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Research Papers

An Enhanced Graph Representation and Heuristic Tabu Search Approach for Flexible and Efficient 3D Shape Matching

[+] Author and Article Information
Yuhang Sun

School of Mechanical Science and Engineering,
Huazhong University of Science and Technology,
Wuhan 430074, China
e-mail: sunyh@mail.hust.edu.cn

Liping Chen

School of Mechanical Science and Engineering,
Huazhong University of Science and Technology,
Wuhan 430074, China
e-mail: chenlp@mail.hust.edu.cn

Yunbao Huang

School of Mechanical Science and Engineering,
Huazhong University of Science and Technology,
Wuhan 430074, China
e-mail: huangyb@mail.hust.edu.cn

Sha Wan

School of Mechanical Science and Engineering,
Huazhong University of Science and Technology,
Wuhan 430074, China
e-mail: ws_shiner@qq.com

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received February 1, 2014; final manuscript received May 3, 2014; published online June 2, 2014. Assoc. Editor: Charlie C. L. Wang.

J. Comput. Inf. Sci. Eng 14(3), 031009 (Jun 02, 2014) (10 pages) Paper No: JCISE-14-1037; doi: 10.1115/1.4027616 History: Received February 01, 2014; Revised May 03, 2014

3D shape matching is widely used in engineering design for model retrieval, shape similarity assessment or collaborative development. In this paper, an enhanced graph representation and heuristic tabu search based approach is presented to enable flexible and efficient 3D shape matching. The core idea includes (1) generic shape features are recognized from boundary representation (B-rep) of 3D shape as many as possible to incorporate domain design knowledge, (2) an enhanced graph representation of 3D shape is constructed by mixing faces of B-rep and recognized features, to achieve meaningful matching results at low-level of faces or high-level of features satisfying various design intents, and (3) a tabu list of possible improper matches is built to reduce the search space so that the optimal result can be efficiently obtained. Finally, Two examples are demonstrated to show that both two levels of 3D shape matching results can be efficiently obtained for various design intents in the engineering applications, only not more than 18% computation time is required when compared with a typical shape matching method, and it takes only 20 s when the number of matching nodes is more than 460.

Copyright © 2014 by ASME
Topics: Shapes
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Figures

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Fig. 1

3D shape matching for efficient structure design

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Fig. 2

Examples of isolated generic shape features

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Fig. 3

Examples of hybrid generic shape features

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Fig. 4

Examples of generic shape feature patterns

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Fig. 5

Generic shape feature recognition

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Fig. 6

Faces coding for graph attributes computing

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Fig. 7

Edges coding for graph attributes computing

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Fig. 8

Features coding for graph attributes computing

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Fig. 9

Enhanced graph representation of a 3D shape part

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Fig. 10

Flow chart of tabu search based heuristic graph matching for efficient 3D shape matching

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Fig. 11

Node relationships in enhanced graph representation

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Fig. 12

3D shape matching based on enhanced graph representation and heuristic tabu search

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Fig. 13

Flexible 3D shape matching for parts collaborative design

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Fig. 14

Flexible 3D shape matching for parts structure retrieval

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Fig. 15

Flexible 3D shape matching for complex parts redesign

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Fig. 16

Graph matching time comparison

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