loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Giampaolo Pagnutti and Pietro Zanuttigh

Affiliation: University of Padova, Italy

ISBN: 978-989-758-175-5

ISSN: 2184-4321

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 proposed method provides an accurate and reliable scene segmentation. (More)

PDF ImageFull Text

Download
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 3.235.238.217

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 - Volume 4 VISAPP: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, ISSN 2184-4321, 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 - Volume 4 VISAPP: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005672700930100},
isbn={978-989-758-175-5},
}

TY - CONF

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.