3D Model Retrieval Using Multiple Features and Manifold Ranking

被引:0
作者
Hsieh, Cheng-Ta [1 ]
Han, Chin-Chuan [2 ]
Shih, Jau-Ling [3 ]
Lee, Chang-Hsing [3 ]
Fan, Kuo-Chin [1 ]
机构
[1] Natl Cent Univ, Dept Comp Sci & Informat Engn, Taoyuan, Taiwan
[2] Natl United Univ, Dept Comp Sci & Informat Engn, Miaoli, Taiwan
[3] Chung Hua Univ, Dept Comp Sci & Informat Engn, Hsinchu, Taiwan
来源
2015 8TH INTERNATIONAL CONFERENCE ON UBI-MEDIA COMPUTING (UMEDIA) CONFERENCE PROCEEDINGS | 2015年
关键词
3D model retrieval; Manifold ranking; multiple features; adjacency graph; distance metric;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The demand of 3D object retrieval became urgent according to the widely use of 3D printer. In this paper, a 3D object retrieval method is proposed using multiple features and manifold ranking. Five descriptors are concatenated to be a new feature vector of length 792 for 3D object retrieval. They are angular radial transform-based elevation descriptor(ART-ED), principal plane descriptor(PPD), 3D-angular radial transform(3D-ART), shell grid descriptor(SGD), and Grid Distance 2 (GD2). Next, a manifold ranking method is used to re-rank the retrieved results. In addition, various distance metrics are addressed in the construction of manifold graph. The retrieval results on a benchmark dataset SHREC-W have been reported to show the feasibility of the proposed method.
引用
收藏
页码:7 / 10
页数:4
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