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2005 IEEE International Conference on Multimedia and Expo
Improved face finding in visually challenging environments
Amsterdam, Netherlands
July 06-July 06
ISBN: 0-7803-9331-7
ASCII Text
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J. Jiang, G. Potamianos, G. Iyengar, "Improved face finding in visually challenging environments," Multimedia and Expo, IEEE International Conference on, pp. 4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005.
 
 
BibTex
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@article{ 10.1109/ICME.2005.1521612,
author = {J. Jiang and G. Potamianos and G. Iyengar},
title = {Improved face finding in visually challenging environments},
journal ={Multimedia and Expo, IEEE International Conference on},
volume = {0},
year = {2005},
isbn = {0-7803-9331-7},
pages = {4 pp.},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICME.2005.1521612},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Multimedia and Expo, IEEE International Conference on
TI - Improved face finding in visually challenging environments
SN - 0-7803-9331-7
SP
EP
A1 - J. Jiang,
A1 - G. Potamianos,
A1 - G. Iyengar,
PY - 2005
KW - AdaBoost technique
KW - face finding
KW - visually challenging environment
KW - face detection system
KW - IBM appearance
KW - skintone prescreening
KW - Hamming windowing
KW - DCT coefficient selection
VL - 0
JA - Multimedia and Expo, IEEE International Conference on
ER -
 
J. Jiang, IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
G. Potamianos, IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
G. Iyengar, IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Finding faces in visually challenging environments is crucial to many applications, such as audio-visual automatic speech recognition, video indexing, person recognition, and video surveillance. In this study, we investigate several algorithms to improve face detection accuracy in visually challenging environments using the IBM appearance based face detection system. The algorithms considered are trainable skintone pre-screening, Hamming windowing of the face images, DCT coefficient selection, and the AdaBoost technique. When these methods are combined, an up to 68% relative reduction in face detection error is observed on visually challenging datasets.
Index Terms:
AdaBoost technique, face finding, visually challenging environment, face detection system, IBM appearance, skintone prescreening, Hamming windowing, DCT coefficient selection
Citation:
J. Jiang, G. Potamianos, G. Iyengar, "Improved face finding in visually challenging environments," icme, pp.4 pp., 2005 IEEE International Conference on Multimedia and Expo, 2005
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