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17th International Conference on Pattern Recognition (ICPR'04) - Volume 2
Boosting Nested Cascade Detector for Multi-View Face Detection
Cambridge UK
August 23-August 26
ISBN: 0-7695-2128-2
ASCII Text
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Chang Huang, Haizhou Ai, Bo Wu, Shihong Lao, "Boosting Nested Cascade Detector for Multi-View Face Detection," Pattern Recognition, International Conference on, vol. 2, pp. 415-418, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004.
 
 
BibTex
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@article{ 10.1109/ICPR.2004.1334239,
author = {Chang Huang and Haizhou Ai and Bo Wu and Shihong Lao},
title = {Boosting Nested Cascade Detector for Multi-View Face Detection},
journal ={Pattern Recognition, International Conference on},
volume = {2},
year = {2004},
issn = {1051-4651},
pages = {415-418},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334239},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - Boosting Nested Cascade Detector for Multi-View Face Detection
SN - 1051-4651
SP415
EP418
A1 - Chang Huang,
A1 - Haizhou Ai,
A1 - Bo Wu,
A1 - Shihong Lao,
PY - 2004
KW - null
VL - 2
JA - Pattern Recognition, International Conference on
ER -
 
Chang Huang, Tsinghua University, Beijing, China
Haizhou Ai, Tsinghua University, Beijing, China
Bo Wu, Tsinghua University, Beijing, China
Shihong Lao, Omron Corporation
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.
Citation:
Chang Huang, Haizhou Ai, Bo Wu, Shihong Lao, "Boosting Nested Cascade Detector for Multi-View Face Detection," icpr, vol. 2, pp.415-418, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004
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