Face recognition with generalized entropy measurements

Abstract

This paper describes the use of shape-from-shading for face recognition. We apply shape-from-shading to tightly cropped face images to extract fields of surface normals or needle maps. From the surface normal information, we make estimates of curvature attributes. The quantities studied include minimum and maximum curvature, mean and Gaussian curvature, and, curvedness and shape index. These curvature attributes are encoded as histograms. We perform recognition by comparing the histogram bin contents using a number of distance and similarity measures including the Euclidean distance, the Shannon entropy, the Renyi entropy and the Tsallis entropy. We compare the results obtained using the different curvature attributes and the different entropy measurements. © Springer-Verlag 2004.