Nonrigid-Deformation Recovery for 3D Face Recognition Using Multiscale Registration

Nonrigid deformation is a fundamental feature in face recognition. The proposed method extracts nonrigid deformation by finding the mapping between two shapes. To improve registration accuracy, it integrates geometric shape decomposition and nonrigid point-set registration. On the basis of manifold harmonics, the method first decomposes shapes into low-frequency and high-frequency parts. Then, it applies the modified registration algorithm to obtain deformation parameters. An extensive set of experiments evaluated the method´s performance on the FRGC (Face Recognition Grand Challenge) v2 database. The method achieved not only higher accuracy for fitting but also 98.2 percent identification and 97.4 percent verification at a 0.001 false-acceptance rate.