchronization accuracy of the video stream. During the test, evaluate the transmission effect of video data in the network, including delay consistency and data integrity. Through the test, verify whether the adjusted configuration effectively improves the synchronization accuracy of the video stream and generates optimized synchronization acquisition results.

[0143] See also Figure 8 A multi-camera synchronous data acquisition system is provided, and the multi-camera synchronous data acquisition system is used to execute the multi-camera synchronous data acquisition method. The system comprises:

[0144] The moving object recognition module is based on the real-time video stream of the camera. By analyzing the video frames, it identifies the moving objects in the differentiated video stream, and synchronously records the appearance time and position changes of the moving objects in the differentiated camera to obtain the view angle change data;

[0145] The shooting parameter adjustment module analyzes the angle deviation of each camera capturing the same scene based on the perspective change data, adjusts the angle and focal length of each camera, and adjusts the ISO and exposure parameters of each camera according to the ambient light intensity of each camera to obtain optimized shooting parameters;

[0146] The shooting trigger control module uniformly configures the trigger time of each camera based on the optimized shooting parameters, controls the cameras to capture the scene at the same time, synchronously triggers each camera through the network, starts image shooting, and obtains a synchronous trigger data set;

[0147] The synchronization error correction module compares and analyzes the timestamp differences and frame rate inconsistencies between each camera based on the synchronization trigger data set, and corrects the synchronization error by adjusting the timestamp of the data packet to generate the synchronization error correction result;

[0148] The network fluctuation compensation module dynamically adjusts the camera video stream data transmission process based on the synchronization error correction results, and adjusts the data packet sending time and receiving buffer parameters according to network delay and bandwidth changes to obtain optimized synchronization acquisition results.

[0149] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for synchronous data acquisition of multiple cameras, characterized in that: The following steps are involved: Based on the real-time video stream of the camera, by analyzing the video frames, the moving objects in the differentiated video stream are identified, and the appearance time and position changes of the moving objects in the differentiated camera are synchronously recorded to obtain the perspective change data; Based on the perspective change data, by comparing the positions of the same moving object in the differentiated camera images, identifying the angle deviation of each camera capturing the same scene, adjusting the angle and focal length of each camera, and obtaining the camera angle adjustment parameters; Based on the camera angle adjustment parameters, the ISO and exposure parameters of each camera are adjusted according to the ambient light intensity of each camera to obtain optimized shooting parameters; Based on the optimized shooting parameters, the trigger time of each camera is uniformly configured, each camera is synchronously triggered through the network, image shooting is started, and a synchronous triggering data set is obtained; Based on the synchronization trigger data set, compare and analyze the timestamp difference and frame rate inconsistency between each camera, and correct the synchronization error by adjusting the timestamp of the data packet to generate a synchronization error correction result; Based on the synchronization error correction result, the camera video stream data transmission process is dynamically adjusted, and the sending time and receiving buffer parameters of the data packet are adjusted according to the network delay and bandwidth changes to obtain an optimized synchronization acquisition result.

2. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: The perspective change data includes the position coordinates, timestamp and relative speed of the moving object captured by the camera, the camera angle adjustment parameters include the focal length adjustment value and perspective alignment index of the camera, the optimized shooting parameters include the adjusted ISO value, exposure compensation value and dynamic range information, the synchronization trigger data set includes the time setting of the synchronization trigger, the shooting parameter configuration of the camera and the start timestamp, the synchronization error correction result includes the accuracy value of the timestamp alignment, the frame rate consistency adjustment result and the synchronization accuracy index between cameras, and the optimized synchronization acquisition result includes the data transmission delay optimization value, the receiving buffer adjustment parameter and the network bandwidth utilization.

3. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the real-time video stream of the camera, by analyzing the video frames, identifying the moving objects in the differentiated video stream, and synchronously recording the appearance time and position changes of the moving objects in the differentiated camera, the specific steps to obtain the perspective change data are as follows: Based on the real-time video stream of the camera, each frame of the video stream is time-stamped, and the position coordinates and the time point of appearance of each moving object are recorded to obtain the basic position and time data; Based on the basic position time data, compare the time stamps and position coordinates of the same moving object in multiple camera viewing angles, identify the appearance sequence of the moving object in each viewing angle, and obtain a moving object recognition record; Based on the mobile object recognition record, the position and time changes of the mobile object in the differentiated camera viewing angle are analyzed, and the changed position and the corresponding time are synchronously recorded to obtain the viewing angle change data.

4. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the perspective change data, by comparing the positions of the same moving object in the differentiated camera images, identifying the angle deviation of each camera capturing the same scene, adjusting the angle and focal length of each camera, and obtaining the camera angle adjustment parameters are specifically as follows: Based on the perspective change data, the spatial coordinate position of the moving object in the picture captured by the differential camera is analyzed, the angle deviation and the capture direction value corresponding to each camera are identified, and the perspective deviation analysis result is obtained; Based on the perspective deviation analysis result, the adjustment target value of each camera angle and focal length is analyzed, and the camera is adjusted to adjust the angle and focal length of the camera to obtain a camera adjustment log; Based on the camera adjustment log, the effect of the adjusted camera settings is verified, and by capturing video data, analyzing the perspective difference and the performance of the object in the adjusted picture, evaluating whether the perspective error is corrected, and obtaining the camera angle adjustment parameters.

5. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the camera angle adjustment parameters, the ISO and exposure parameters of each camera are adjusted according to the ambient light intensity of each camera, and the steps of obtaining the optimized shooting parameters are specifically as follows: Based on the camera angle adjustment parameter, the ambient light intensity at each camera position is measured by a light sensor, and the light intensity value at each camera position is recorded to obtain an ambient light data record; Based on the ambient light data record, adjusting the ISO setting and exposure time of each camera to match the ambient light intensity, optimizing the quality and consistency of image capture under differentiated lighting conditions, and obtaining adjusted shooting parameters; Based on the adjusted shooting parameters, the image quality of each camera is evaluated by testing the image capture effect, and according to the evaluation results, ISO and exposure settings are adjusted to optimize the image quality and obtain optimized shooting parameters.

6. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the optimized shooting parameters, the trigger time of each camera is uniformly configured, each camera is synchronously triggered through the network, and image shooting is started. The steps of obtaining the synchronous triggering data set are specifically as follows: Based on the optimized shooting parameters, a unified trigger time is set for each camera, and a network communication protocol is configured to adjust the camera to receive a trigger signal within a predetermined time to obtain a unified trigger configuration; Based on the unified trigger configuration, when data collection is required, a synchronous trigger signal is sent to each camera, the cameras are controlled to start shooting at the same time according to the unified trigger configuration, and the actual trigger time of each camera is recorded to obtain a trigger time record; Based on the trigger time record, the time synchronization accuracy is checked, the cause of the time deviation is analyzed, and the network delay setting is adjusted to reconfigure the trigger mechanism of the camera to avoid the startup deviation and obtain a synchronous trigger data set.

7. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the synchronization trigger data set, the timestamp difference and frame rate inconsistency between each camera are compared and analyzed, and the synchronization error is corrected by adjusting the timestamp of the data packet. The steps of generating the synchronization error correction result are specifically as follows: Based on the synchronous trigger data set, extract the video stream data output by each camera, record the timestamp and the number of frames per second of each video stream, and obtain a time frame rate data table; Based on the time frame rate data table, the timestamp and frame rate of each camera are compared, the time offset and frame rate change are calculated, and the cameras with synchronization errors are analyzed to obtain the time frame rate difference analysis results; Based on the time frame rate difference analysis result, the timestamp of the camera video stream with time deviation is adjusted, the data stream is synchronized, the temporal consistency of each camera output video is verified, and the synchronization error correction result is obtained.

8. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: Based on the synchronization error correction result, the camera video stream data transmission process is dynamically adjusted, and the sending time and receiving buffer parameters of the data packet are adjusted according to the network delay and bandwidth changes to obtain the optimized synchronization acquisition result. Specifically, the steps are as follows: Based on the synchronization error correction result, the delay and bandwidth status of the current network are monitored in real time, the network performance indicators at different time points are recorded, and real-time network monitoring information is obtained; Based on the real-time network monitoring information, the sending time of each camera data stream and the buffer parameters of the receiving end are adjusted to match the network fluctuations, optimize the synchronization of data packets between the camera and the server, and obtain the adjusted data stream configuration information; Based on the adjusted data stream configuration information, the synchronization accuracy of the video stream output by each camera is detected, the transmission effect of the video data in the network is verified, and the optimized synchronization acquisition result is obtained.

9. The method for synchronous data acquisition of multiple cameras according to claim 1, characterized in that: The calculation formulas for adjusting the sending time of each camera data stream and the buffer parameters of the receiving end are: and Among them, T adj is the adjusted sending time, T base represents the benchmark sending time, Δt represents the average network delay time, k1 is the adjustment coefficient, BW curr Represents the current bandwidth, BW base represents the base bandwidth, k2 is the weight parameter, k3 is the buffer coefficient, B size is the adjusted buffer size, and k4 is the conversion factor.

10. A multi-camera synchronous data acquisition system, characterized in that: According to any one of claims 1 to 9, the method for synchronous data acquisition of multiple cameras comprises: The moving object recognition module is based on the real-time video stream of the camera. By analyzing the video frames, it identifies the moving objects in the differentiated video stream, and synchronously records the appearance time and position changes of the moving objects in the differentiated camera to obtain the view angle change data; The shooting parameter adjustment module analyzes the angle deviation of each camera capturing the same scene based on the perspective change data, adjusts the angle and focal length of each camera, and adjusts the ISO and exposure parameters of each camera according to the ambient light intensity of each camera to obtain optimized shooting parameters; The shooting trigger control module uniformly configures the trigger time of each camera based on the optimized shooting parameters, controls the cameras to capture the scene at the same time, synchronously triggers each camera through the network, starts image shooting, and obtains a synchronous trigger data set; The synchronization error correction module compares and analyzes the timestamp difference and frame rate inconsistency between each camera based on the synchronization trigger data set, corrects the synchronization error by adjusting the timestamp of the data packet, and generates a synchronization error correction result; The network fluctuation compensation module dynamically adjusts the camera video stream data transmission process based on the synchronization error correction result, and adjusts the data packet sending time and receiving buffer parameters according to network delay and bandwidth changes to obtain optimized synchronization acquisition results.

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