Intelligent video monitoring method and system capable of exploring abnormal events
A technology for intelligent video monitoring and abnormal events, which is applied in closed-circuit television systems, computer components, image data processing, etc., and can solve problems such as low intelligence and poor real-time performance
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Embodiment 1
[0033] refer to figure 1 and figure 2 , an intelligent video surveillance processing method with abnormal event mining function, the method comprises the following steps:
[0034] Step 1, the passive camera monitors abnormal conditions around the camera, and collects video data in the monitoring scene;
[0035] Step 2. Detect and track the moving object appearing in the monitoring scene, mark the moving object, and transmit the position and size parameters of the moving object to the active camera;
[0036] Step 3: According to the obtained position and size parameters of the active camera, according to the set parameters, judge whether it is necessary to mobilize the active camera to obtain the local close-up of the target; if the requirement of mobilizing the active camera is met, adjust the parameters of the active camera and posture, adaptively give close-up close-ups of moving targets that appear in the monitoring scene; also judge whether it is necessary to stop the m...
Embodiment 2
[0056] refer to figure 1 and figure 2 , an intelligent video surveillance processing system with abnormal event mining function, said system comprising:
[0057] The video acquisition module is used to collect video in the monitoring area, and uses a pair of master-slave cameras to work together to monitor abnormal events in the scene;
[0058] The intelligent detection module is used to detect and track the moving target in the monitoring area, and obtain the real-time position and size parameters of the moving target;
[0059] The abnormal event mining module is used to understand the behavior of the classified moving target, extract the behavioral characteristics of the moving human target itself, compare the trained behavior samples, identify its behavior and judge whether it is abnormal behavior, according to the set Determine whether an abnormal event has occurred according to the specified abnormal behavior standard. If no abnormal event occurs, it will return to con...
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