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Authors: Aniruddha Sinha 1 ; Diptesh Das 1 ; Kingshuk Chakravarty 1 ; Amit Konar 2 and Sudeepto Dutta 3

Affiliations: 1 Tata Consultancy Services Ltd., India ; 2 Jadavpur University, India ; 3 Sikkim Manipal Institute of Technology, India

Keyword(s): Kinect sensor, Human Identification, Gait Detection, Clustering, Classification, Fusion, Dempster-Shafer Theory, Human Skeleton.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction

Abstract: The demand of human identification in a non-intrusive manner has risen increasingly in recent years. Several works have already been done in this context using gait-cycle detection from human skeleton data using Microsoft Kinect as a data capture sensor. In this paper we have proposed a novel method for automatic human identification in real time using the fusion of both supervised and unsupervised learning on gait-based features in an efficient way using Dempster-Shafer (DS) theory. Performance comparison of the proposed fusion based algorithm is done with that of the standard supervised or unsupervised algorithm and it needs to be mentioned that the proposed algorithm is able to achieve 71% recognition accuracy.

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Paper citation in several formats:
Sinha, A.; Das, D.; Chakravarty, K.; Konar, A. and Dutta, S. (2014). Kinect based People Identification System using Fusion of Clustering and Classification. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3; ISSN 2184-4321, pages 171-179. DOI: 10.5220/0004690201710179

@conference{visapp14,
author={Aniruddha Sinha. and Diptesh Das. and Kingshuk Chakravarty. and Amit Konar. and Sudeepto Dutta.},
title={Kinect based People Identification System using Fusion of Clustering and Classification},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={171-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004690201710179},
isbn={978-989-758-009-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Kinect based People Identification System using Fusion of Clustering and Classification
SN - 978-989-758-009-3
IS - 2184-4321
AU - Sinha, A.
AU - Das, D.
AU - Chakravarty, K.
AU - Konar, A.
AU - Dutta, S.
PY - 2014
SP - 171
EP - 179
DO - 10.5220/0004690201710179

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