Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms

T. Ridene; F. Goulette; S. Chendeb

doi:10.5194/isprsarchives-XL-2-W2-59-2013

Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms

T. Ridene
, F. Goulette
, S. Chendeb

Université Paris 8
Mines ParisTech

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

Résumé

The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

langue originale	Anglais
Pages (de - à)	59-64
Nombre de pages	6
journal	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume	XL-2/W2
Les DOIs	https://doi.org/10.5194/isprsarchives-XL-2-W2-59-2013
état	Publié - 1 janv. 2013
Modification externe	Oui
Evénement	ISPRS 8th 3D GeoInfo Conference and WG II/2 Workshop - Istanbul, Turquie Durée: 27 nov. 2013 → 29 nov. 2013

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10.5194/isprsarchives-XL-2-W2-59-2013

Contient cette citation

@article{2c2e1f0bfe844a56a23e2ea82cd1cd24,

title = "Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms",

abstract = "The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.",

keywords = "3D point clouds, Binary, DSM, FBQ-evaluation, Fuzzy, ICP, MMS",

author = "T. Ridene and F. Goulette and S. Chendeb",

year = "2013",

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doi = "10.5194/isprsarchives-XL-2-W2-59-2013",

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journal = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives",

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Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms. / Ridene, T.; Goulette, F.; Chendeb, S.
Dans: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol XL-2/W2, 01.01.2013, p. 59-64.

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

TY - JOUR

T1 - Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms

AU - Ridene, T.

AU - Goulette, F.

AU - Chendeb, S.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

AB - The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

KW - 3D point clouds

KW - Binary

KW - DSM

KW - FBQ-evaluation

KW - Fuzzy

KW - ICP

KW - MMS

U2 - 10.5194/isprsarchives-XL-2-W2-59-2013

DO - 10.5194/isprsarchives-XL-2-W2-59-2013

M3 - Conference article

AN - SCOPUS:84906993537

SN - 1682-1750

VL - XL-2/W2

SP - 59

EP - 64

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

T2 - ISPRS 8th 3D GeoInfo Conference and WG II/2 Workshop

Y2 - 27 November 2013 through 29 November 2013

ER -

Feature-based quality evaluation of 3D point clouds -Study of the performance of 3D registration algorithms

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