3D face recognition using local binary pattern and grey level co-occurrence matrix

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 two approaches. A training phase is necessary, to pass to the test phase which is followed by classification. We use a multiclass Support Vector Machines (SVM) for classification. The experimental results prove that in this classification problem 3D-LBP is the more suitable.