Biometrics Identification Based on Visual Hand Movements Using Wavelet Transform

Sanjay kumar, Dinesh Kant Kumar, Neil Mclachalan

2005

Abstract

This work presents a novel technique of biometric identification based on the temporal history templates (THTs) of visual hand movements. The technique uses view-based approach for representation of hand movements, and uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation of action. The low level representation of the action collapses the temporal structure of the motion from the video sequences of the hand movements while removing any static content from the video sequences to generate temporal history templates (THTs) of the hand movement. THTs of different individuals present distinctive 2-D motion patterns, where each pixel describes the function of temporal history of motion in that sequence. This THT are further sub-divided into four sub-images an average and three detailed images using multi resolution wavelet transforms. The approximate wavelet sub-image is considered as the feature for recognition. The recognition criterion is established using KNN nearest neighbor technique using Mahalanobis distance. The accuracy of accepting an enrolled subject (AAES %) and accuracy of rejecting an imposter (ARI %) are the indicators of identification performance of the technique. The experimental results from 5-different individual indicate that the THT based technique achieves high identification rate when subject specific movements are assigned to the subjects during enrolment.

References

  1. Prabhakar, S., Sharathpankanti. and A.K. Jain, "Biometric Recognition: Security and Privacy Concerns". IEEE Security and Privacy, 2003.
  2. George Panotopoulos, D.P., "Hand Gesture Biometrics". Caltech Centre for Neuromorphic Systems Engineering, 2001.
  3. Nixon, M.S., et al., "Automatic Gait Recogntion". Biometrics: Personal Identification in Networked society, 1999: p. 231-250.
  4. Huang, P.S., C.J. Harris, and M.S. Nixon, "Human gait recognition in canonical space using temporal templates". VISP, April 1999.
  5. Huang, P.S., C.J. Harris, and M.S. Nixon., "Recognising humans by gait via parametric canonical space". Artificial Intelligence in Engineering, 1999. 13: p. 359-366.
  6. Little, J.J.a.J.E.B., "Recognising People by their Gait: The shape of the motion". Videre: Journal of Computer Vision Research,, 1998. 1: p. 2-32.
  7. Shutler, J.D., M.S. Nixon, and C.J. Harris, "Statistical Gait Recognition via Velocity Moments". Institute of Electrical Engineers, Savoy Place, London, 2000.
  8. Niyuogi, S.A.a.E.H.A., "Analysis and Recognizing walking figures in XYT ". Proc. IEEE conference on Computer Vision and Pattern Recognition, June 1994.
  9. Cunado, D., M.S. Nixon, and J.N. Carter, "Using Gait as a Biometric, via Phase-weighted Magnitude Spectra". First International Conference, AVBPA Crans Montana Switzerland., March 1997.
  10. Davis, J., "Recognizing movement using motion histograms ". MIT Media lab Technical Report #487., March 1999.11. Davis, J.a.A.B., "A robust human-silhouette extraction technique for interactive virtual environments". Proc. Modelling and Motion capture Techniques for Virtual Environments, 1998.
  11. Davis, J., "Representing and Recognizing Human Motion: From Motion Templates To Movement Categories". International Conference On Intelligent Robots and Systems,Maui, Hawaii, 2001.
  12. Davis, J.a.A.B., "The representation and recognition of human movement using temporal templates". Proceedings of Computer Vision and Pattern Recognition, June 1997.
  13. Davis, J.a.A.B., "Virtual PAT: a virtual personal aerobics trainer". Proc. Perceptual User Interfaces, November 1998.
  14. Aaron F Bobick, J.D., "The recognition of Human Movements Using Temporal Templates". IEEE Pattern Analysis and Machine Intelligence, 2001. 23 No 3: p. 257-267.
  15. Arun Sharma, D.K.K., Sanjay Kumar, Neil McLachalan., "Representation and Classification of Human Movement Using Temporal Templates and Statistical Measure of Similarity". Workshop On Internet Telecommunications and Signal Processing. 2002. Wollongong, Sydney Australia., WITSP'2002.
  16. Starner, T.P., A., "Visual Recognition of American Sign Language Using Hidden Markov Models". Proc. Intl Workshop on Automated Face and Gesture Recognition Zurich, 1995.
  17. Pentland, I.E.a.A., "Coding, Analysis, Interpretation, and Recognition of Facial Expressions ",. IEEE Trans. Pattern Analysis and Machine Intelligence, July 1997. 19, no. 7: p. 757-763.
  18. Little, J., and J. Boyd, " Describing motion for recognition". International Symposium on Computer Vision, November 1995: p. 235-240.
  19. Sanjay Kumar, A.S., Dinesh K Kumar, Neil McLachalan., "Classification Of Visual Hand gestures For HCI". ACIVS 2002 Proceedings Of the International Conference On Advanced Concepts for Intelligent Vision Systems. 9-11 Sept 2002. Ghent, Belgium.
  20. Sanjay Kumar, A.S., Dinesh Kant Kumar, Neil McLachlan., "Classification of Visual Hand Gestures Using Difference of Frames". Proc. of the Int. Conf. on Imaging Science and Technology, Las Vegas, Nevada, USA , CISST'02. 2002. Las Vegas, USA: (CSREA Press, 2002).
  21. Sanjay Kumar, D.K.K., Arun Sharma, Neil McLachalan., "Visual Hand Gestures Classification Using Wavelets Transform". International Journal Of Wavelets and Multiresolution Information Processing (IJWMP), December-2003. 1, No-4: p. 373-392.
  22. I.Daubcheis, "Orthonormal bases of compactly supported wavelets". Pure Applied. Math, 1998. XLI: p. 906-996.
  23. S.Mallat, A Theory for multiresolution Signal Decomposition:The wavelet Representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 7th July 1989. 11: p. 674-693.
  24. Sarlashkar, A.N.B., M; Malkani, M.J., "Feature Extraction Using Wavelet Transform for neural network based image classification". System Theory Proceeding of the Thirtieth Southeastern Symposium, Morgantown, WV, USA., 1998.
  25. Chumsamrong, W.T., P. Rangsanseri, Y, "Wavelet-based texture analysis for SAR image classification",. Proceedings Of IEEE International Geosciences and Remote Sensing Symposium (IGARSS'99) Hamburg, Germany.,. g19990
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Paper Citation


in Harvard Style

kumar S., Kant Kumar D. and Mclachalan N. (2005). Biometrics Identification Based on Visual Hand Movements Using Wavelet Transform . In Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005) ISBN 972-8865-35-X, pages 131-141. DOI: 10.5220/0001193201310141


in Bibtex Style

@conference{bpc05,
author={Sanjay kumar and Dinesh Kant Kumar and Neil Mclachalan},
title={Biometrics Identification Based on Visual Hand Movements Using Wavelet Transform},
booktitle={Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)},
year={2005},
pages={131-141},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001193201310141},
isbn={972-8865-35-X},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)
TI - Biometrics Identification Based on Visual Hand Movements Using Wavelet Transform
SN - 972-8865-35-X
AU - kumar S.
AU - Kant Kumar D.
AU - Mclachalan N.
PY - 2005
SP - 131
EP - 141
DO - 10.5220/0001193201310141