Visibility estimation in point clouds with variable density

P. Biasutti; A. Bugeau; J. F. Aujol; M. Brédif

doi:10.5220/0007308600270035

Visibility estimation in point clouds with variable density

P. Biasutti
, A. Bugeau
, J. F. Aujol
, M. Brédif

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Editors	Andreas Kerren, Christophe Hurter, Jose Braz
Publisher	SciTePress
Pages	27-35
Number of pages	9
ISBN (Electronic)	9789897583544
DOIs	https://doi.org/10.5220/0007308600270035
Publication status	Published - 1 Jan 2019
Externally published	Yes
Event	14th International Conference on Computer Vision Theory and Applications, VISAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019 - Prague, Czech Republic Duration: 25 Feb 2019 → 27 Feb 2019

Publication series

Name	VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Volume	4

Conference

Conference	14th International Conference on Computer Vision Theory and Applications, VISAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019
Country/Territory	Czech Republic
City	Prague
Period	25/02/19 → 27/02/19

Keywords

3D Point Cloud
Benchmark
Dataset
LiDAR
Visibility
Visualization

Access to Document

10.5220/0007308600270035

Cite this

Biasutti, P., Bugeau, A., Aujol, J. F., & Brédif, M. (2019). Visibility estimation in point clouds with variable density. In A. Kerren, C. Hurter, & J. Braz (Eds.), VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 27-35). (VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications; Vol. 4). SciTePress. https://doi.org/10.5220/0007308600270035

Biasutti, P. ; Bugeau, A. ; Aujol, J. F. et al. / Visibility estimation in point clouds with variable density. VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. editor / Andreas Kerren ; Christophe Hurter ; Jose Braz. SciTePress, 2019. pp. 27-35 (VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications).

@inproceedings{4e25eff5760848278f1bdc13adbe7d70,

title = "Visibility estimation in point clouds with variable density",

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.",

keywords = "3D Point Cloud, Benchmark, Dataset, LiDAR, Visibility, Visualization",

author = "P. Biasutti and A. Bugeau and Aujol, \{J. F.\} and M. Br{\'e}dif",

note = "Publisher Copyright: Copyright {\textcopyright} 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved; 14th International Conference on Computer Vision Theory and Applications, VISAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019 ; Conference date: 25-02-2019 Through 27-02-2019",

year = "2019",

month = jan,

day = "1",

doi = "10.5220/0007308600270035",

language = "English",

series = "VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",

publisher = "SciTePress",

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booktitle = "VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",

}

Biasutti, P, Bugeau, A, Aujol, JF & Brédif, M 2019, Visibility estimation in point clouds with variable density. in A Kerren, C Hurter & J Braz (eds), VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, vol. 4, SciTePress, pp. 27-35, 14th International Conference on Computer Vision Theory and Applications, VISAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Prague, Czech Republic, 25/02/19. https://doi.org/10.5220/0007308600270035

Visibility estimation in point clouds with variable density. / Biasutti, P.; Bugeau, A.; Aujol, J. F. et al.
VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. ed. / Andreas Kerren; Christophe Hurter; Jose Braz. SciTePress, 2019. p. 27-35 (VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Visibility estimation in point clouds with variable density

AU - Biasutti, P.

AU - Bugeau, A.

AU - Aujol, J. F.

AU - Brédif, M.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - 3D Point Cloud

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KW - Dataset

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KW - Visibility

KW - Visualization

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DO - 10.5220/0007308600270035

M3 - Conference contribution

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BT - VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

A2 - Kerren, Andreas

A2 - Hurter, Christophe

A2 - Braz, Jose

PB - SciTePress

T2 - 14th International Conference on Computer Vision Theory and Applications, VISAPP 2019 - Part of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019

Y2 - 25 February 2019 through 27 February 2019

ER -

Biasutti P, Bugeau A, Aujol JF, Brédif M. Visibility estimation in point clouds with variable density. In Kerren A, Hurter C, Braz J, editors, VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SciTePress. 2019. p. 27-35. (VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications). doi: 10.5220/0007308600270035

Visibility estimation in point clouds with variable density

Abstract

Publication series

Conference

Keywords

Access to Document

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Cite this