Multimodal Face Recognition from Depth and Intensity Curvelet Features
نویسنده
چکیده
This paper presents a face recognition based on the fusion of the intensity image and stereo depth map at the score level. The 3D surfaces are reconstructed from the stereo face images using stereo vision technique. The curvelet transform is a multiresolution method, which is used to extract features from depth and intensity images independently. Then, principal component analysis (PCA) is used to reduce the dimension of feature set. The extracted Eigen features of intensity and depth map are combined at score level to improve the face recognition rate. The combination of intensity and depth map is verified experimentally using benchmark face database.
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