Theoretical analysis of illumination in PCA-based vision systems

In this paper, we address the problem: How to account for arbitrary illumin ation effects for a pose of an object in PCA-based vision systems. This is a key problem since after solving this problem, the approach can be applied directly to an arbitrary number of poses of an arbitrary number of objects . We solve this problem by first generating an analytic closed-form formula of the covariance matrix for a special lighting condition. Then after anal yzing all possible illumination effects, an equation called the illuminatio n equation is derived to account for arbitrary illumination effects. Experi ments on simulated conditions and real world conditions confirm the advanta ges of our new methods. A direct application of current research is that fo r any pose, our method can be used to compress the image of the object in a ny possible illumination. This is demonstrated in the real world experiment in the paper. Furthermore, this paper gives a new framework on how to addr ess illumination effects in computer vision in general. (C) 1999 Pattern Re cognition Society. Published by Elsevier Science Ltd. All rights reserved.