During the last few years different video-surveillance systems have been developed based on video processing and using different techniques. This surveillance system generally seeks to track people (and/or vehicles) moving through a scene, to classify the behaviors of each track, and to identify whether these behaviors can be considered normal or abnormal. All Automated surveillance systems require some mechanism to detect interested objects in the field of view of the sensor. Once objects are detected, the further processing for tracking. In my paper a method is described for tracking moving objects from a sequence of video frame. This method is implemented by using optical flow (Horn-Schunck) and Region filtering in matlab simulink. The objective of this paper is to identify and track a moving object within a video sequence for both Abrupt change video as well as Gradual change video in video surveillance.
No takes yet. Share an insight, caveat, or question.
Shukla et al. (2013) studied this question.
Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context: