3D face recognition using multi matcher approach

In the last decades 3D face recognition is considered as the most promising axe of reasearch; however its amelioration with information from different resources seems to be more encouraged. Our motivation for a fusion information step is that the data issues from matchers based on different approaches can be completed and determined. Then we propose in this paper a new method of 3D facial recognition based on information fusion. Firstly we describe the different algorithms (matchers) used for face recognition and results issues from each algorithm. Secondly, fusion techniques were tested using those three algorithms. Finally, we present results of our approach which achieve an excellent recognition rate. To validate our approach a subset taken from FRGC v2 dataset is used, the experiments are tested for the both scenarios known in biometric; authentication and identification.