Kinect based People Identification System using Fusion of Clustering and Classification

Aniruddha Sinha, Diptesh Das, Kingshuk Chakravarty, Amit Konar, Sudeepto Dutta

2014

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.

References

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Paper Citation


in Harvard Style

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, pages 171-179. DOI: 10.5220/0004690201710179


in Bibtex Style

@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},
}


in EndNote Style

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
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