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Consistent Segment-wise Matching with Multi-Layer Graphs

Taiwei Wang, David George, Yu-kun Lai, Xianghua Xie Orcid Logo, Gary Tam

International Conference on Geometric Modeling and Processing

Swansea University Author: Xianghua Xie Orcid Logo

Abstract

Segment-wise matching is an important research problem that supports higher-level understanding ofshapes in geometry processing. Many existing segment-wise matching techniques assume perfect input seg-mentation, and would suffer from imperfect or over-segmented input. To handle this shortcoming, we...

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Published in: International Conference on Geometric Modeling and Processing
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Online Access: http://www.eguk.org.uk/CGVC2018/programme.html
URI: https://cronfa.swan.ac.uk/Record/cronfa49120
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first_indexed 2019-03-05T20:00:05Z
last_indexed 2020-11-03T04:00:41Z
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spelling 2020-11-02T09:41:57.6247955 v2 49120 2019-03-05 Consistent Segment-wise Matching with Multi-Layer Graphs b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2019-03-05 SCS Segment-wise matching is an important research problem that supports higher-level understanding ofshapes in geometry processing. Many existing segment-wise matching techniques assume perfect input seg-mentation, and would suffer from imperfect or over-segmented input. To handle this shortcoming, we proposemulti-layer graphs (MLGs) to represent possible arrangements of partially merged segments of input shapes.We then adapt the diffusion pruning technique on the MLGs to find consistent segment-wise matching. Toobtain high quality matching, we develop a voting step to find hierarchically consistent correspondences asfinal output. We evaluate our technique with both qualitative and quantitative experiments on both man-made and deformable shapes. Experimental results demonstrate the effectiveness of our technique whencompared to two state-of-the-art methods. Other International Conference on Geometric Modeling and Processing 0 0 0 0001-01-01 http://www.eguk.org.uk/CGVC2018/programme.html COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2020-11-02T09:41:57.6247955 2019-03-05T12:52:42.1824484 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Taiwei Wang 1 David George 2 Yu-kun Lai 3 Xianghua Xie 0000-0002-2701-8660 4 Gary Tam 5
title Consistent Segment-wise Matching with Multi-Layer Graphs
spellingShingle Consistent Segment-wise Matching with Multi-Layer Graphs
Xianghua Xie
title_short Consistent Segment-wise Matching with Multi-Layer Graphs
title_full Consistent Segment-wise Matching with Multi-Layer Graphs
title_fullStr Consistent Segment-wise Matching with Multi-Layer Graphs
title_full_unstemmed Consistent Segment-wise Matching with Multi-Layer Graphs
title_sort Consistent Segment-wise Matching with Multi-Layer Graphs
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
author Xianghua Xie
author2 Taiwei Wang
David George
Yu-kun Lai
Xianghua Xie
Gary Tam
format Other
container_title International Conference on Geometric Modeling and Processing
institution Swansea University
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://www.eguk.org.uk/CGVC2018/programme.html
document_store_str 0
active_str 0
description Segment-wise matching is an important research problem that supports higher-level understanding ofshapes in geometry processing. Many existing segment-wise matching techniques assume perfect input seg-mentation, and would suffer from imperfect or over-segmented input. To handle this shortcoming, we proposemulti-layer graphs (MLGs) to represent possible arrangements of partially merged segments of input shapes.We then adapt the diffusion pruning technique on the MLGs to find consistent segment-wise matching. Toobtain high quality matching, we develop a voting step to find hierarchically consistent correspondences asfinal output. We evaluate our technique with both qualitative and quantitative experiments on both man-made and deformable shapes. Experimental results demonstrate the effectiveness of our technique whencompared to two state-of-the-art methods.
published_date 0001-01-01T03:59:54Z
_version_ 1763753060630265856
score 11.03559

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