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Authors: Marco Körner ; Daniel Haase and Joachim Denzler

Affiliation: Friedrich Schiller University of Jena, Germany

Keyword(s): Human action recognition, Manifold learning, PCA, Shape model.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Human-Computer Interaction ; ICA, PCA, CCA and other Linear Models ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Shape Representation ; Software Engineering ; Theory and Methods

Abstract: Since depth measuring devices for real-world scenarios became available in the recent past, the use of 3d data now comes more in focus of human action recognition. We propose a scheme for representing human actions in 3d, which is designed to be invariant with respect to the actor’s scale, rotation, and translation. Our approach employs Principal Component Analysis (PCA) as an exemplary technique from the domain of manifold learning. To distinguish actions regarding their execution speed, we include temporal information into our modeling scheme. Experiments performed on the CMU Motion Capture dataset shows promising recognition rates as well as its robustness with respect to noise and incorrect detection of landmarks.

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Paper citation in several formats:
Körner, M.; Haase, D. and Denzler, J. (2012). SCALE-INDEPENDENT SPATIO-TEMPORAL STATISTICAL SHAPE REPRESENTATIONS FOR 3D HUMAN ACTION RECOGNITION. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM; ISBN 978-989-8425-98-0; ISSN 2184-4313, SciTePress, pages 288-294. DOI: 10.5220/0003766202880294

@conference{icpram12,
author={Marco Körner. and Daniel Haase. and Joachim Denzler.},
title={SCALE-INDEPENDENT SPATIO-TEMPORAL STATISTICAL SHAPE REPRESENTATIONS FOR 3D HUMAN ACTION RECOGNITION},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM},
year={2012},
pages={288-294},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003766202880294},
isbn={978-989-8425-98-0},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM
TI - SCALE-INDEPENDENT SPATIO-TEMPORAL STATISTICAL SHAPE REPRESENTATIONS FOR 3D HUMAN ACTION RECOGNITION
SN - 978-989-8425-98-0
IS - 2184-4313
AU - Körner, M.
AU - Haase, D.
AU - Denzler, J.
PY - 2012
SP - 288
EP - 294
DO - 10.5220/0003766202880294
PB - SciTePress