3D face has recently emerged as a major trend in face recognition. While 3D face is reputed to be relatively invariant to lighting conditions and pose, one still needs to cope with facial expression variations for a reliable face recognition solution. Many works in the literature try to define some invariants with respect to facial expressions. In this paper, we consider facial expressions as results of moving parts of a facial surface, and thus a careful study of anatomical face enables us to set up a region-based face surface matching, giving more importance to stable facial regions in the comparison. The very first experiments show the effectiveness of our approach.