Unusual activity detection for video surveillance

Abstract

ideo surveillance has gained importance in law enforcement, security and military applications. The system consists of processing steps such as object detection, movement tracking, and activity monitoring. The paper contribution is to present the human activity analysis system that both detect a human with carrying or abandoning an object and segments the object from the human so that it can be tracked. Segmentation of objects is done from the background using advance Gaussian mixture model. The tracking algorithm considers the human as whole from frame to frame, it does not track the human parts such as limbs. Object features such as center of mass, size, and bounding box are used in this paper to estimate a matching between objects in consecutive frames. As the object is segmented and tracked, Bayesian inference framework is used for event analysis. This system uses a single camera view and unusual activity is detected using the detected objects and object tracking result. The operator is notified if an unusual activity is detected.