| Paper: | MLSP-P5.4 | ||
| Session: | Image and Video Processing | ||
| Time: | Thursday, May 20, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Signal detection, Pattern Recognition and Classification | ||
| Title: | FACE DETECTION USING SUPPORT VECTOR DOMAIN DESCRIPTION IN COLOR IMAGES | ||
| Authors: | Jin Seo; Korea University | ||
| Hanseok Ko; Korea University | |||
| Abstract: | In this paper, we present face detection system using Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require training procedure using the face images and non-face ones. In the SVDD, however, we use only face images for training. We can detect faces in color images from a radius and a center of the SVDD. We also use Entropic Threshold for extracting the facial feature and Sliding Window for better performance and saving the processing time. The experiments’ results indicate the effectiveness and efficiency of the proposed algorithm compared to the conventional PCA (Principal Component Analysis)-based method. | ||
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