Using Geodesic Distances for 2D-3D and 3D-3D Face Recognition

Abstract

In this paper, we propose an original framework for rep resenting 2D and 3D face information using geodesic distances. This aims to define a representation enabling 3D- 3D face recognition as well as the direct comparison between 2D face images of a subject against its 3D face model. This representation is extracted by measuring geodesic distances in 3D and 2D. In 3D, the geodesic distance between two points on a surface is computed as the length of the shortest path connecting the two points. In 2D, the geodesic distance between two pixels is computed based on the differences of gray level intensities along the segment connecting the two pixels. Experimental results are reported for 3D-3D and 2D-3D face recognition, in order to demonstrate the potential of the proposed solution.