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Authors: Jilliam María Díaz Barros 1 ; Frederic Garcia 2 and Désiré Sidibé 1

Affiliations: 1 Université de Bourgogne, France ; 2 University of Luxembourg, Luxembourg

Keyword(s): Human Pose Estimation, Point Cloud, Skeleton Model.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping ; Shape Representation and Matching

Abstract: This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being robust, precise and handling large portions of missing data due to occlusions, acquisition hindrances or registration inaccuracies.

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Paper citation in several formats:
Díaz Barros, J. ; Garcia, F. and Sidibé, D. (2015). Real-time Human Pose Estimation from Body-scanned Point Clouds. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP; ISBN 978-989-758-089-5; ISSN 2184-4321, SciTePress, pages 553-560. DOI: 10.5220/0005309005530560

@conference{visapp15,
author={Jilliam María {Díaz Barros} and Frederic Garcia and Désiré Sidibé},
title={Real-time Human Pose Estimation from Body-scanned Point Clouds},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP},
year={2015},
pages={553-560},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005309005530560},
isbn={978-989-758-089-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP
TI - Real-time Human Pose Estimation from Body-scanned Point Clouds
SN - 978-989-758-089-5
IS - 2184-4321
AU - Díaz Barros, J.
AU - Garcia, F.
AU - Sidibé, D.
PY - 2015
SP - 553
EP - 560
DO - 10.5220/0005309005530560
PB - SciTePress

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