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Published in:
2012 | OriginalPaper | Chapter
Urban Traffic Monitoring System
Authors : Nam Tang, Cuong Do, Tien Ba Dinh, Thang Ba Dinh
Published in: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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Traffic video analysis is a challenging problem: crowded moving vehicles with various appearances, illumination changes, and speed variations according to the traffic flow. In this paper, we propose an efficient single-camera Traffic Monitoring System (TMS), which is capable of automatically analyzing the vehicles flow on urban streets in real time. The system has three main modules included calculating density of vehicles based on background subtraction methods, estimating average speed of traffic flow using optical flow method and counting the number of vehicles on the street by clustering motion features relied on Delaunay Triangulation algorithm. From that fundamental information, our system infers several high semantic events such as traffic jams, breaking-law vehicles, people crossing street. Experiments are demonstrated in real-life scenarios with heavy traffic in Ho Chi Minh City, Vietnam.