Abstract: In range image processing，the research on modeling and recognition for scattered data points is more universality，and it has became the focus of attention in computer vision.For the characteristic of discrete and irregular 3D data points，the existent problems of superquadric parametric fitting，multi-object scene segmenting and parts recognizing are analyzed through investigating the theory and method of superquadric modeling，segmentation and recognition，including the application of evolutionary computation in 3D modeling and recognition.It is proposed to enhance the capability of superquadric representation and to make use of the basic elements of superquadrics for scene modeling and segmenting in future work，and it also is put forward to bring the theory of swarm parallel evolutionary and relational match into the superquadric modeling and recognition.The research aims to explore a scheme of 3D modeling and recognition which is effective and practicable.

Key words: superquadric modeling, range image segmentation, parts recognition, evolutionary computation

摘要： 在深度图像处理中，针对散乱的数据点进行三维建模与识别研究更具一般性，它是计算机视觉领域中的一个研究热点。通过阐述超二次曲面建模、分割与识别理论和方法的研究进展，以及演化计算在三维建模与识别中的应用，针对离散不规则三维数据点的特性，分析了超二次曲面参数拟合、多物体场景分割、部件识别存在的问题，提出进一步研究扩展超二次曲面的表达能力，利用的超二次曲面作为基元部件对场景进行建模与分割，并将群体并行演化以及关系匹配理论引入到超二次曲面建模与识别中，其目的在于探求一种高效实用的三维建模与识别方案。

关键词: 超二次曲面建模, 深度图像分割, 部件识别, 演化计算