An Interpolation Method for the Reconstruction and Recognition of Face Images
Abstract:
An interpolation method is presented for the reconstruction and recognition of human face images. Basic ingredients include an optimal basis set defining a low-dimensional face space and a set of best interpolation pixels capturing the most relevant characteristics of known faces. The best interpolation pixels are chosen as points of the pixel grid so as to best interpolate the set of known face images. These pixels are then used in a least-squares interpolation procedure to determine interpolant components of a face image very inexpensively, thereby providing efficient reconstruction of faces. In addition, the method allows a fully automatic computer system to be developed for the real-time recognition of faces. Two significant advantages of this method are 1 the computational cost of recognizing a new face is independent of the size of the pixel grid and 2 it allows for the reconstruction and recognition of incomplete images.