Intelligent camera linkage correction method and system, electronic device and storage medium

Abstract

The invention relates to an intelligent camera linkage correction method and system, an electronic device and a storage medium. The method comprises the following steps: acquiring a trigger event in a preset monitoring area; extracting trigger characteristics in the trigger event to determine the occurrence of a specific event; determining an acquisition source of the trigger event according to the trigger feature; when it is determined that the acquisition source is the gun camera, determining the target position of the dome camera by using a preset coordinate transformation matrix, sending a control instruction to the dome camera, and controlling the dome camera to adjust the shooting angle according to the target position information, so that the specific event is kept in the central area of the monitoring image; when it is determined that the acquisition source is the dome camera, the target position of the dome camera is determined, a control instruction is sent to the dome camera, the dome camera is controlled to adjust the shooting angle, and the specific event is kept in the center area of the monitoring image; the problem that automation and intelligence are lacked when multi-camera linkage is achieved in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of door lock technology, and in particular to a smart camera linkage correction method, system, electronic device and storage medium. Background Art

[0002] With the growing demand for security monitoring, the traditional single-camera monitoring system can no longer meet the needs of large-scale, high-precision monitoring. Currently, cameras on the market generally use wide-angle lenses to pursue a wider field of view, but wide-angle lenses have problems with insufficient clarity and low resolution, especially when shooting distant objects. Therefore, multi-camera zoom camera systems came into being, but in the existing technology, the linkage tracking function between multiple cameras is still not perfect.

[0003] The existing multi-camera monitoring system often cannot achieve high-precision linkage correction, resulting in the inability to achieve the goal of "seeing far and seeing clearly" during the monitoring process. In addition, the existing technology often requires complex manual operations when realizing multi-camera linkage, lacking automation and intelligence. Summary of the invention

[0004] The embodiments of the present application provide a smart camera linkage correction method, system, electronic device and storage medium to at least solve the problem that the prior art often requires complex manual operations and lacks automation and intelligence when realizing multi-camera linkage.

[0005] In a first aspect, an embodiment of the present application provides a method for intelligent camera linkage correction, comprising: obtaining a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; extracting the trigger feature from the trigger event, and determining the occurrence of a specific event based on the trigger feature using a database, wherein the database at least includes the associated corresponding data between the trigger feature and the specific event; determining the acquisition source of the trigger event based on the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera; when it is determined that the acquisition source is a gun camera, determining the target position of the ball camera using a preset coordinate transformation matrix, And send a control instruction to the ball camera, according to the target position information, control the ball camera to adjust the shooting angle, so that the specific event remains in the center area of ​​the monitoring screen; otherwise, in the case where the acquisition source is determined to be the ball camera, determine the target position of the ball camera, and send a control instruction to the ball camera, the control instruction at least includes the target position information, according to the target position information, control the ball camera to adjust the shooting angle, so that the specific event remains in the center area of ​​the monitoring screen; wherein, the control instruction at least includes the target position information, the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one ball camera. .

[0006] In some embodiments, the preset coordinate conversion matrix includes: presetting the origin coordinates of the ball camera to be located in the middle position of the at least two gun cameras; dividing the monitoring area of ​​the at least two gun cameras into preset sub-areas, and recording the center coordinates of each sub-area; collecting the image coordinates of the sub-areas and inputting them into a preset correction algorithm, calculating the associated angles between the at least two gun cameras and the ball camera respectively, and forming the preset coordinate conversion matrix.

[0007] In some of the embodiments, the image coordinates of the sub-area are collected and input into a preset correction algorithm to calculate the associated angles of the at least two gun cameras and the dome camera, including: collecting the image coordinates of the sub-area and inputting them into a preset correction algorithm to calculate the offset from the origin coordinates of the dome camera to the center coordinates of the sub-area; using a distortion correction method to calculate the focal length in units of pixel x and y dimensions, and the image plane coordinates; selecting at least three non-coplanar calibration points through a calibration method, and calculating the mapping parameter matrix using the least squares method; outputting the coordinate matrix relationship according to the sub-area center coordinates and the offset to form the preset coordinate transformation matrix.

[0008] In some of the embodiments, an adaptive algorithm is used to automatically adjust the calibration parameters in the linkage association matrix according to the real-time monitoring screen.

[0009] In some of the embodiments, the origin coordinates of the dome camera are preset to be located in the middle of the at least two gun cameras, and also include: when switching from an off state to a switch state, controlling the dome camera to move and patrol according to a preset path, the origin coordinates of the dome camera are preset to be located in the middle of the at least two gun cameras, and there are pixel overlaps in the monitoring areas of the dome camera and the gun camera.

[0010] In some of the embodiments, the tracking mode of the ball camera is automatically selected according to the preset coordinate transformation matrix and the preset linkage rules, wherein the tracking mode includes at least one of a locked tracking mode, an intelligent area tracking mode, a multi-target tracking mode, an event-triggered tracking mode, and a virtual fence tracking mode.

[0011] In a second aspect, an embodiment of the present application provides an intelligent camera linkage correction system, characterized in that it includes:

[0012] A camera module, used to obtain a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; a detection module, coupled with the camera module, used to extract the trigger feature from the trigger event, and determine the occurrence of a specific event based on the trigger feature using a database, wherein the database at least includes the associated corresponding data between the trigger feature and the specific event; a processing module, coupled with the detection module, used to determine the acquisition source of the trigger event based on the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera; a tracking module, coupled with the processing module, used to use a preset coordinate transformation matrix to obtain the acquisition source of the trigger event based on the trigger feature. Determine the target position of the ball camera, and send a control instruction to the ball camera, and according to the target position information, control the ball camera to adjust the shooting angle so that the specific event remains in the central area of ​​the monitoring screen; otherwise, in the case where it is determined that the acquisition source is the ball camera, determine the target position of the ball camera, and send a control instruction to the ball camera, the control instruction at least includes the target position information, and according to the target position information, control the ball camera to adjust the shooting angle so that the specific event remains in the central area of ​​the monitoring screen; wherein, the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one ball camera.

[0013] In some of the embodiments, it also includes: a tracking mode switching module, coupled with the tracking module, for automatically selecting the tracking mode of the ball camera according to the preset coordinate transformation matrix and the preset linkage rules, wherein the tracking mode includes at least one of the locked tracking mode, the intelligent area tracking mode, the multi-target tracking mode, the event-triggered tracking mode, and the virtual fence tracking mode.

[0014] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps of the intelligent camera linkage correction method as described in the first aspect above.

[0015] In a third aspect, an embodiment of the present application provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the intelligent camera linkage correction method described in the first aspect above are implemented.

[0016] Compared with the related art, the intelligent camera linkage correction method, system, electronic device and storage medium provided in the embodiments of the present application adopt the method of obtaining a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; extracting the trigger feature from the trigger event, and determining the occurrence of a specific event based on the trigger feature using a database, wherein the database at least includes the associated corresponding data between the trigger feature and the specific event; determining the acquisition source of the trigger event based on the trigger feature, wherein the acquisition source is at least one of two gun cameras and one dome camera; when it is determined that the acquisition source is a gun camera, determining the target position of the dome camera using a preset coordinate transformation matrix, and sending a control instruction to the dome camera according to The target position information controls the dome camera to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is the dome camera, the target position of the dome camera is determined, and a control instruction is sent to the dome camera, wherein the control instruction at least includes the target position information, and according to the target position information, the dome camera is controlled to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; wherein the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one dome camera, which solves the problem that the prior art often requires complex manual operations and lacks automation and intelligence when realizing multi-camera linkage.

[0017] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 It is a hardware structure block diagram of a terminal of the intelligent camera linkage correction method according to an embodiment of the present application;

[0020] Figure 2 is a flow chart of a smart camera linkage calibration method according to an embodiment of the present application;

[0021] Figure 3 It is a structural block diagram of the intelligent camera linkage correction system according to the embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated 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 application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0023] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0024] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The "multiple links" involved in this application refer to links greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in this application are only used to distinguish similar objects, and do not represent a specific ordering of objects.

[0025] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. Taking running on a terminal as an example, Figure 1 : is a hardware structure block diagram of a terminal of the intelligent camera linkage correction method of the embodiment of the present application. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0026] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the intelligent camera linkage correction method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by the communication provider of the terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0028] This embodiment provides a smart camera linkage calibration method running on the above terminal, Figure 2 is a flow chart of the intelligent camera linkage correction method according to an embodiment of the present application. Figure 2 As shown, the process includes the following steps:

[0029] Step S201, obtaining a triggering event in a preset monitoring area, wherein the triggering event at least includes a triggering feature.

[0030] In this embodiment, the technical solution of the present invention relates to an intelligent monitoring system, which is designed to detect and respond to specific trigger events in a predefined monitoring area. These trigger events refer to specific activities or situations captured during the monitoring process, and they contain at least one trigger feature that can be recognized and analyzed by the system. Preset monitoring area, the system first defines one or more monitoring areas, which are specific parts of the camera's monitoring field of view and can be set based on geographic location, scene content or other criteria. Trigger event, a trigger event refers to a specific activity or change that occurs in the monitoring area, such as human intrusion, items left behind, abnormal sounds, etc. These events are regarded as abnormal or important situations that require system attention and response. Trigger feature, the trigger feature is the key attribute or parameter of the trigger event, which can be a visual feature (such as shape, color, motion pattern), audio feature (such as sound frequency, intensity, duration) or other sensor data. Trigger features are used to distinguish different types of events and provide a basis for the identification and classification of events. Event detection, the system uses image processing, pattern recognition, machine learning and other technologies to perform real-time analysis on the video stream captured by the camera to identify and extract the features of the trigger event. Feature extraction: Once a potential triggering event is detected, the system extracts the features of the event and analyzes these features through algorithms to determine whether the preset triggering conditions are met. Response mechanism: When the system confirms that a triggering event has been detected, it will execute corresponding response measures according to preset rules and strategies, such as sounding an alarm, notifying security personnel, automatically adjusting the camera focus to track the target, or recording event details for subsequent analysis. The technical effects of this step are: improving monitoring efficiency: by automatically identifying and classifying events in the monitoring area, the reliance on manual monitoring is reduced, and the efficiency of the monitoring process is improved. Enhanced response speed: The system can quickly identify triggering events and respond immediately, which improves the response speed to emergencies. Improved security: The system can promptly identify potential security threats or abnormal behaviors and take corresponding preventive or intervention measures, thereby enhancing the security of the monitoring area. Reduce false alarms: Through precise feature extraction and intelligent analysis, the system can distinguish between real security threats and harmless events, thereby reducing false alarms and unnecessary alarms. Data recording and analysis: The system can record detailed information about triggering events and provide data to support subsequent security analysis and auditing work, which helps to improve monitoring strategies and improve monitoring quality. In summary, this technical solution not only improves the automation and intelligence level of the monitoring system by intelligently identifying and processing trigger events within the monitoring area, but also provides users with a safer and more efficient monitoring environment.

[0031] Step S202: extracting the trigger feature from the trigger event, and determining the occurrence of a specific event using a database according to the trigger feature, wherein the database at least contains the corresponding data of the association between the trigger feature and the specific event.

[0032] In this embodiment, the technical solution of the present invention is a key component for event identification and classification in an intelligent monitoring system. The system detects and responds to specific trigger events by analyzing surveillance videos. The following are the detailed steps of the scheme: Trigger event detection, the system identifies abnormal or specific activities in a preset monitoring area through real-time video analysis, which are defined as trigger events. Trigger feature extraction, once a trigger event is detected, the system will extract key features. These features may include but are not limited to motion patterns, shapes, colors, sizes or other identification marks, which are quantitative descriptions of events. Database query, the extracted trigger features are used for matching queries in the database. The database stores the associated corresponding data between predefined trigger features and known specific event types. Specific event determination, the system determines the specific type of the detected trigger event based on the matching results in the database. For example, if the detected trigger feature matches the feature of "crowd gathering" in the database, the system determines that a "crowd gathering" event has occurred. Event response, once the occurrence of a specific event is determined, the system can execute preset response measures, such as sending an alarm, notifying security personnel, starting recording, or triggering other security protocols. Technical effect: Improve accuracy. By analyzing the trigger features and matching them with known patterns in the database, the system can more accurately identify and classify monitoring events. Rapid response. The system can quickly identify specific events and take immediate response measures, which improves the response speed to emergencies. Enhance security. Accurate event identification and rapid response mechanisms significantly improve the security of the monitoring area. Reduce false alarms. Through precise feature matching and intelligent analysis, the system can distinguish between real security threats and false alarms, thereby reducing unnecessary alarms. Data-driven decision-making. The system can record and analyze event data to provide data support for security policies and resource allocation. Automated monitoring reduces reliance on manual monitoring and makes the monitoring process more automated and intelligent. In summary, this technical solution improves the effectiveness of the monitoring system and the security of the monitoring area through intelligent analysis and database matching. Through automated event detection and response, it ensures that events occurring in the monitoring area can be handled in a timely and accurate manner.

[0033] Step S203, determining the acquisition source of the trigger event according to the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera.

[0034] In this embodiment, the technical solution of the present invention describes a method for identifying the source of a specific event in a monitoring area in an intelligent monitoring system. The system detects trigger events by analyzing the video stream captured by the camera, extracts the features of the event, and then determines the source of the event based on these features. The following are the detailed steps of the scheme: Trigger event detection, the system identifies abnormal or specific activities in a preset monitoring area through real-time video analysis, which are defined as trigger events. Trigger feature extraction, once a trigger event is detected, the system will extract key features. These features may include but are not limited to motion patterns, shapes, colors, sizes or other identification marks, which are quantitative descriptions of events. Event source determination, the system will determine the source of the trigger event based on the extracted trigger features and the associated corresponding data stored in the database. In this process, the system compares the trigger features with the features recorded in the database to determine which of the two gun cameras or the ball camera captured the event. Database query, the database contains the associated corresponding data between the predefined trigger features and specific event types, which is used to help the system determine the source of the event. Technical effect: Improved accuracy, by analyzing the trigger features and matching them with known data in the database, the system can more accurately identify and classify the source of the monitoring event. Rapid positioning: The system is able to quickly determine the source of an event, allowing it to quickly take appropriate response measures, such as notifying security personnel or automatically adjusting cameras to monitor the situation more closely. Enhanced responsiveness: Accurate event source identification helps improve the monitoring system's ability to respond to emergencies, making the response more timely and effective. Reduce false alarms: Through precise feature matching and intelligent analysis, the system is able to distinguish between real security threats and false alarms, thereby reducing unnecessary alarms. Optimize resource allocation: Determining the source of an event can help the system optimize resource allocation, for example, focusing more processing power or monitoring attention on the area where the event occurred. In summary, this technical solution improves the effectiveness of the monitoring system through intelligent analysis and database matching, ensuring that events occurring in the monitored area can be handled in a timely and accurate manner.

[0035] Step S204, when it is determined that the acquisition source is a gun camera, the target position of the ball camera is determined using a preset coordinate transformation matrix, and a control instruction is sent to the ball camera. According to the target position information, the ball camera is controlled to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is a ball camera, the target position of the ball camera is determined, and a control instruction is sent to the ball camera, the control instruction at least includes the target position information, and according to the target position information, the ball camera is controlled to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; wherein the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one ball camera.

[0036] In this embodiment, the technical solution of the present invention describes a linkage correction and target tracking process in an intelligent camera system. The system includes multiple fixed-position gun cameras and a movable dome camera. The following are the detailed steps: Get source determination. When a trigger event is detected, the system first determines whether the event is captured by a gun camera or a dome camera. Coordinate conversion (gun camera). If the trigger event is captured by the gun camera, the system will use a preset coordinate conversion matrix to convert the trigger feature position in the gun camera coordinate system to the position in the dome camera coordinate system. Target position determination (gun camera). Using the converted coordinates, determine the target position to which the dome camera needs to turn so as to place a specific event in the center area of ​​its monitoring screen. Send control instructions (gun camera). The system sends control instructions to the dome camera, including target position information, to guide the dome camera to adjust its shooting angle. Coordinate conversion (dome camera). If the trigger event is captured by the dome camera, the system will directly use the built-in coordinate system of the camera to determine the target position. Target position determination (dome camera). The system determines the current position that the dome camera needs to maintain so as to keep a specific event in the center area of ​​its monitoring screen. Send control command (ball camera), the system sends control command to the ball camera, including target location information, to adjust its shooting angle. Adjustment of monitoring screen, no matter what the situation is, the ball camera will adjust the shooting angle according to the control command to ensure that the specific event is located in the center area of ​​the monitoring screen. Linkage monitoring area, the monitoring screen contains at least the preset monitoring area, and is covered by the monitoring area of ​​at least two gun cameras and one ball camera. Technical effect: Accurate target tracking, the system can accurately identify and track specific events in the monitoring area. Quick response, the time from detecting an event to adjusting the camera in place is shortened, which improves the response speed of the system. Optimize resource allocation, by automatically adjusting the camera, the system can allocate monitoring resources more effectively and focus on important monitoring events. Enhance monitoring coverage, the linkage of the gun camera and the ball camera ensures full coverage of the monitoring area and reduces monitoring blind spots. Improve monitoring quality, by keeping the event in the center of the monitoring screen, the quality of the monitoring screen is improved, making the event easier for security personnel to observe and analyze. Automated monitoring process, reducing the need for manual intervention, making the monitoring process more automated and intelligent. In summary, this technical solution improves the efficiency and effectiveness of the monitoring system through an intelligent linkage mechanism and automated target tracking, ensuring that events occurring in the monitoring area can be handled promptly and accurately.

[0037] Through the above steps S201 to S204, the intelligent camera linkage correction method, system, electronic device and storage medium adopt the method of obtaining a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; extracting the trigger feature from the trigger event, and determining the occurrence of a specific event based on the trigger feature using a database, wherein the database at least includes the associated corresponding data between the trigger feature and the specific event; determining the acquisition source of the trigger event based on the trigger feature, wherein the acquisition source is at least one of two gun cameras and one dome camera; when it is determined that the acquisition source is a gun camera, determining the target position of the dome camera using a preset coordinate transformation matrix, and sending a control instruction to the dome camera, based on the trigger feature. According to the target position information, the ball camera is controlled to adjust the shooting angle so that the specific event remains in the central area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is the ball camera, the target position of the ball camera is determined, and a control instruction is sent to the ball camera, the control instruction at least includes the target position information, and according to the target position information, the ball camera is controlled to adjust the shooting angle so that the specific event remains in the central area of ​​the monitoring screen; wherein, the control instruction at least includes the target position information, the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring area of ​​at least two of the gun cameras and one ball camera, which solves the problem that the prior art often requires complex manual operations and lacks automation and intelligence when realizing multi-camera linkage. This technical solution describes an intelligent camera linkage correction method, which uses multiple cameras to obtain trigger events in a preset monitoring area. The trigger event includes at least one trigger feature, which is extracted and used to match the occurrence of a specific event in a database. The database contains the associated corresponding data of the trigger feature and the specific event. In addition, the system also needs to determine the acquisition source of the trigger event, that is, which of the two gun cameras or the ball camera captured the event. Technical Effect: Improved accuracy: The system can more accurately identify and classify monitoring events by extracting trigger features and matching them with known data in the database. Rapid response: Once the occurrence of a specific event is determined, the system can quickly take appropriate response measures, such as sounding an alarm or notifying security personnel. Enhanced security: Accurate event identification and rapid response mechanisms significantly improve the security of the monitored area. Reduced false alarms: Through precise feature matching, the system is able to distinguish between real security threats and false alarms, thereby reducing unnecessary alarms. Optimized resource allocation: The system can optimize resource allocation based on the source of the event, for example, focusing more processing power or monitoring attention on the area where the event occurred. Automated monitoring processes: Reduced reliance on manual monitoring, making the monitoring process more automated and intelligent.In summary, this technical solution improves the effectiveness of the monitoring system through intelligent analysis and database matching, ensuring that events occurring in the monitoring area can be handled promptly and accurately.

[0038] In some embodiments, the preset coordinate conversion matrix includes: presetting the origin coordinates of the ball camera to be located in the middle position of the at least two gun cameras; dividing the monitoring area of ​​the at least two gun cameras into preset sub-areas, and recording the center coordinates of each sub-area; collecting the image coordinates of the sub-areas and inputting them into a preset correction algorithm, calculating the associated angles between the at least two gun cameras and the ball camera respectively, and forming the preset coordinate conversion matrix.

[0039] In this embodiment, the technical solution of the present invention performs intelligent coordinate conversion through a preset coordinate conversion matrix, specifically including the following steps: setting the origin coordinates of the ball camera, the system presets the origin coordinates of the ball camera, and positions it in the middle of at least two gun cameras. This setting helps to achieve coordinate unification and correction between the ball camera and the gun camera. Monitoring area division, dividing the monitoring area of ​​at least two gun cameras into multiple sub-areas, and recording the center coordinates of each sub-area. This division helps to more finely manage and adjust specific parts in the monitoring area. Image coordinate acquisition and processing, acquiring the image coordinates of each sub-area, and inputting these coordinates into a preset correction algorithm. This step is the basis for realizing coordinate conversion. By acquiring and processing the image coordinates, the system can more accurately understand and respond to activities in the monitoring area. Calculating the association angle, using the correction algorithm to calculate the association angle between at least two gun cameras and the ball camera. This is a key step in realizing coordinate conversion. By calculating these angles, the system can accurately convert the events captured by the gun camera into the coordinate system of the ball camera. Forming a coordinate conversion matrix, forming a preset coordinate conversion matrix based on the above calculation results. This matrix is ​​the core of the coordinate conversion between the gun camera and the ball camera, which enables the system to accurately convert the event position captured by one camera into the tracking target of another camera. Technical effect: Accurate coordinate conversion, through the preset coordinate conversion matrix, the system can accurately convert the event position in the coordinate system of one camera to the coordinate system of another camera, improving the accuracy of event tracking and response. Enhanced linkage effect, the effective linkage between the gun camera and the ball camera has been strengthened, enabling the system to respond to specific events in the monitoring area more quickly and accurately. Optimized monitoring coverage, through the division of monitoring areas and the recording of the center coordinates of sub-areas, the system can more effectively manage and optimize the monitoring coverage area to ensure that important areas are fully monitored. Improved system reliability, the preset coordinate conversion matrix improves the reliability of the system in complex monitoring environments, especially in scenarios that require multiple cameras to collaborate. Automated monitoring process, through automated coordinate conversion and event processing, reduces the need for manual intervention, making the monitoring process more efficient and intelligent. In summary, this technical solution improves the performance and efficiency of the intelligent camera system in a multi-camera monitoring environment through the precise setting and application of the coordinate conversion matrix. .

[0040] In some of the embodiments, the image coordinates of the sub-area are collected and input into a preset correction algorithm to calculate the associated angles of the at least two gun cameras and the dome camera, including: collecting the image coordinates of the sub-area and inputting them into a preset correction algorithm to calculate the offset from the origin coordinates of the dome camera to the center coordinates of the sub-area; using a distortion correction method to calculate the focal length in units of pixel x and y dimensions, and the image plane coordinates; selecting at least three non-coplanar calibration points through a calibration method, and calculating the mapping parameter matrix using the least squares method; outputting the coordinate matrix relationship according to the sub-area center coordinates and the offset to form the preset coordinate transformation matrix.

[0041] In this embodiment, the technical solution of the present invention relates to the preset and application of the coordinate conversion matrix in the intelligent camera system. The system first collects the image coordinates of the sub-area monitored by at least two gun cameras and inputs them into the preset correction algorithm. The algorithm calculates the associated angle between the gun camera and the ball camera, and includes the following key steps: calculating the offset, calculating the offset from the origin coordinates of the ball camera to the center coordinates of the sub-area monitored by the gun camera. Distortion correction, using the distortion correction method, calculate the focal length in pixels and the image plane coordinates. Calibration method, by selecting at least three non-coplanar calibration points, using the least squares method to calculate the mapping parameter matrix. Coordinate matrix output, according to the coordinate matrix relationship of the sub-area center coordinates and the offset output, to form a preset coordinate conversion matrix. Technical effect: accurate coordinate conversion, the preset coordinate conversion matrix enables the system to accurately convert the event position in the gun camera coordinate system to the target position in the ball camera coordinate system. Automated linkage response, when the trigger event is captured by the gun camera, the system can automatically adjust the angle of the ball camera to ensure that the event remains in the center area of ​​the monitoring screen. Optimized resource utilization: Through precise coordinate conversion and event tracking, the system can more effectively utilize monitoring resources and improve monitoring efficiency. Improved monitoring quality: The system can ensure the quality of the monitoring screen through automated tracking and adjustment, so that events in the monitoring area can be clearly recorded. In summary, this technical solution improves the performance and efficiency of the intelligent camera system in a multi-camera monitoring environment through precise coordinate conversion and automated camera adjustment.

[0042] In some of the embodiments, an adaptive algorithm is used to automatically adjust the calibration parameters in the linkage association matrix according to the real-time monitoring screen.

[0043] In this embodiment, the technical solution of the present invention describes a method for automatically adjusting the calibration parameters in the linkage association matrix according to the real-time monitoring screen using an adaptive algorithm. An adaptive algorithm is an algorithm that can automatically adjust its parameters or behaviors according to input data or environmental changes. In an intelligent camera system, the algorithm can dynamically adjust the calibration parameters of the camera to adapt to different monitoring conditions and scenarios. Real-time monitoring screen analysis, the system analyzes the monitoring screen in real time to detect visual features such as motion, color, and shape. Adaptive algorithm application, according to the content of the real-time monitoring screen, the adaptive algorithm automatically adjusts the parameters in the linkage association matrix, such as focal length, shooting angle, etc. Linkage association matrix adjustment, the linkage association matrix is ​​updated according to the adjustment of the adaptive algorithm, ensuring that the camera system can accurately track and respond to activities in the monitoring area. Parameter optimization, the adaptive algorithm continuously optimizes parameters according to historical data and current performance, and improves the accuracy and efficiency of the monitoring system. Technical effect: Improved accuracy, the adaptive algorithm can automatically adjust parameters according to the real-time monitoring screen, and improves the accuracy of the camera system in identifying and tracking specific events. Fast response, the system can quickly respond to changes in the monitoring area and adjust the camera in time to capture important monitoring events. Enhanced adaptability: The adaptive algorithm enables the camera system to adapt to various monitoring environments and conditions, such as light changes, weather changes, etc. Reduced manual intervention: Through automated parameter adjustment, the need for manual intervention is reduced, and the intelligence level of the monitoring system is improved. Improved monitoring quality: The system can automatically adjust according to the real-time monitoring screen to ensure the quality of the monitoring screen, so that events in the monitoring area can be clearly recorded. In summary, the technical solution of automatically adjusting the calibration parameters in the linkage association matrix using an adaptive algorithm can improve the performance and efficiency of the intelligent camera system in a complex and changeable monitoring environment. In the intelligent monitoring system, the specific models of the adaptive algorithm may include the following types: Adaptive threshold algorithm, used for target detection, automatically adjusts the detection threshold according to the change of ambient light. Kalman filter, used for target tracking, predicts and updates the position and speed of the target. Particle filter, used for target tracking that processes nonlinear and / or non-Gaussian noise statistical characteristics. Adaptive reinforcement learning algorithm, used for pattern recognition, automatically identifies and tracks targets through machine learning methods. Neural networks, used for image recognition and classification, identify targets by learning a large amount of image data. Support Vector Machines (SVM), used for classification problems, to determine the boundary that best represents two types of data. Adaptive control algorithms, used to adjust camera parameters such as focal length, aperture, and exposure time. Fuzzy Logic Controller, used for fuzzy control, to handle uncertainty and ambiguity problems.Genetic Algorithms are used for optimization problems and search for the best solution through natural selection. Deep learning models, such as convolutional neural networks (CNNs), are used for image recognition and classification.

[0044] In some of the embodiments, the origin coordinates of the dome camera are preset to be located in the middle of the at least two gun cameras, and also include: when switching from an off state to a switch state, controlling the dome camera to move and patrol according to a preset path, the origin coordinates of the dome camera are preset to be located in the middle of the at least two gun cameras, and there are pixel overlaps in the monitoring areas of the dome camera and the gun camera.

[0045] In this embodiment, the technical solution of the present invention describes a method for intelligent camera linkage correction, which involves controlling the ball camera to move and patrol according to a preset path when the camera is switched from the off state to the on state. The origin coordinates of the ball camera are preset in the middle position of at least two gun cameras to ensure that there are pixel overlap points between the monitoring areas of the ball camera and the gun camera. This process includes: the camera starts patrolling, when the camera system is started, the ball camera patrols according to the preset path to ensure that the preset monitoring area defined by at least two gun cameras is covered. Origin coordinate positioning, the origin coordinates of the ball camera are set in the middle position of the two gun cameras. This positioning method helps to achieve seamless connection between the two gun cameras and the ball camera in monitoring coverage. Confirmation of pixel overlap points, by ensuring that there are pixel overlap points between the monitoring areas of the gun camera and the ball camera, enhances the continuity and accuracy of monitoring. Technical effect: Enhanced monitoring continuity, by patrolling when the camera is started, ensuring that the monitoring area is covered in time and reducing monitoring blind spots. Improve positioning accuracy, set the origin coordinates of the ball camera in the middle of the gun camera, and ensure that there are pixel overlaps between the monitoring areas, thereby improving the accuracy of monitoring positioning. Optimized monitoring experience, through automatic patrol and precise positioning, users can get a more stable and reliable monitoring experience. Improved system reliability, the setting of preset paths and origin coordinates helps to quickly enter the monitoring state after the camera is started, improving the reliability of the entire monitoring system. In summary, this technical solution achieves effective coverage of the monitoring area and precise positioning of the monitoring screen through the linkage correction of the intelligent camera, improving the performance of the monitoring system and user experience.

[0046] In some of the embodiments, the tracking mode of the ball camera is automatically selected according to the preset coordinate transformation matrix and the preset linkage rules, wherein the tracking mode includes at least one of a locked tracking mode, an intelligent area tracking mode, a multi-target tracking mode, an event-triggered tracking mode, and a virtual fence tracking mode.

[0047] In this embodiment, the technical solution describes a method for selecting an automatic tracking mode of a ball camera in an intelligent camera system. The method automatically selects the tracking mode of the ball camera based on a preset coordinate conversion matrix and linkage rules. The coordinate conversion matrix is ​​used to convert the coordinates in the gun camera coordinate system into the coordinates in the ball camera coordinate system, thereby achieving accurate target tracking. The linkage rules are used to automatically select the most appropriate tracking mode according to the scene requirements and the characteristics of the triggering event. Among them, the tracking mode includes at least: a. Lock tracking mode, which is used to continuously track a specific target regardless of how the target moves; b. Smart area tracking mode, which starts tracking only when the target moves to a preset key area; c. Multi-target tracking mode, which can simultaneously track a preset number of multiple targets; d. Event-triggered tracking mode, which starts tracking only when a specific event is triggered, such as motion detection or sound recognition; e. Virtual fence tracking mode, which tracks the target and ensures that it remains within a preset virtual fence. Technical effect: multiple tracking modes, the system provides multiple tracking modes, including lock tracking mode, smart area tracking mode, multi-target tracking mode, event-triggered tracking mode and virtual fence tracking mode to adapt to different monitoring needs and scenarios. Automated intelligent selection: Through adaptive algorithms, the system can automatically adjust and select the most appropriate tracking mode according to the real-time monitoring screen, improving monitoring efficiency and response speed. Improve tracking accuracy: The combined use of coordinate transformation matrix and linkage rules enables the ball camera to more accurately track specific events or targets in the monitoring area. Enhance the intelligence of the monitoring system: The function of automatically selecting the tracking mode reduces manual intervention and improves the automation and intelligence level of the monitoring system. Optimize resource utilization: The system can dynamically adjust resource allocation, such as CPU and storage resources, according to actual monitoring needs to make the most efficient use of system resources. In summary, this technical solution improves the performance and efficiency of the intelligent camera system in complex and changing monitoring environments by intelligently selecting the tracking mode of the ball camera.

[0048] This embodiment also provides an intelligent camera linkage correction system, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated here. As used below, the terms "module", "unit", "subunit", etc. can be a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0049] Figure 3 is a structural block diagram of the intelligent camera linkage correction system according to an embodiment of the present application, such as Figure 3 As shown, the device includes a camera module 31, a detection module 32, a processing module 33 and a tracking module 34, wherein:

[0050] The camera module 31 is used to obtain a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature;

[0051] A detection module 32, coupled to the camera module 31, is used to extract the trigger feature from the trigger event, and determine the occurrence of a specific event using a database according to the trigger feature, wherein the database at least contains the association corresponding data between the trigger feature and the specific event;

[0052] A processing module 33, coupled to the detection module 32, for determining an acquisition source of the trigger event according to the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera;

[0053] The tracking module 34 is coupled to the processing module 33, and is used to determine the target position of the ball camera using a preset coordinate transformation matrix when it is determined that the acquisition source is a gun camera, and send a control instruction to the ball camera, and control the ball camera to adjust the shooting angle according to the target position information so that the specific event remains in the center area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is a ball camera, determine the target position of the ball camera, and send a control instruction to the ball camera, the control instruction at least includes the target position information, and control the ball camera to adjust the shooting angle according to the target position information so that the specific event remains in the center area of ​​the monitoring screen; wherein the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one ball camera.

[0054] In some of the embodiments, it also includes: a tracking mode switching module 35, coupled with the tracking module 34, for automatically selecting the tracking mode of the ball camera according to the preset coordinate transformation matrix and the preset linkage rules, wherein the tracking mode includes at least one of the locked tracking mode, the intelligent area tracking mode, the multi-target tracking mode, the event-triggered tracking mode, and the virtual fence tracking mode.

[0055] The beneficial effects brought by the technical solution of the present invention are as follows: intelligent detection, tracking and linkage functions are realized, and the automation and efficiency of the monitoring system are improved. Through the linkage correction system, intelligent collaboration between the gun camera and the ball camera is realized, and manual intervention and errors are reduced. Through the linkage correction system, the linkage monitoring function of multiple cameras is realized. It is highly flexible and suitable for a variety of scenes and environments, and can meet different monitoring needs. And in order to better illustrate the application of the present invention, it is described by the following specific embodiments.

[0056] Example 1: Home outdoor monitoring

[0057] Condition: Turn on the detection system and linkage system.

[0058] Operation: Install the 4-camera of the present invention outdoors to monitor the gate or parking area. Enable the human detection system through the APP. When someone enters the monitoring area, a human event will be triggered, and an alarm message will be automatically sent to the APP. The target will be automatically tracked and recorded.

[0059] Example 2: School bullying monitoring

[0060] Condition: Turn on human detection, crying detection and linkage systems.

[0061] Operation: Place the 4 cameras of the present invention along the stairways or activity areas in the campus. Use the APP to start the human detection system. When bullying occurs in the school, the system can realize all-round tracking and recording to avoid the occurrence of blind spots in monitoring.

[0062] This embodiment further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0063] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0064] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0065] In addition, in combination with the intelligent camera linkage correction method in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any one of the intelligent camera linkage correction methods in the above embodiment is implemented.

[0066] Those skilled in the art should understand that the technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0067] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A smart camera linkage correction method, characterized in that: include: Acquire a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; Extracting the trigger feature from the trigger event, and determining the occurrence of a specific event using a database according to the trigger feature, wherein the database at least contains the association corresponding data between the trigger feature and the specific event; Determining the acquisition source of the trigger event according to the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera; When it is determined that the acquisition source is a gun camera, the target position of the dome camera is determined using a preset coordinate transformation matrix, and a control instruction is sent to the dome camera. According to the target position information, the dome camera is controlled to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is a dome camera, the target position of the dome camera is determined, and a control instruction is sent to the dome camera, the control instruction at least includes the target position information, and according to the target position information, the dome camera is controlled to adjust the shooting angle so that the specific event remains in the center area of ​​the monitoring screen; wherein the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one dome camera.

2. The method according to claim 1, characterized in that The preset coordinate transformation matrix includes: The origin coordinate of the ball camera is preset to be located in the middle position of the at least two gun cameras; Dividing the monitoring area of ​​the at least two gun cameras into preset sub-areas, and recording the center coordinates of each sub-area; The image coordinates of the sub-area are collected and input into a preset correction algorithm, and the associated angles between the at least two gun cameras and the ball camera are calculated to form the preset coordinate conversion matrix.

3. The method according to claim 2, characterized in that The image coordinates of the sub-area are collected and input into a preset correction algorithm to calculate the associated angles of the at least two gun cameras and the ball camera, respectively, including: The image coordinates of the sub-area are collected and input into a preset correction algorithm to calculate the offset from the origin coordinates of the ball camera to the center coordinates of the sub-area; The focal length in pixels in x and y directions and the image plane coordinates are calculated using the distortion correction method; At least three non-coplanar calibration points are selected by a calibration method, and a mapping parameter matrix is ​​calculated by a least square method; The preset coordinate transformation matrix is ​​formed according to the coordinates of the sub-region center and the offset output coordinate matrix relationship.

4. The method according to claim 3, characterized in that Also includes: An adaptive algorithm is used to automatically adjust the calibration parameters in the linkage association matrix according to the real-time monitoring screen.

5. The method according to claim 2, characterized in that: The method of presetting the origin coordinate of the ball camera to be located at the middle position of the at least two gun camera cameras also includes: When switching from the off state to the on state, the ball camera is controlled to move and patrol according to a preset path. The origin coordinates of the preset ball camera are located in the middle position of the at least two gun cameras, and there are pixel overlaps in the monitoring areas of the ball camera and the gun camera.

6. The method according to claim 1, characterized in that According to the preset coordinate transformation matrix and the preset linkage rules, the tracking mode of the ball camera is automatically selected, wherein the tracking mode includes at least one of the locked tracking mode, the intelligent area tracking mode, the multi-target tracking mode, the event-triggered tracking mode, and the virtual fence tracking mode.

7. An intelligent camera linkage correction system, characterized in that: include: A camera module, used to obtain a trigger event in a preset monitoring area, wherein the trigger event includes at least one trigger feature; A detection module, coupled to the camera module, for extracting the trigger feature from the trigger event, and determining the occurrence of a specific event using a database according to the trigger feature, wherein the database at least contains the corresponding data of the association between the trigger feature and the specific event; a processing module, coupled to the detection module, for determining an acquisition source of the trigger event according to the trigger feature, wherein the acquisition source is at least one of two gun cameras and one ball camera; The tracking module is coupled with the processing module and is used to determine the target position of the ball camera using a preset coordinate transformation matrix when it is determined that the acquisition source is a gun camera, and send a control instruction to the ball camera, and control the ball camera to adjust the shooting angle according to the target position information so that the specific event remains in the center area of ​​the monitoring screen; otherwise, when it is determined that the acquisition source is a ball camera, determine the target position of the ball camera, and send a control instruction to the ball camera, the control instruction at least including the target position information, and control the ball camera to adjust the shooting angle according to the target position information so that the specific event remains in the center area of ​​the monitoring screen; wherein the control instruction at least includes the target position information, and the monitoring screen at least includes the preset monitoring area, and is covered by the monitoring areas of at least two of the gun cameras and one ball camera.

8. The system according to claim 7, characterized in that include: A tracking mode switching module is coupled to the tracking module and is used to automatically select the tracking mode of the ball camera according to the preset coordinate transformation matrix and the preset linkage rules, wherein the tracking mode includes at least one of the locked tracking mode, the intelligent area tracking mode, the multi-target tracking mode, the event-triggered tracking mode, and the virtual fence tracking mode.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps of the intelligent camera linkage correction method according to any one of claims 1 to 6.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of intelligent camera linkage correction according to any one of claims 1 to 6 are implemented.

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