DYNAMIC HAND GESTURE RECOGNITION SYSTEM USING NEURAL NETWORK

Chitralekha Mahanta, T. Srinivas Yadav, Hemanta Medhi

Abstract

Vision-based hand gesture recognition enabling computers to understand hand gestures as humans do is an important technology for intelligent human computer interaction. In this paper, a recognition system for dynamic hand gestures is proposed. In dynamic hand gesture recognition, hand is segmented by using background subtraction method. MPEG-7 ART based shape descriptors are used to extract spatial information. Our approach is based on particle filter to extract trajectory features. After collecting suitable features, Radial Basis Function neural network is used for classification. Gesture recognition rate is in the range of 80% to 98%.

References

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Paper Citation


in Harvard Style

Mahanta C., Srinivas Yadav T. and Medhi H. (2011). DYNAMIC HAND GESTURE RECOGNITION SYSTEM USING NEURAL NETWORK . In Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-8425-48-5, pages 253-256. DOI: 10.5220/0003299102530256


in Bibtex Style

@conference{peccs11,
author={Chitralekha Mahanta and T. Srinivas Yadav and Hemanta Medhi},
title={DYNAMIC HAND GESTURE RECOGNITION SYSTEM USING NEURAL NETWORK},
booktitle={Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2011},
pages={253-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003299102530256},
isbn={978-989-8425-48-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - DYNAMIC HAND GESTURE RECOGNITION SYSTEM USING NEURAL NETWORK
SN - 978-989-8425-48-5
AU - Mahanta C.
AU - Srinivas Yadav T.
AU - Medhi H.
PY - 2011
SP - 253
EP - 256
DO - 10.5220/0003299102530256