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Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster) / Taiwei Wang; David George; Yu-kun Lai; Xianghua Xie; Gary Tam

International Conference on Geometric Modeling and Processing

Swansea University Author: Xie, Xianghua

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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spelling 2019-06-13T16:42:58Z v2 49120 2019-03-05 Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster) Xianghua Xie Xianghua Xie true 0000-0002-2701-8660 false b334d40963c7a2f435f06d2c26c74e11 53b7e8cec1e3c035df428f36f80bdea5 ulOdsUw0nzyNlMFzZoDyVp320YwKTXZRCaAvm14NMEw= 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 of Science Computer Science CSCI SCS Visual Computing None 2019-06-13T16:42:58Z 2019-03-05T12:52:42Z College of Science Computer Science Taiwei Wang 1 David George 2 Yu-kun Lai 3 Xianghua Xie 4 Gary Tam 5
title Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
spellingShingle Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
Xie, Xianghua
title_short Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
title_full Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
title_fullStr Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
title_full_unstemmed Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
title_sort Consistent Segment-wise Matching with Multi-Layer Graphs (CGVC2018 Poster)
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xie, Xianghua
author Xie, Xianghua
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 College of Science
hierarchytype
hierarchy_top_id collegeofscience
hierarchy_top_title College of Science
hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
url http://www.eguk.org.uk/CGVC2018/programme.html
document_store_str 0
active_str 1
researchgroup_str Visual Computing
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 0001-01-01T05:11:21Z
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score 10.847208