Human face detection and tracking based on supervised learning

Min Luo; Xiaohui Duan; Shiwen Zhu; Zheng Song; Chaohui Zhan

doi:10.1117/12.749583

15 November 2007 Human face detection and tracking based on supervised learning

Min Luo, Xiaohui Duan, Shiwen Zhu, Zheng Song, Chaohui Zhan

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67862A (2007) https://doi.org/10.1117/12.749583
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Min Luo, Xiaohui Duan, Shiwen Zhu, Zheng Song, and Chaohui Zhan "Human face detection and tracking based on supervised learning", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862A (15 November 2007); https://doi.org/10.1117/12.749583

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