A Distributed Outdoor Video Surveillance System for Detection of Abnormal People Trajectories
Abstract: Distributed surveillance systems are nowadays widely adopted to monitor large areas for security purposes. In this paper, we present a complete multicamera system designed for people tracking from multiple partially overlapped views and capable of inferring and detecting abnormal people trajectories. Detection and tracking are performed by means of background suppression and an appearance-based probabilistic approach. Objects' label ambiguities are geometrically solved and the concept of "normality" is learned from data using a robust statistical model based on Von Mises distributions. Abnormal trajectories are detected using a first-order Bayesian network and, for each abnormal event, the appearance of the subject from each view is logged. Experiments demonstrate that our system can process with real-time performance up to three cameras simultaneously in an unsupervised setup and under varying environmental conditions.
Citation:
Calderara, Simone; Cucchiara, Rita; Prati, Andrea "A Distributed Outdoor Video Surveillance System for Detection of Abnormal People Trajectories" 2007 First ACM/IEEE International Conference on Distributed Smart Cameras, Vienna, Austria, pp. 364 -371 , September 25-28 2007, 2007 DOI: 10.1109/ICDSC.2007.4357545
not available
Paper download:
- Author version:
- DOI: 10.1109/ICDSC.2007.4357545