A real-time object detecting and tracking system for outdoor night surveillance

• Published in: Pattern recognition Vol. 41; no. 1; pp. 432 - 444
• Main Authors: Huang, Kaiqi, Wang, Liangsheng, Tan, Tieniu, Maybank, Steve
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2008; Elsevier Science
• Subjects: Applied sciences; Contrast; Detection and tracking; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Information, signal and communications theory; Night; Pattern recognition; Signal and communications theory; Signal processing; Signal, noise; Telecommunications and information theory; Visual surveillance; Visual surveillance; Detection and tracking; Night; Contrast; Autonomous system; Nearest neighbour; Target tracking; Moving target; Outdoor installation; Video technique; Algorithm; Remote sensing; False alarm rate; Indoor installation; Object detection; Real time processing; Target detection; Monitoring; Remote supervision
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2007.05.017

Autonomous video surveillance and monitoring has a rich history. Many deployed systems are able to reliably track human motion in indoor and controlled outdoor environments. However, object detection and tracking at night remain very important problems for visual surveillance. The objects are often distant, small and their signatures have low contrast against the background. Traditional methods based on the analysis of the difference between successive frames and a background frame will do not work. In this paper, a novel real time object detection algorithm is proposed for night-time visual surveillance. The algorithm is based on contrast analysis. In the first stage, the contrast in local change over time is used to detect potential moving objects. Then motion prediction and spatial nearest neighbor data association are used to suppress false alarms. Experiments on real scenes show that the algorithm is effective for night-time object detection and tracking.