Face Recognition from Facial Surface Metric

Recently, a 3D face recognition approach based on geometric invariant signatures, has been proposed. The key idea is a representation of the facial surface, invariant to isometric deformations, such as those resulting from facial expressions. One important stage in the construction of the geometric invariants involves in measuring geodesic distances on triangulated surfaces, which is carried out by the fast marching on triangulated domains algorithm. Proposed here is a method that uses only the metric tensor of the surface for geodesic distance computation. That is, the explicit integration of the surface in 3D from its gradients is not needed for the recognition task. It enables the use of simple and cost-efficient 3D acquisition techniques such as photometric stereo. Avoiding the explicit surface reconstruction stage saves computational time and reduces numerical errors.

• Type: Conference
• Year: 2004
• Where: ECCV
• Authors: Alexander M. Bronstein, Michael M. Bronstein, Alon Spira, Ron Kimmel
• Keywords: 3D Face Recognition, Computer Vision, Cost-efficient 3D Acquisition, ECCV 2004, Explicit Surface Reconstruction, Facial Surface, Geometric Invariant Signatures