Abstract: Stereo vision is one of the critical techniques in computer vision, which determines conjugate pairs in stereo image and measures height of pixel robustly and accurately. But it can only produce a sparse set of surface depths due to the difficulty of identifying corresponding feature points in the region where gray level varies gradually. The integration of shape from shading and stereo vision is considered to be the possible outcome of the investigation of solving this problem. In this paper, the ill-posed nature of shape from shading is explained, and is applied to explicate the unreliability, instability, and limitation of the current SFS algorithms. So these algorithms are impracticable to be put into the integrated system directly. The methods of integrating the two vision modules are introduced in four categories, namely, mergence, adjustment, combination and cooperation. And it is illustrated that, the reasonable implementation of an integrated system should involve models of each vision module and models of their interaction. This could not only make it possible to overcome the ambiguity of shape from shading with the supplementary information supplied by stereo module, bur also benefit the performance of the whole vision system. Keywords Shape from shading, Stereo vision, Surface orientation, Reflective albedo