MATE： A Visual Based 3D Shape Descriptor  

作　　者：LENG Biao QIN Zheng CAO Xiaoman WEI Tao ZHANG Zhuxi 

机构地区：[1]Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China [2]School of Software, Tsinghua University, Beijing 100084, China [3]General Logistics Research Institute, Beijing 100071, China

出　　处：《Chinese Journal of Electronics》2009年第2期291-296,共6页电子学报（英文版）

摘　　要：Since 3D models have been widely applied in many research areas, the techniques for content-based 3D model retrieval become necessary. In this paper, a novel visual based 3D shape descriptor called MATE is proposed. A modified Principal component analysis （PCA） method for model normalization is presented at first. Secondly, a new Adjacent angle distance Fourier （AADF） algorithm is proposed. Then the original two-viewed Dbuffer method is presented to extract characteristics of projected images. Finally, based on the modified PCA method, the shape descriptor MATE is proposed by combining AADF, Tchebichef and two-viewed Dhuffer. Experimental results show that the descriptor MATE provides better retrieval performance than the best current descriptors.

关 键 词：3D model retrieval Shape descriptor Visual similarity. 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TP391.41[自动化与计算机技术—计算机科学与技术]