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PCM
2004
Springer

Probabilistic Face Tracking Using Boosted Multi-view Detector

14 years 4 months ago
Probabilistic Face Tracking Using Boosted Multi-view Detector
Face tracking in realistic environments is a difficult problem due to pose variations, occlusions of objects, illumination changes and cluttered background, among others. The paper presents a robust and real-time face tracking algorithm. A novel likelihood is developed based on a boosted multi-view face detector to characterize the structure information. The likelihood function is further integrated with particle filter which can maintain multiple hypotheses. The algorithm proposed is able to track faces in different poses, and is robust to temporary occlusions, illumination changes and complex background. In addition, it enjoys a real-time implementation. Experiments with a challenging image sequence shows the effectiveness of the algorithm.
Peihua Li, Haijing Wang
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PCM
Authors Peihua Li, Haijing Wang
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