Analyzing a Scene's Picture Set under Varying Lighting

摘要

Based on physical laws of optics, this article analytically derives a complete description of the set of all pictures that can be taken from a given scene under varying lighting, where the camera, the scene, and the light sources are static but where each light source can vary arbitrarily in radiance. It will be shown that this picture set forms a single convex region in picture space, where each picture is represented as a high-dimensional vector. An optimum radiance invariant projection is derived which is invariant under a simultaneous change of the radiances of all light sources and which decreases the dimension of the convex region by one. The theoretical predictions are confirmed experimentally for a scene illuminated with two light sources varying in intensity. A simple lighting invariant recognition algorithm is introduced and tested in a face recognition experiment. A comparison between the new algorithm and a standard recognition algorithm is presented, which shows that lighting invariant recognition leads to considerably better performance, even if the radiance of the light sourcesandthe lighting directions change.