鉴于非刚体的运动分析业已成为计算机视觉中的一个重要应用领域，为了使人们对该领域的研究现状有个概略了解，首先基于微分几何上的高斯曲率变化，对不同非刚性物体(简称非刚体)进行了分类，指出可把所有运动物体分为8类；然后对该领域目前存在的各种算法进行归纳总结，指出可把它们分为基于特征的方法和基于形状模型的方法两大类，并讨论了这两类方法各自的优势和不足之处；最后分析了该领域面临的困难，并展望了它未来可能的发展方向。同时指出，非刚性运动的视觉分析虽是一个蓬勃发展的研究领域，但目前仍处于初期阶段，因为近年来所进行的工作只是涉及众多困难问题中的较少部分，而且现有的各种模型和算法都还很不完善，人们还远未找到解决非刚性运动视觉分析问题的最有效的途径，但已有成果表明，一些相关研究领域，如语音识别和计算机图形学将会对该领域的发展提供帮助。

The visual analysis of non rigid motion is becoming a major area in computer vision. A classification of non rigid motion performed by objects on various degrees of non rigidity is elucidated in this paper according to the curvature changes of the objects, indicating that an 8 class scheme can cover all the objects from rigidity to high non rigidity. A large number of existing approaches in this area are surveyed and divided into two major categories: feature based methods and model based methods, and the advantages and disadvantages of the two classes are discussed respectively. The last section of this paper expatiates on the difficulties confronted by non rigid motion analysis and expects its possible future directions. Non rigid motion analysis is a burgeoning research area but still in its early development. The available body of research has begun to make inroads into only a few of the many difficult problems. Most of the extant models are far from perfect and people are far from a general solution to this problem. Some related research fields, such as speech recognition and computer graphics, may benefit this field.