loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Andrés Serna ; Beatriz Marcotegui ; François Goulette and Jean-Emmanuel Deschaud

Affiliation: MINES ParisTech, France

Keyword(s): 3D Database, Mobile Laser Scanner, Urban Analysis, Segmentation, Classification, Point-wise Evaluation.

Abstract: This paper describes a publicly available 3D database from the rueMadame, a street in the 6th Parisian district. Data have been acquired by the Mobile Laser Scanning (MLS) system L3D2 and correspond to a 160 m long street section. Annotation has been carried out in a manually assisted way. An initial annotation is obtained using an automatic segmentation algorithm. Then, a manual refinement is done and a label is assigned to each segmented object. Finally, a class is also manually assigned to each object. Available classes include facades, ground, cars, motorcycles, pedestrians, traffic signs, among others. The result is a list of (X, Y, Z, reflectance, label, class) points. Our aim is to offer, to the scientific community, a 3D manually labeled dataset for detection, segmentation and classification benchmarking. With respect to other databases available in the state of the art, this dataset has been exhaustively annotated in order to include all available objects and to allow point- wise comparison. (More)

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 3.15.228.171

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:
Serna, A.; Marcotegui, B.; Goulette, F. and Deschaud, J. (2014). Paris-rue-Madame Database - A 3D Mobile Laser Scanner Dataset for Benchmarking Urban Detection, Segmentation and Classification Methods. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014) - USA; ISBN 978-989-758-018-5; ISSN 2184-4313, SciTePress, pages 819-824. DOI: 10.5220/0004934808190824

@conference{usa14,
author={Andrés Serna. and Beatriz Marcotegui. and Fran\c{C}ois Goulette. and Jean{-}Emmanuel Deschaud.},
title={Paris-rue-Madame Database - A 3D Mobile Laser Scanner Dataset for Benchmarking Urban Detection, Segmentation and Classification Methods},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014) - USA},
year={2014},
pages={819-824},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004934808190824},
isbn={978-989-758-018-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014) - USA
TI - Paris-rue-Madame Database - A 3D Mobile Laser Scanner Dataset for Benchmarking Urban Detection, Segmentation and Classification Methods
SN - 978-989-758-018-5
IS - 2184-4313
AU - Serna, A.
AU - Marcotegui, B.
AU - Goulette, F.
AU - Deschaud, J.
PY - 2014
SP - 819
EP - 824
DO - 10.5220/0004934808190824
PB - SciTePress