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In real world application, video security is becoming more important now-a-days due to the happening of unwanted events in our surroundings. Moving object detection is a challenging task in low resolution video, variable lightening conditions and in crowed area due to the limitation of pattern recognition techniques and itlooses many important details in the visual appearance of the moving object...
This paper presents a method to detect unusual behavior in human crowds based on histograms of velocities in world coordinates. A combination of background removal and optical flow is used to extract the global motion at each image frame, discarding small motion vectors due artifacts such as noise, non-stationary background pixels and compression issues. Using a calibrated camera, the global motion...
Activity modeling and unusual event detection in a network of cameras is challenging, particularly when the camera views are not overlapped. We show that it is possible to detect unusual events in multiple disjoint cameras as context-incoherent patterns through incremental learning of time delayed dependencies between distributed local activities observed within and across camera views. Specifically,...
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