Title Human face detection and tracking based on supervised learning - art. no. 67862A
Authors Luo, Min
Duan, Xiaohui
Zhu, Shiwen
Song, Zheng
Zhan, Chaohui
Affiliation Peking Univ, Inst Elect Engn, Signal & Informat Proc Lab, Beijing 100871, Peoples R China.
Keywords face detection
face tracking
boosted rectangle filters
representative based integration method
uniform linear motion model
quadric motion model
Issue Date 2007
Citation MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2.6786(A7862-A7862).
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.
URI http://hdl.handle.net/20.500.11897/406497
ISSN 0277-786X
DOI 10.1117/12.749583
Indexed EI
CPCI-S(ISTP)
Appears in Collections: 待认领

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