Abstract—Recently, a 3D face recognition approach based on

geometric invariant signatures, has been proposed. The key idea

of the algorithm is a representation of the facial surface, invariant

to isometric deformations, such as those resulting from facial

expressions. One of the crucial stages in the construction of the

geometric invariants is the measurement of geodesic distances on

triangulated surfaces, carried out by fast marching on

triangulated domains (FMTD). Proposed here is a method, which

uses only the metric tensor of the surface for geodesic distance

computation. When combined with photometric stereo used for

facial surface acquisition, it allows constructing a bending-

invariant representation of the face without reconstructing the 3D

surface. -　

Abstract—Recently, a 3D face recognition approach based on

geometric invariant signatures, has been proposed. The key idea

of the algorithm is a representation of the facial surface, invariant

to isometric deformations, such as those resulting from facial

expressions. One of the crucial stages in the construction of the

geometric invariants is the measurement of geodesic distances on

triangulated surfaces, carried out by fast marching on

triangulated domains (FMTD). Proposed here is a method, which

uses only the metric tensor of the surface for geodesic distance

computation. When combined with photometric stereo used for

facial surface acquisition, it allows constructing a bending-

invariant representation of the face without reconstructing the 3D

surface.