3D Face Recognition Using an Expression Insensitive Dynamic Mask

Human face recognition is one of the most popular biometric approaches. In last decade 3D face recognition attracted much attention. In this paper, we present an automatic face recognition algorithm and demonstrate its performance on the Bosphorus 3D face database. A novel Dynamic mask is used to segment automatically the regions of face which are less sensitive to expressions. We applied a multilayer perceptron (MLP) to compute maskable region (MR). MR shows which percentage of face image pixels must be masked to produce the expression insensitive binary mask for 3D faces. We applied a modified nearest neighbor classifier for identification. We only used one neutral frontal face of each subject as gallery images and tested our algorithm with emotional expression images. The identification rate obtained is 85.36 percent in non-neutral expression.

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