loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Faisal Azhar ; Stephen Pollard and Guy Adams

Affiliation: HP Labs, Bristol and U.K.

Keyword(s): Gaussian Curvature, 3D Registration, Matching, Point Cloud, Hash Table.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Pattern Recognition ; Robotics ; Shape Representation and Matching ; Software Engineering

Abstract: We propose a novel Gaussian Curvature (GC) based criterion to discard false point correspondences within the RANdom SAmple Matching (RANSAM) framework to improve the 3D registration. The RANSAM method is used to find a point pair correspondence match between two surfaces and GC is used to verify whether this point pair is a correct (similar curvatures) or false (dissimilar curvatures) match. The point pairs which pass the curvature test are used to compute a transformation which aligns the two overlapping surfaces. The results on shape alignment benchmarks show improved accuracy of the GRANSAM versus RANSAM and six other registration methods while maintaining efficiency.

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 3.145.111.183

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:
Azhar, F.; Pollard, S. and Adams, G. (2019). Gaussian Curvature Criterion based Random Sample Matching for Improved 3D Registration. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 319-325. DOI: 10.5220/0007343403190325

@conference{visapp19,
author={Faisal Azhar. and Stephen Pollard. and Guy Adams.},
title={Gaussian Curvature Criterion based Random Sample Matching for Improved 3D Registration},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={319-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007343403190325},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Gaussian Curvature Criterion based Random Sample Matching for Improved 3D Registration
SN - 978-989-758-354-4
IS - 2184-4321
AU - Azhar, F.
AU - Pollard, S.
AU - Adams, G.
PY - 2019
SP - 319
EP - 325
DO - 10.5220/0007343403190325
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic