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Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96)
Face detection using local maxima
Killington, Vermont
October 14-October 16
ISBN: 0-8186-7713-9
ASCII Text
x 
 
R. Hoogenboom, M. Lew, "Face detection using local maxima," Automatic Face and Gesture Recognition, IEEE International Conference on, pp. 334, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996.
 
 
BibTex
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@article{ 10.1109/AFGR.1996.557287,
author = {R. Hoogenboom and M. Lew},
title = {Face detection using local maxima},
journal ={Automatic Face and Gesture Recognition, IEEE International Conference on},
volume = {0},
year = {1996},
isbn = {0-8186-7713-9},
pages = {334},
doi = {http://doi.ieeecomputersociety.org/10.1109/AFGR.1996.557287},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Automatic Face and Gesture Recognition, IEEE International Conference on
TI - Face detection using local maxima
SN - 0-8186-7713-9
SP
EP
A1 - R. Hoogenboom,
A1 - M. Lew,
PY - 1996
KW - face recognition; human face detection; digital images; complex environment; computer vision; pattern recognition; human face recognition; content based image retrieval; model based video coding; image pyramid; nose-eye templates; local maxima method; false positives; image databases; template matching
VL - 0
JA - Automatic Face and Gesture Recognition, IEEE International Conference on
ER -
 
R. Hoogenboom, Dept. of Comput. Sci., Leiden Univ., Netherlands
M. Lew, Dept. of Comput. Sci., Leiden Univ., Netherlands
Automatic human face detection in digital images with a complex environment is still an unsolved problem in computer vision and pattern recognition. It has several uses, such as human face recognition, content based image retrieval and model based video coding. We present an automatic human face detection system where several methods are tested and compared. The underlying principle of the system is to compare subimages of the image pyramid, spanned by the input image, with a set of 'nose-eye' templates. However this comparison is not done on the entire set of subimages of the image pyramid, but on a small subset, which is defined by the 'local maxima method'. False positives are found by using a set of non-face templates. The system is tested on two databases, each include over 1000 images.
Index Terms:
face recognition; human face detection; digital images; complex environment; computer vision; pattern recognition; human face recognition; content based image retrieval; model based video coding; image pyramid; nose-eye templates; local maxima method; false positives; image databases; template matching
Citation:
R. Hoogenboom, M. Lew, "Face detection using local maxima," fg, pp.334, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996
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