Security and surveillance are important issues in today‟s world. Any behavior which is uncommon in occurrence and deviates from normally understood behavior can be termed as suspicious. This model aims at automatic detection of abnormal behavior in surveillance videos. We have targeted to create a system for the recognition of human activity and behavior, and extract new information of interest for end-users in highly secured indoor surveillance system. The objective of this project is to design a model for detection of abandoned objects and track abnormal human behaviors. The multi-object detection is done by background subtraction with the help of clustering techniques. Anomaly detection is done for tracking persons based on their individual appearance using Motion movement capture.
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Video Surveillance, Abnormal behaviour, Thresholding, Motion Detection.