DocumentCode
2606766
Title
A Comparison of Pixel, Edge andWavelet Features for Face Detection using a Semi-Naive Bayesian Classifier
Author
Beveridge, J. Ross ; Saraf, Jilmil ; Randall, B.
Author_Institution
Dept. of Comput. Sci., Colorado State Univ., Fort Collins, CO
Volume
3
fYear
0
fDate
0-0 0
Firstpage
1175
Lastpage
1178
Abstract
Henry Schneiderman at Carnegie Mellon University developed a face detection algorithm based upon a semi-naive Bayesian classifier and 5/3 linear phase wavelets. This paper explores the relative value of these wavelet features compared to simpler pixel and edge features. Experiments suggest edge features are superior for highly controlled lighting, while pixel features are better and more stable for uncontrolled lighting. Tests use the Notre Dame face data collected in Fall 2003 and Spring 2004 and use over 400, 000 face and non-face test image chips
Keywords
edge detection; face recognition; feature extraction; Notre Dame face data; edge feature comparison; face detection; linear phase wavelets; pixel feature comparison; seminaive Bayesian classifier; wavelet feature comparison; Bayesian methods; Computer science; Computer vision; Face detection; Face recognition; Image edge detection; Lighting control; Pixel; Springs; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.50
Filename
1699735
Link To Document