DocumentCode :
3348680
Title :
Face detection using support vector domain description in color images
Author :
Seo, Jin ; Ko, Hanseok
Author_Institution :
Dept. of Electron. & Comput. Eng., Korea Univ., Seoul, South Korea
Volume :
5
fYear :
2004
fDate :
17-21 May 2004
Abstract :
We present a system for face detection in color images using the support vector domain description (SVDD). Conventional face detection algorithms require a training procedure using both face and non-face images. In the SVDD, however, we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use entropic threshold for extracting the facial feature and sliding window for improved performance while saving processing time. Experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to the conventional PCA (principal component analysis) based methods.
Keywords :
entropy; face recognition; feature extraction; image colour analysis; learning (artificial intelligence); object detection; PCA; color images; entropic threshold; face detection; facial feature extraction; principal component analysis; sliding window; support vector domain description; training procedure; Algorithm design and analysis; Color; Face detection; Facial features; Lagrangian functions; Neural networks; Principal component analysis; Support vector machine classification; Support vector machines; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8484-9
Type :
conf
DOI :
10.1109/ICASSP.2004.1327214
Filename :
1327214
Link To Document :
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