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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
Published:
Online Access: http://www.eguk.org.uk/CGVC2018/programme.html
URI: https://cronfa.swan.ac.uk/Record/cronfa49120
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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 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.
College: College of Science