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Authors: Manuel Frei and Simon Winkelbach

Affiliation: TU Braunschweig, Germany

Keyword(s): Surface Registration, Scan Alignment, Self-similarity, Surface-based Feature, RANSAC, RANSAM, 3D Puzzle.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Geometry and Modeling ; Image and Video Analysis ; Image-Based Modeling ; Pattern Recognition ; Shape Representation and Matching ; Software Engineering

Abstract: In the last 20 years many approaches for the registration and localization of surfaces were developed. Most of them generate solutions by minimizing point distances or maximizing contact areas between surface points. Other algorithms try to detect corresponding points on the two surfaces by searching for points with same features and align them. However, aligning and localizing self-similar surfaces or surfaces having large regions with approximately constant curvature is still a complex problem. In this paper a new algorithm for registration and matching of surfaces is introduced, which extends an approach maximizing the contact area between the surfaces by surface-based dissimilarity features and thereby solves the problem of registering the problematic surfaces described above. Our evaluation shows the great potential of our approach regarding efficiency, accuracy and robustness for various applications like scan alignment, pottery assembly or bone reduction.

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Paper citation in several formats:
Frei, M. and Winkelbach, S. (2014). Shape Similarity based Surface Registration. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP; ISBN 978-989-758-003-1; ISSN 2184-4321, SciTePress, pages 359-366. DOI: 10.5220/0004733603590366

@conference{visapp14,
author={Manuel Frei. and Simon Winkelbach.},
title={Shape Similarity based Surface Registration},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP},
year={2014},
pages={359-366},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004733603590366},
isbn={978-989-758-003-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP
TI - Shape Similarity based Surface Registration
SN - 978-989-758-003-1
IS - 2184-4321
AU - Frei, M.
AU - Winkelbach, S.
PY - 2014
SP - 359
EP - 366
DO - 10.5220/0004733603590366
PB - SciTePress