MULTIIMAGE PHOTOMETRIC STEREO USING SURFACE APPROXIMATION BY LEGENDREPOLYNOMIALS

This paper presents a photometric stereo algorithm that reconstructs o bject shapes from multiple images, in which given 3D surfaces are appr oximated by Legendre polynomials and the relationships between the giv en surface and its derivatives are represented in matrix forms in term s of a polynomial coefficient vector. The reflectance map is linearize d and the cost function expressed in quadratic matrix form in terms of the polynomial coefficient vector is minimized. The relative depth an d its derivatives are obtained by updating them iteratively. Computer simulation with various noiseless/noisy sets of test images shows that the performance of the presented two-image photometric stereo algorit hm is comparable to that of the conventional methods in terms of three different error measures: brightness error, orientation error and hei ght error. Also the performance comparison of the presented and conven tional three-image photometric stereo algorithms for the noiseless/noi sy sets of images is shown. (C) 1998 Pattern Recognition Society. Publ ished by Elsevier Science Ltd. All rights reserved.