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In this paper, we aim to study the problem of 3D face recognition. This problem becomes complex when we consider the human face expressions and different face occlusions. In this context is situated our work, we use the 3D UMB database to evaluate two powerful methods: the 3D Local Binary Pattern (3D-LBP) and the 3D Grey Level Co-occurrence Matrix (3D-GLCM). We tested also the combination of these...
We propose a robust method for 3D face recognition using 3D to 2D modeling and facial curvatures detection. The 3D-2D algorithm permits to transform 3D images into 3D triangular mesh, then the mesh model is deformed and fitted to the 2D space in order to obtain a 2D smoother mesh. Then, we apply Gabor wavelets to the deformed model in order to exploit surface curves in the detection of salient face...
Automatic location of face salient points is one of the key steps in 3D face recognition. This paper presents a fully automatic locating algorithm for 3D facial nose tip and inner eye corner in different views, which relies on a statistical model by combining local shape map and local shape index with the statistical radius of the local shape map. The experimental results on the CASIA 3D face database...
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