Boosting Nested Cascade Detector for Multi-View Face Detection

Authors:
Chang Huang;Haizhou Ai;Bo Wu;Shihong Lao
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Omron Corporation
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Year:
2004

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Abstract

In this paper, a novel nested cascade detector for multi-view face detection is presented. This nested cascade is learned by Schapire and Singer's improved boosting algorithms that use real-valued confidence-rated weak classifiers [Improved Boosting Algorithms Using Confidence-rated Predictions], wherewe use confidence-rated Look-Up-Table (LUT) weak classifiers based on Haar features. Experiments show the system performance is significantly improved compared with previous methods.