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Authors: S. Amin Dadgar ; Jean-Christophe Nebel and Dimitrios Makris

Affiliation: Kingston University, United Kingdom

Keyword(s): 3D Pose Estimation, Principle Component Analysis, Gaussian Mixture Model, Annealed Particle Filter.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Model-Based Object Tracking in Image Sequences ; Motion, Tracking and Stereo Vision

Abstract: This paper presents a system for 3D Pose estimation of cyclic activities (e.g. walking, jogging). Principal Component Analysis is used to compress the high dimensional space of poses. Human activities are encoded by Hidden Markov Models, overlaid on Gaussian Mixture Models. A generative approach based on the Annealed Particle Filter is used to estimate poses from silhouettes derived by a monocular camera. Experimental results indicate the value of the proposed Dense Gaussian Mixture Model when initialised by a gait cycle.

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Paper citation in several formats:
Amin Dadgar, S.; Nebel, J. and Makris, D. (2010). 3D POSE ESTIMATION FROM SILHOUETTES IN CYCLIC ACTIVITIES ENCODED BY A DENSE GAUSSIANS MIXTURE MODEL. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP; ISBN 978-989-674-028-3; ISSN 2184-4321, SciTePress, pages 492-495. DOI: 10.5220/0002896004920495

@conference{visapp10,
author={S. {Amin Dadgar}. and Jean{-}Christophe Nebel. and Dimitrios Makris.},
title={3D POSE ESTIMATION FROM SILHOUETTES IN CYCLIC ACTIVITIES ENCODED BY A DENSE GAUSSIANS MIXTURE MODEL},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP},
year={2010},
pages={492-495},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002896004920495},
isbn={978-989-674-028-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 1: VISAPP
TI - 3D POSE ESTIMATION FROM SILHOUETTES IN CYCLIC ACTIVITIES ENCODED BY A DENSE GAUSSIANS MIXTURE MODEL
SN - 978-989-674-028-3
IS - 2184-4321
AU - Amin Dadgar, S.
AU - Nebel, J.
AU - Makris, D.
PY - 2010
SP - 492
EP - 495
DO - 10.5220/0002896004920495
PB - SciTePress

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