Improving Face Detection through Fusion of Contour and Region Information
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Based on the complementarity of face contour and facial region, the paper proposes a novel contour-region face detector. A new feature extraction method is proposed to efficiently depict face contour pattern. Both Face-Contour-Classifier and the Facial-Region-Classifier are trained as Support Vector Machine models. Bayesian decision rule is adopted to fusing both Face-Contour- and Facial-Region- classifiers. The proposed face detector is tested on a standard head image database, BioID gray color face image database and a color face database. Experimental results demonstrate the efficiency of the proposed contour-region face detector.