JOURNAL ARTICLE

SHREC 16 Partial Matching of Deformable Shapes

Cosmo, LucaRodola, EmanueleBronstein, MichaelTorsello, AndreaCremers, DanielSahillioğlu, Yusuf

Year: 2016 Journal:   Spectrum Research Repository (Concordia University)   Publisher: Concordia University

Abstract

Matching deformable 3D shapes under partiality transformations is a challenging problem that has received limited focus in the computer vision and graphics communities. With this benchmark, we explore and thoroughly investigate the robustness of existing matching methods in this challenging task. Participants are asked to provide a point-to-point correspondence (either sparse or dense) between deformable shapes undergoing different kinds of partiality transformations, resulting in a total of 400 matching problems to be solved for each method – making this benchmark the biggest and most challenging of its kind. Five matching algorithms were evaluated in the contest; this paper presents the details of the dataset, the adopted evaluation measures, and shows thorough comparisons among all competing methods.

Keywords:
Robustness (evolution) Matching (statistics) Focus (optics) Computer graphics Benchmark (surveying) Pattern recognition (psychology)

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Topics

3D Shape Modeling and Analysis
Physical Sciences →  Engineering →  Computational Mechanics
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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