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Authors: Arnaud Boucher 1 ; Olivier Martinot 2 and Nicole Vincent 3

Affiliations: 1 University of Burgundy, France ; 2 Alcatel Lucent, France ; 3 Paris Descartes University, France

ISBN: 978-989-758-091-8

Keyword(s): Video Segmentation, Depth+RGB Data, Confidence Estimation.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Camera Networks and Vision ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction ; Image and Video Analysis ; Segmentation and Grouping

Abstract: The paper addresses the problem of people extraction in a closed context in a video sequence including colour and depth information. The study is based on low cost depth captor included in products such as Kinect or Asus devices that contain a couple of cameras, colour and depth cameras. Depth cameras lack precision especially where a discontinuity in depth occur and some times fail to give an answer. Colour information may be ambiguous to discriminate between background and foreground. This made us use first depth information to achieve a coarse segmentation that is improved with colour information. Furthermore, color information is only used when a classification in two classes of fore/background pixels is clear enough. The developed method provides a reliable and robust segmentation and a natural visual rendering, while maintaining a real time processing.

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Paper citation in several formats:
Boucher, A.; Martinot, O. and Vincent, N. (2015). Depth Camera to Improve Segmenting People in Indoor Environments - Real Time RGB-Depth Video Segmentation.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 55-62. DOI: 10.5220/0005269700550062

@conference{visapp15,
author={Arnaud Boucher. and Olivier Martinot. and Nicole Vincent.},
title={Depth Camera to Improve Segmenting People in Indoor Environments - Real Time RGB-Depth Video Segmentation},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={55-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005269700550062},
isbn={978-989-758-091-8},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Depth Camera to Improve Segmenting People in Indoor Environments - Real Time RGB-Depth Video Segmentation
SN - 978-989-758-091-8
AU - Boucher, A.
AU - Martinot, O.
AU - Vincent, N.
PY - 2015
SP - 55
EP - 62
DO - 10.5220/0005269700550062

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