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Published Articles >> Table of Contents >> Abstract
17th International Conference on Pattern Recognition (ICPR'04) - Volume 2
pp. 415-418
Boosting Nested Cascade Detector for Multi-View Face Detection
Chang Huang, Tsinghua University, Beijing, China
Haizhou Ai, Tsinghua University, Beijing, China
Bo Wu, Tsinghua University, Beijing, China
Shihong Lao, Omron Corporation
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334239
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| Abstract |
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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], where we 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.
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 Additional Information
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Citation:
Chang Huang, Haizhou Ai, Bo Wu, Shihong Lao,
"Boosting Nested Cascade Detector for Multi-View Face Detection,"
icpr,
pp. 415-418,
17th International Conference on Pattern Recognition (ICPR'04) - Volume 2,
2004
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