A Multi-Camera Visual Surveillance System for Tracking of Reoccurrences of People

This paper describes a software system to track the reoccurrences of objects in multi-camera visual surveillance. Specifically, it is designed for after-event tracking of people to aid in a typical investigation of events occurring in a certain location at a certain time. This is a nontrivial problem because of several aspects that influence the appearance of scenes and people, such as changes in viewpoints, lighting conditions, shadow, occlusion, and weather conditions. Another challenge, which is the focus of this paper, is to integrate different required components into a complete working system, namely (i) motion detection, (ii) object classification, (iii) object modeling and matching, and (iv) interactive retrieval and visualization. We have designed and implemented a robust system consisting of state-of-the-art technologies in each component. We performed experiments with the system on a real-life dataset gathered from 12 street surveillance cameras over two hours in a city area. The experiments showed promising results in retrieving the reoccurrences of four target subjects.