with a camera geometry transformation and by incorporating the stereo data as an initial estimate were investigated Based on the traditional problem formulation, it is difficult to integrate the two important vision cues, i.e., shading and by Shao et al. [17] and Leclerc and Bobik [9], respectively. stereo, for shape reconstruction due to conflicting albedo and Recently, Cryer et al. [2] proposed a method based on a image projection assumptions. In this research, we propose a human visual model which integrates the low-frequency novel scheme to integrate shading and stereo. First, by using the information from the stereo and high-frequency informaphotometric ratio, we derive a new SFS (shape from shading) tion from SFS.
formulation where no albedo is needed for shape reconstruction.
However, there exist two major difficulties in their inte-Then, we establish a unified framework for the integration of gration since the basic assumptions of the stereo method photometric ratio and stereo by employing perspective projecand the traditional SFS technique are conflicting. One is tion on a parametric surface via minimizing a cost functional due to the albedo assumption of the object surface. The which consists of a weighted sum of shading and stereo errors. stereo method utilizes the feature of highly textured (vary-Simulation results are given to show the performance of our new robust algorithm.