从明暗恢复形状(SFS)的几类典型算法分析与评价

Analysis and Evaluation of Several Typical SFS Algorithms

从明暗恢复形状 (shape from shading,简称 SFS)是计算机视觉中三维形状恢复问题的关键技术之一 ,其任务是利用单幅图象中物体表面的明暗变化来恢复其表面三维形状 .为了使人们对 SFS研究现状及求解 SFS问题的各种算法的优缺点有个概略了解 ,首先介绍了求解传统 SFS问题的 4类方法中几个典型算法的基本原理及求解方法 ,并给出了实验结果 ,然后从算法解的唯一性、对真解的逼近程度、求解效率及适用范围等方面对这 4类算法进行了比较和评价 .

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.