Extracting invariant features of the human face from 3D range data

Abstract

The surface of the human face can be represented by a set of facets. The Phase Fourier Transform (PFT) can be used to transform a facet in the space domain to a peak in the frequency domain. The position and the distribution of the peak represent the orientation and shape of the facet respectively. The PFT of the human face provides a new signature of the face. The intensity of the PFT is invariant to the shift and out-of-plane rotation within a certain angle. It is also scale invariant within a certain range. We have used Circular Harmonic m-r filtering to achieve the in- plane partial rotation invariance. The recognition decision is based on the intensity and performance of the correlation peak.