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