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Real-time Multiple People Tracking using Competitive Condensation  

강희구 (포항공과대학교 컴퓨터공학과)
김대진 (포항공과대학교 컴퓨터공학과)
방승양 (포항공과대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.30, no.7_8, 2003 , pp. 713-718 More about this Journal
Abstract
The CONDENSATION (Conditional Density Propagation) algorithm has a robust tracking performance and suitability for real-time implementation. However, the CONDENSATION tracker has some difficulties with real-time implementation for multiple people tracking since it requires very complicated shape modeling and a large number of samples for precise tracking performance. Further, it shows a poor tracking performance in the case of close or partially occluded people. To overcome these difficulties, we present three improvements: First, we construct effective templates of people´s shapes using the SOM (Self-Organizing Map). Second, we take the discrete HMM (Hidden Markov Modeling) for an accurate dynamical model of the people´s shape transition. Third, we use the competition rule to separate close or partially occluded people effectively. Simulation results shows that the proposed CONDENSATION algorithm can achieve robust and real-time tracking in the image sequences of a crowd of people.
Keywords
Condensation; Multiple people tracking; Competitive rule; SOM; HMM;
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