<title>Unconstrained shape from shading</title>

Abstract

Most conventional SFS (shape from shading) algorithms have been developed under three basic assumptions about surface properties and imaging geometry to simplify the problem. They are the Lambertian surface property, the orthographic projection, and the distant single light source. However, since these assumptions are not appropriate for many real applications, apparent distortions of reconstructed surfaces occur with conventional SFS algorithms. To obtain a more practically useful and accurate SFS algorithm, it is necessary to relax these restrictive assumptions and adopt more general conditions or models about the imaging process. In this research, we propose a new direct shape recovery algorithm from one or multiple shaded images generated by a general reflectance model which includes diffuse and specular effects, perspective projection, and a nearby point light source. The basic idea of our approach is to use a finite triangular surface model and express the image irradiance in terms of surface nodal depth variables through a linearized reflectance map under the perspective projection model. The object shape is recovered by determining all nodal depth variable through a cost minimization process.