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Proceedings Paper

Human face detection and tracking based on supervised learning
Author(s): Min Luo; Xiaohui Duan; Shiwen Zhu; Zheng Song; Chaohui Zhan
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Paper Abstract

In this paper a novel method of human face detection and tracking based on supervised learning for video sequence is designed. The system is composed of a face detector using boosted rectangular filters with a new representative based integration method, a linear capture model and a quadric tracking model. The main contribution of this paper is a new view to face tracking solutions on condition that a robust real-time detector is adopted first. It differs fundamentally from traditional tracking algorithms for that it organically combines fast and robust detection with efficient capture and tracking which can be easily implemented in practical video systems while obtaining a satisfying real-time performance. Experimental results show that this algorithm can finely meet the reliability and effectiveness demands of video surveillance system.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862A (15 November 2007); doi: 10.1117/12.749583
Show Author Affiliations
Min Luo, Peking Univ. (China)
Xiaohui Duan, Peking Univ. (China)
Shiwen Zhu, Peking Univ. (China)
Zheng Song, Peking Univ. (China)
Chaohui Zhan, Peking Univ. (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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