基于内容的三维模型检索综述

对当前基于内容的三维模型检索技术的国际研究现状及进展进行了广泛而深入的综述．探讨和分析了基于内容的三维模型检索技术的系统框架及其关键方法，重点介绍其中的模型坐标标准化、特征提取与索引、相似性匹配、查询方式与用户界面等方面的基本内容，并进行了适当分类．分析总结了现有的基于内容的三维模型检索系统及搜索引擎的典型实例．最后，对现有研究中存在的难点问题及其未来的发展方向进行了展望．  

形状匹配综述

本文对形状匹配的方法进行了回顾，介绍了一些形状表示方法，其中主要是形状简化的方法，形状匹配的方法可以分为基于各种变换不变量的形状匹配方法和基于局部特征的形状匹配方法，并根据这一分类介绍了很多有代表性的匹配方法。  

一种快速的复杂多边形匹配算法

提出了一种能够快速进行复杂形状多边形匹配的算法，该算法基于正切空间表示，先对复杂多边形进行离散曲线演化，再将得到的简化多边形分为一系列最大凸/凹弧线，并选择每段最大凸弧线的起点作为匹配的起始点进行匹配。实验结果证明该算法不但能够对复杂多边形快速而精确的匹配，而且具有不受噪声影响的优点。  

A survey of content based 3D shape retrieval methods

Recent developments in techniques for modeling, digitizing and visualizing 3D shapes has led to an explosion in the number of available 3D models on the Internet and in domain-specific databases. This has led to the development of 3D shape retrieval systems that, given a query object, retrieve similar 3D objects. For visualization, 3D shapes are often represented as a surface, in particular polygonal meshes, for example in VRML format. Often these models contain holes, intersecting polygons, are not manifold, and do not enclose a volume unambiguously. On the contrary, 3D volume models, such as solid models produced by CAD systems, or voxels models, enclose a volume properly. This paper surveys the literature on methods for content based 3D retrieval, taking into account the applicability to surface models as well as to volume models. The methods are evaluated with respect to several requirements of content based 3D shape retrieval, such as: (1) shape representation requirements, (2) properties of dissimilarity measures, (3) efficiency, (4) discrimination abilities, (5) ability to perform partial matching, (6) robustness, and (7) necessity of pose normalization. Finally, the advantages and limitations of the several approaches in content based 3D shape retrieval are discussed.

基于Hausdorff距离的2D形状匹配改进算法

在计算机视觉检测中，常常需要将两幅图象在空间上配准，以便进行后续的检测过程，该文提出将Ｈａｕｓｄｏｒｆｆ距离作为物体轮廓相似性的测度，并用遗传算法进行最佳形状匹配的快速搜索，根据遗传搜索的结果再进行一次线性搜索，从而提高解的精度，实验结果证明了该方法能快速，精确地对两幅２Ｄ形状进行匹配。  

一种基于部件空间分布的三维模型检索方法

三维形状分析是三维模型检索的关键问题.提出一种基于三维模型部件空间分布的形状特征描述方法.此方法的主要思想是依据认知心理学的理论,在描述对象形状时强调它的结构属性.首先将三维模型分割为若干个组成部件,每个部件用一个曲面片表示,然后采用曲面片的质心位置、面积占总面积的百分比的组合作为部件特征,最后将满足指定条件的部件特征的集合作为三维模型的形状特征.基于这一特征表示,给出了一种三维模型检索方法.该方法具有受模型精度和连通性影响较小、相似性度量的计算速度较快的优点.实验结果验证了该检索方法的有效性.  

一种碎纸自动拼接中的形状匹配方法

碎纸自动拼接技术是图像处理与模式识别领域中的一个较新但是很典型的应用，它是通过扫描和图像提取技术获取一组碎纸片的形状、颜色等信息，然后利用计算机进行相应的处理从而实现对这些碎纸片的全自动或半自动拼接还原。碎纸自动拼接过程一般包括图像预处理和匹配两个主要步骤。形状匹配是碎纸自动拼接过程中的关键技术，但是至今为止，没有很成熟的方法应用于相关工作中。该文给出一种从提取碎纸片轮廓线出发，通过边界准则和面积准则来判断两个轮廓是否匹配来达到碎纸拼接目的的方法，实现了基于计算机辅助的碎纸自动拼接还原。  

An approach to computer-supported cartooning

An approach to computer-supported cartooning is described that aims at optimizing the image-related working process by introducing computer-support in the drawing and painting stages of traditional cartoon production, in particular, allowing automatic coloring of a sequence of digitized images. This is achieved by using a shape-matching algorithm to evaluate the similarity of image regions and by performing an optimum region assignment to identify the corresponding ones and propagate the color information through the image sequence. In order to maintain the use of traditional drawing tools, the first step in the proposed system architecture is the processing of scanned animators' drawings to enhance their quality and extract meaningful information. Two different system modules allow either manual coloring of images or computer-assisted automatic painting of an image sequence. Additional modules allow the construction of a vector representation for the images, the generation of in-betweens, and the composing of each cartoon frame. The first stages of the system's architecture — image preprocessing, painting and vectorization — are presented. Special emphasis is placed on the fundamental ideas behind the computer-assisted painting and vectorization steps. The competitiveness of the approach, which requires no special hardware or high-performance workstation, is shown.  

基于多尺度形状分析的叶形识别系统

叶形自动识别系统使用一种改进了的边界跟踪算法检测叶片边界,应用多尺度形状分析技术有效地提取出规范锯齿长度和曲率尺度空间图像极大值点集两个曲率特征。综合叶片的离心率、似圆率和这两个边界曲率特征来检索叶片数据库,进行形状匹配,实现叶片自动分类。实验结果表明,该系统使用的技术能大幅提高叶形识别的精确率和检索率。