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In this paper, we present a novel fusion approach 2D and 3D face recognition based on score level fusion using Relevance Vector Machine. RVM uses a combination of kernel functions on training data for classification and compared to SVM. Several novelties are introduced to make the recognition robust to facial expressions. These novelties include: Automatic invariant feature in the pose and in the...
In this paper, we propose a new approach which allows us producing a new representation independent from the position and the orientation of each 3D point cloud. This approach builds, from the 3D point cloud, the models of faces which are used afterward for the recognition. This framework allows us to use statistical inferences such as the estimation of the missing parts of the face by means of the...
Face analysis is a critical and popular topic in the area of computer vision and image processing for its wide application potential and scientific challenge. 2D Face analysis has been considered as a major solution to deal with unsolved issues of reliable 2D face recognition. In this paper we study and compare two classical algorithms (PCA and LDA) of features extracted which provide theoretical...
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