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Authors: Dena Bazazian ; Josep R. Casas and Javier Ruiz-Hidalgo

Affiliation: Universitat Politècnica de Catalunya, Spain

ISBN: 978-989-758-225-7

Keyword(s): Edge extraction, Multi-scale, Segmentation, Unorganized Point Cloud.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Segmentation and Grouping

Abstract: Edge extraction has attracted a lot of attention in computer vision. The accuracy of extracting edges in point clouds can be a significant asset for a variety of engineering scenarios. To address these issues, we propose a segmentation-based multi-scale edge extraction technique. In this approach, different regions of a point cloud are segmented by a global analysis according to the geodesic distance. Afterwards, a multi-scale operator is defined according to local neighborhoods. Thereupon, by applying this operator at multiple scales of the point cloud, the persistence of features is determined. We illustrate the proposed method by computing a feature weight that measures the likelihood of a point to be an edge, then detects the edge points based on that value at both global and local scales. Moreover, we evaluate quantitatively and qualitatively our method. Experimental results show that the proposed approach achieves a superior accuracy. Furthermore, we demonstrate the robustness o f our approach in noisier real-world datasets. (More)

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Paper citation in several formats:
Bazazian D., R. Casas J. and Ruiz-Hidalgo J. (2017). Segmentation-based Multi-scale Edge Extraction to Measure the Persistence of Features in Unorganized Point Clouds.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 317-325. DOI: 10.5220/0006092503170325

@conference{visapp17,
author={Dena Bazazian and Josep {R. Casas} and Javier Ruiz{-}Hidalgo},
title={Segmentation-based Multi-scale Edge Extraction to Measure the Persistence of Features in Unorganized Point Clouds},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={317-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006092503170325},
isbn={978-989-758-225-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Segmentation-based Multi-scale Edge Extraction to Measure the Persistence of Features in Unorganized Point Clouds
SN - 978-989-758-225-7
AU - Bazazian D.
AU - R. Casas J.
AU - Ruiz-Hidalgo J.
PY - 2017
SP - 317
EP - 325
DO - 10.5220/0006092503170325

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