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Face Detection and Facial Feature Extraction Using Support Vecto Machines
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104743416th International Conference on Patt ...
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Dihua Xi, Korea University
Seong-Whan Lee, Korea University
This paper proposes a new fast algorithm for detecting human face and extracting the facial features. For this task, we have developed a flexible coordinate system and several support vector machines. The design of a face model for both detection and extraction is based on multi-resolution wavelet decomposition (MWD). Using a mean face, the MWD and a small number of feature points are applied for rough searching by estimating the modified cross correlation (MCC). More accurate results can be achieved by a serious of support vector machines (SVMs). Experimental results show that the proposed approach is fast and has a high detection rate even in cases when a face is embedded in a complicated background.
Citation:
Dihua Xi, Seong-Whan Lee, "Face Detection and Facial Feature Extraction Using Support Vecto Machines," icpr, vol. 4, pp.40209, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 4, 2002
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