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Reseach Article

Face and Hand Gesture Recognition using Principle Component Analysis and kNN Classifier

by Adita K Nimbalkar, R. R. Karhe, C. S. Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 8
Year of Publication: 2014
Authors: Adita K Nimbalkar, R. R. Karhe, C. S. Patil
10.5120/17394-7944

Adita K Nimbalkar, R. R. Karhe, C. S. Patil . Face and Hand Gesture Recognition using Principle Component Analysis and kNN Classifier. International Journal of Computer Applications. 99, 8 ( August 2014), 26-28. DOI=10.5120/17394-7944

@article{ 10.5120/17394-7944,
author = { Adita K Nimbalkar, R. R. Karhe, C. S. Patil },
title = { Face and Hand Gesture Recognition using Principle Component Analysis and kNN Classifier },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 8 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number8/17394-7944/ },
doi = { 10.5120/17394-7944 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:40.683631+05:30
%A Adita K Nimbalkar
%A R. R. Karhe
%A C. S. Patil
%T Face and Hand Gesture Recognition using Principle Component Analysis and kNN Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 8
%P 26-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Gesture recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation to virtual reality. In this paper, we provide a survey on gesture recognition with particular emphasis on hand gestures and facial expressions. Applications involving wavelet transform and principal component analysis for face and hand gesture recognition on digital images.

References
  1. Bui. T. T. T, Phan. N. H, Spitsyn V. G, "Face and hand Gesture Recognition Algorith based on Wavelet Transform & Principle Component Analysis", 978-1-4673-1773-3/12/$31. 00 ©2013 IEEE
  2. P. Viola and M. J. Jones, "Rapid object detection using a boosted cascade of simple features," IEEE Conf. on Computer Vision and Pattern Recognition,. vol. 1, pp. 511–518, Kauai, Hawaii, USA, 2001.
  3. P. Viola and M. J. Jones, "Robust real-time face detection," International Journal of Computer Vision, vol. 57, no. 2, pp. 137–154, 2004.
  4. Murthy, G. R. S. and Jadon, R. S. A Review of Vision Based Hand Gestures Recognition. Int. J. of Information Technology and Knowledge Management, 2(2) (2009), 405 – 410
  5. Richard Duda, Peter Hart, David Stork, "Pattern Cassification"
  6. R. C. Gonzalez and R. E. Woods, Digital image processing. Reading MA: Addison-Wesley, 2001.
  7. C. Papageorgiou, M. Oren and T. Poggio, "A general framework for object detection," // International Conference on Computer Vision,1998.
  8. T. K. Kim, S. F. , Wong and R. Cipolla, "Cambrige Hand Gesture Data set," [Online]. Available: http://www. iis. ee. ic. ac. uk/~tkkim/ges_db. htm
Index Terms

Computer Science
Information Sciences

Keywords

Wavelet transforms Principle component analysis KNN