Multiple-person tracking system for content analysis

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Abstract

This paper presents a framework to track multiple persons in real-time. First, a method with real-time and adaptable capability is proposed to extract face-like regions based on skin, motion, and silhouette features. Then, a two-stage face verification algorithm is proposed to quickly eliminate false faces based on the face geometries and the Support Vector Machine(SVM). In order to overcome the effect of lighting changes, a method of color constancy compensation is applied. Then, a robust tracking scheme is applied to track multiple persons based on a face-status table. With the table, the system has extreme capabilities to track different persons at different statuses, which is quite important in face-related applications. Experimental results show that the proposed method is much robust and powerful than other traditional methods.

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Hsieh, J. W., Huang, L. W., & Huang, Y. S. (2001). Multiple-person tracking system for content analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2195, pp. 897–902). Springer Verlag. https://doi.org/10.1007/3-540-45453-5_118

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