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
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;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.50
