Abstract
The design of a video surveillance system is directed on automatic identification of events of interest, especially on tracking and classification of moving vehicles or pedestrians. In case of any abnormal activities, an alert should be issued. Normally a video surveillance system combines three phases of data processing: moving object extraction, moving object recognition and tracking, and decisions about actions. The extraction of moving objects, followed by object tracking and recognition, can often be defined in very general terms. The final component is largely depended upon the application context, such as pedestrian counting or traffic monitoring. In this paper, we review previous research on moving object tracking techniques, analyze some experimental results, and finally provide our conclusions for improved performances of traffic surveillance systems. One stationary camera has been used.
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© 2003 Springer-Verlag Berlin Heidelberg
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Zang, Q., Klette, R. (2003). Object Classification and Tracking in Video Surveillance. In: Petkov, N., Westenberg, M.A. (eds) Computer Analysis of Images and Patterns. CAIP 2003. Lecture Notes in Computer Science, vol 2756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45179-2_25
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DOI: https://doi.org/10.1007/978-3-540-45179-2_25
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