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An Adaptive Algorithm for Hand Segmentation and Tracking for Continuous Hand Posture Recognition

Published on February 2013 by Madhurjya Kumar Nayak, Anjan Kumar Talukdar, Kandarpa Kumar Sarma
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Mobile and Embedded Technology International Conference 2013
Foundation of Computer Science USA
MECON - Number 1
February 2013
Authors: Madhurjya Kumar Nayak, Anjan Kumar Talukdar, Kandarpa Kumar Sarma
f2fa3c97-0527-4c97-b186-7dfda7ee28e3

Madhurjya Kumar Nayak, Anjan Kumar Talukdar, Kandarpa Kumar Sarma . An Adaptive Algorithm for Hand Segmentation and Tracking for Continuous Hand Posture Recognition. Mobile and Embedded Technology International Conference 2013. MECON, 1 (February 2013), 49-53.

@article{
author = { Madhurjya Kumar Nayak, Anjan Kumar Talukdar, Kandarpa Kumar Sarma },
title = { An Adaptive Algorithm for Hand Segmentation and Tracking for Continuous Hand Posture Recognition },
journal = { Mobile and Embedded Technology International Conference 2013 },
issue_date = { February 2013 },
volume = { MECON },
number = { 1 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 49-53 },
numpages = 5,
url = { /proceedings/mecon/number1/10794-1009/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Mobile and Embedded Technology International Conference 2013
%A Madhurjya Kumar Nayak
%A Anjan Kumar Talukdar
%A Kandarpa Kumar Sarma
%T An Adaptive Algorithm for Hand Segmentation and Tracking for Continuous Hand Posture Recognition
%J Mobile and Embedded Technology International Conference 2013
%@ 0975-8887
%V MECON
%N 1
%P 49-53
%D 2013
%I International Journal of Computer Applications
Abstract

This work reports the design of a continuous hand posture recognition system. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to report a robust and efficient hand segmentation algorithm where a new method for hand segmentation using different colour space models with required morphological processing are utilized. Problems such as skin colour detection, complex background removal and variable lighting condition are found to be efficiently handled with this system. Noise present in the segmented image due to dynamic background can be removed with the help of this adaptive technique. The proposed approach is found to be effective for a range of conditions.

References
  1. T. Ishihara, N. Otsu, "Gesture Recognition Using Auto-Regressive Coefficients of Higher-Order Local Auto-Correlation Features," Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition,pp 583-584, 2004.
  2. F. Flórez, J. M. I. García, J. García and A. Hernández, "Hand Gesture Recognition Following the Dynamics of a Topology-Preserving Network", Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition,pp. 318-319,Washington, 2002.
  3. H. K. Lee and J. H. Kim, "An HMM-Based Threshold Model Approach for Gesture Recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 961-963, 1999.
  4. H. D. Yang,S. Sclaroff and S. W. Lee, "Sign Language Spotting with a Threshold Model Based on Conditional Random Fields", IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 31, no. 7. pp 1264-1265, 2009.
  5. S. L. Phung, A. Bouzerdoum and D. Chai, "Skin Segmentation Using Color Pixel Classification: Analysis and Comparison," IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 27, no. 1, pp 148-151, 2005.
  6. C. Manresa, J. Varona, R. Mas and F. J. Perales, "Real –Time Hand Tracking and Gesture Recognition for Human-Computer Interaction," Computer Vision Center Universitat Autonoma de Barcelona, Barcelona,. pp-1-3, , Spain. 2000.
  7. Y. C. Lu, "Background Substraction Based Segmentation Using Motion Feedback," First International Conference on Robot Vision and Signal Processing(RVSP), pp 224-227, Kaohsiung ,2011.
  8. E. Emami, M. Fathy, "Object Tracking Using Improved CAMShift Algorithm Combined with Motion Segmentation", 7th Iranian Machine Vision and Image Processing(MVIP), pp 1-4,Tehran, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Hand Tracking And Segmentation Hand Gesture Recognition Colour Based Segmentation Background Subtraction Mixture Model