loading
Documents

Research.Publish.Connect.

Paper

Authors: P. Biasutti 1 ; A. Bugeau 2 ; J-F. Aujol 3 and M. Brédif 4

Affiliations: 1 Univ. Bordeaux, LaBRI, INP, CNRS, UMR 5800, F-33400 Talence, France, Univ. Bordeaux, IMB, INP, CNRS, UMR 5251, F-33400 Talence, France, Univ. Paris-Est, LASTIG GEOVIS, IGN, ENSG, F-94160 Saint-Mandé and France ; 2 Univ. Bordeaux, LaBRI, INP, CNRS, UMR 5800, F-33400 Talence and France ; 3 Univ. Bordeaux, IMB, INP, CNRS, UMR 5251, F-33400 Talence and France ; 4 Univ. Paris-Est, LASTIG GEOVIS, IGN, ENSG, F-94160 Saint-Mandé and France

ISBN: 978-989-758-354-4

ISSN: 2184-4321

Keyword(s): 3D Point Cloud, Visibility, Visualization, LiDAR, Dataset, Benchmark.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Device Calibration, Characterization and Modeling ; Geometry and Modeling ; Image Enhancement and Restoration ; Image Formation and Preprocessing ; Image-Based Modeling ; Multimodal and Multi-Sensor Models of Image Formation ; Pattern Recognition ; Robotics ; Software Engineering

Abstract: Estimating visibility in point clouds has many applications such as visualization, surface reconstruction and scene analysis through fusion of LiDAR point clouds and images. However, most current works rely on methods that require strong assumptions on the point cloud density, which are not valid for LiDAR point clouds acquired from mobile mapping systems, leading to low quality of point visibility estimations. This work presents a novel approach for the estimation of the visibility of a point cloud from a viewpoint. The method is designed to be fully automatic and it makes no assumption on the point cloud density. The visibility of each point is estimated by considering its screen-space neighborhood from the given viewpoint. Our results show that our approach succeeds better in estimating the visibility on real-world data acquired using LiDAR scanners. We evaluate our approach by comparing its results to a new manually annotated dataset, which we make available online.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.153.39.7

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Biasutti, P.; Bugeau, A.; Aujol, J. and Brédif, M. (2019). Visibility Estimation in Point Clouds with Variable Density.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, ISBN 978-989-758-354-4, ISSN 2184-4321, pages 27-35. DOI: 10.5220/0007308600270035

@conference{visapp19,
author={P. Biasutti. and A. Bugeau. and J{-}F. Aujol. and M. Brédif.},
title={Visibility Estimation in Point Clouds with Variable Density},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,},
year={2019},
pages={27-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007308600270035},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,
TI - Visibility Estimation in Point Clouds with Variable Density
SN - 978-989-758-354-4
AU - Biasutti, P.
AU - Bugeau, A.
AU - Aujol, J.
AU - Brédif, M.
PY - 2019
SP - 27
EP - 35
DO - 10.5220/0007308600270035

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.