DocumentCode :
2437627
Title :
Information theory and face detection
Author :
Lew, Michael S. ; Huijsmans, Nies
Author_Institution :
Dept. of Comput. Sci., Leiden Univ., Netherlands
Volume :
3
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
601
Abstract :
Face detection in complex environments is an unsolved problem which has fundamental importance to face recognition, model based video coding, content based image retrieval, and human computer interaction. In this paper we model the face detection problem using information theory, and formulate information based measures for detecting faces by maximizing the feature class separation. The underlying principle is that search through an image can be viewed as a reduction of uncertainty in the classification of the image. The face detection algorithm is empirically compared using multiple test sets, which include four face databases from three universities
Keywords :
Markov processes; face recognition; feature extraction; image classification; image matching; information theory; maximum likelihood estimation; Markov random fields; face databases; face detection; face recognition; feature class separation; image classification; information theory; maximum likelihood estimation; template matching; Content based retrieval; Face detection; Face recognition; Human computer interaction; Image databases; Image retrieval; Information theory; Spatial databases; Testing; Video coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.547017
Filename :
547017
Link To Document :
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