Analysis and Evaluation of Several Typical SFS Algorithms
LIAO Yi, ZHAO Rong-chun (Northwest Polytechnical University, Xi'an 710072)
Shape from shading(SFS) is one of the critical techniques to shape recovery in computer vision,which obtains 3-D shape of the visible surface of an object from only one image of it using the shading knowledge in the given picture. In order to give an outline of over 30 years' research work on SFS problems and try to make sense to beginners of advantages and disadvantages of varions methods to solve such problems, this paper adopted the common classification of all SFS methods presented up to now, namely, minimizaiton methods, propagation methods,localization methods, and linearization methods,to each of which some typical algorithms were analyzed both from principles and experiments point of view. Comparisons between and evaluations of these methods together with their corresponding algorithms were also given in several aspects,such as the uniqueness of the recovered surface,the approximation ability to the true surface,the effectiveness and applicability of the algorithm,etc.Through the discussion, we agreed that there is no method applicable to all kinds of SFS problems, and each method has its own range of applicability. In the end,the paper concluded in the unresolved problems to SFS as well as some indications to future work.