한국정보통신학회:학술대회논문집 (Proceedings of the Korean Institute of Information and Commucation Sciences Conference)
- 한국해양정보통신학회 2004년도 SMICS 2004 International Symposium on Maritime and Communication Sciences
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- Pages.106-109
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- 2004
A study on Face Image Classification for Efficient Face Detection Using FLD
초록
Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..
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