A probabilistic approach for 3D shape retrieval by characteristic views

被引:15
|
作者
Mahmoudi, Said
Daoudi, Mohamed
机构
[1] Fac Engn, Dept Comp Sci, B-7000 Mons, Belgium
[2] GET TELECOM Lille1, LIFL, CNRS, USTL UMR 8022, F-59658 Villeneuve Dascq, France
关键词
partial shape retrieval; Curvature Scale Space; M-tree; 3D indexing; characteristic views; Bayesian voting;
D O I
10.1016/j.patrec.2007.04.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This work addresses the problem of 3D models retrieval and recognition using two-dimensional shape representation of 3D objects. However, the human perception of shapes is based on visual parts of objects, where a single significant visual part is sufficient to recognize the whole object. In this paper we present a shape similarity system based on the correspondence of visual 2D parts. These parts are obtained by a shape segmentation approach using the Curvature Scale Space (CSS) descriptor in order to solve scale problems. We propose to combine this partial search method with a probabilistic approach. Finally, we propose a 3D search engine based on 3D models characteristic views and a probabilistic Bayesian voting approach. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:1705 / 1718
页数:14
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