loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Giampaolo Pagnutti and Pietro Zanuttigh

Affiliation: University of Padova, Italy

Keyword(s): Segmentation, Depth, Color, Kinect, NURBS.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: The recent introduction of consumer depth cameras has opened the way to novel segmentation approaches exploiting depth data together with the color information. This paper proposes a region merging segmentation scheme that jointly exploits the two clues. Firstly a set of multi-dimensional vectors is built considering the 3D spatial position, the surface orientation and the color data associated to each scene sample. Normalized cuts spectral clustering is applied to the obtained vectors in order to over-segment the scene into a large number of small segments. Then an iterative merging procedure is used to recombine the segments into the regions corresponding to the various objects and surfaces. The proposed algorithm tries to combine close compatible segments and uses a NURBS surface fitting scheme on the considered segments in order to understand if the regions candidate for the merging correspond to a single surface. The comparison with state-of-the-art methods shows how the propose d method provides an accurate and reliable scene segmentation. (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 3.145.66.104

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:
Pagnutti, G. and Zanuttigh, P. (2016). Joint Color and Depth Segmentation based on Region Merging and Surface Fitting. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 93-100. DOI: 10.5220/0005672700930100

@conference{visapp16,
author={Giampaolo Pagnutti. and Pietro Zanuttigh.},
title={Joint Color and Depth Segmentation based on Region Merging and Surface Fitting},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005672700930100},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - Joint Color and Depth Segmentation based on Region Merging and Surface Fitting
SN - 978-989-758-175-5
IS - 2184-4321
AU - Pagnutti, G.
AU - Zanuttigh, P.
PY - 2016
SP - 93
EP - 100
DO - 10.5220/0005672700930100
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