Similarity-based matching for face authentication

We propose in this paper a face authentication method based on a similarity measure. The SIFT descriptor is used to define some interest keypoints characterized by an invariant parameter. A graph is then built where nodes correspond to these keypoints. We model the authentication problem as a graph matching process. Experimental results on the AR database show an EER equals to 12% with only one image used for the enrollment and with images simulating real conditions.