Video Analysis of Vehicles and Persons for Surveillance

This chapter presents a multi-perspective vision-based analysis of the activities of vehicles and persons for the enhancement of situational awareness in surveillance. Multiple perspectives provide a useful invariant feature of the object in the image, i.e., the footage area on the ground. Moving objects are detected in the image domain, and the tracking results of the objects are represented in the projection domain using planar homography. Spatio-temporal relationships between human and vehicle tracks are categorized as safe or unsafe situation depending on the site context such as walkway and driveway locations. Semantic-level information of the situation is achieved with the anticipation of possible directions of near-future tracks using piecewise velocity history. Crowd density is estimated from the footage on the homography plane. Experimental data show promising results. Our framework can be applied to broad range of situational awareness for emergency response, disaster prevention, human interactions in structured environments, and crowd movement analysis in a wide field of view. 2 Sangho Park, Mohan M. Trivedi