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Authors: Parul Shukla ; K.K. Biswas and Prem K. Kalra

Affiliation: Indian Institiute of Technology, India

Keyword(s): Action Recognition, Kinect, Bag-of-Words, Body-joint.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: In this paper, we propose a Bag-of-Joint-Features model for the classification of human actions from body-joints data acquired using depth sensors such as Microsoft Kinect. Our method uses novel scale and translation invariant features in spherical coordinate system extracted from the joints. These features also capture the subtle movements of joints relative to the depth axis. The proposed Bag-of-Joint-Features model uses the well known bag-of-words model in the context of joints for the representation of an action sample. We also propose to augment the Bag-of-Joint-Features model with a Hierarchical Temporal histogram model to take into account the temporal information of the body-joints sequence. Experimental study shows that the augmentation improves the classification accuracy. We test our approach on theMSR-Action3D and Cornell activity datasets using support vector machine.

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Paper citation in several formats:
Shukla, P.; Biswas, K. and Kalra, P. (2015). Bag-of-Features based Activity Classification using Body-joints Data. 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 314-322. DOI: 10.5220/0005303103140322

@conference{visapp15,
author={Parul Shukla. and K.K. Biswas. and Prem K. Kalra.},
title={Bag-of-Features based Activity Classification using Body-joints Data},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP},
year={2015},
pages={314-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005303103140322},
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 - Bag-of-Features based Activity Classification using Body-joints Data
SN - 978-989-758-089-5
IS - 2184-4321
AU - Shukla, P.
AU - Biswas, K.
AU - Kalra, P.
PY - 2015
SP - 314
EP - 322
DO - 10.5220/0005303103140322
PB - SciTePress