A COMPUTATIONAL MODEL FOR SHAPE ESTIMATION BY INTEGRATION OF SHADING AND EDGE INFORMATION

In constructing a computational model for human perception of shape-from-shading, we must solve two major problems: (1) How do we estimate the shape within a small number of iterations? and (2) How do we integrate the shading and edge information for shape estimation? To solve the first problem, we propose a solution for the shape-from-shading problem by using forward and approximated inverse optics. Because the surface normal modification required due to the brightness error is separated from that required due to the smoothness constraint, we can use a simple and fast algorithm for each modification. To solve the second problem, we propose a computational model for shape estimation by integration of shading and edge information. The model is comprised of three modules for the surface normal, discontinuity, and light direction estimation. A rather weak interaction among the three modules can undo the shape-from-shading problem that resembles the chicken-and-egg problem.