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Point Cloud Structural Parts Extraction based on Segmentation Energy MinimizationTopics: Geometric Computing; Scene and Object Modeling; Surface Modeling

Keyword(s):Point Clouds, Level Set Methods, Minimal Surface Energy, Segmentation, Meshing.

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Ontology
Subjects/Areas/Topics:Computer Vision, Visualization and Computer Graphics
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Geometric Computing
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Geometry and Modeling
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Scene and Object Modeling
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Surface Modeling

Abstract: In this work we consider 3D point sets, which in a typical setting represent unorganized point clouds. Segmentation of these point sets requires first to single out structural components of the unknown surface discretely approximated by the point cloud. Structural components, in turn, are surface patches approximating unknown parts of elementary geometric structures, such as planes, ellipsoids, spheres and so on. The approach used is based on level set methods computing the moving front of the surface and tracing the interfaces between different parts of it. Level set methods are widely recognized to be one of the most efficient methods to segment both 2D images and 3D medical images. Level set methods for 3D segmentation have recently received an increasing interest. We contribute by proposing a novel approach for raw point sets. Based on the motion and distance functions of the level set we introduce four energy minimization models, which are used for segmentation, by considering an equal number of distance functions specified by geometric features. Finally we evaluate the proposed algorithm on point sets simulating unorganized point clouds.(More)

In this work we consider 3D point sets, which in a typical setting represent unorganized point clouds. Segmentation of these point sets requires first to single out structural components of the unknown surface discretely approximated by the point cloud. Structural components, in turn, are surface patches approximating unknown parts of elementary geometric structures, such as planes, ellipsoids, spheres and so on. The approach used is based on level set methods computing the moving front of the surface and tracing the interfaces between different parts of it. Level set methods are widely recognized to be one of the most efficient methods to segment both 2D images and 3D medical images. Level set methods for 3D segmentation have recently received an increasing interest. We contribute by proposing a novel approach for raw point sets. Based on the motion and distance functions of the level set we introduce four energy minimization models, which are used for segmentation, by considering an equal number of distance functions specified by geometric features. Finally we evaluate the proposed algorithm on point sets simulating unorganized point clouds.

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Cafaro, B.; Azimi, I.; Ntouskos, V.; Pirri, F. and Ruiz, M. (2015). Point Cloud Structural Parts Extraction based on Segmentation Energy Minimization.In Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) ISBN 978-989-758-087-1, pages 150-157. DOI: 10.5220/0005309301500157

@conference{grapp15, author={Bruno Cafaro. and Iman Azimi. and Valsamis Ntouskos. and Fiora Pirri. and Manuel Ruiz.}, title={Point Cloud Structural Parts Extraction based on Segmentation Energy Minimization}, booktitle={Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)}, year={2015}, pages={150-157}, publisher={SciTePress}, organization={INSTICC}, doi={10.5220/0005309301500157}, isbn={978-989-758-087-1}, }

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) TI - Point Cloud Structural Parts Extraction based on Segmentation Energy Minimization SN - 978-989-758-087-1 AU - Cafaro, B. AU - Azimi, I. AU - Ntouskos, V. AU - Pirri, F. AU - Ruiz, M. PY - 2015 SP - 150 EP - 157 DO - 10.5220/0005309301500157