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Reseach Article

Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction

by Parimita Saikia, Karen Das
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 25
Year of Publication: 2013
Authors: Parimita Saikia, Karen Das
10.5120/11270-6303

Parimita Saikia, Karen Das . Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction. International Journal of Computer Applications. 65, 25 ( March 2013), 5-11. DOI=10.5120/11270-6303

@article{ 10.5120/11270-6303,
author = { Parimita Saikia, Karen Das },
title = { Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 25 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number25/11270-6303/ },
doi = { 10.5120/11270-6303 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:20:51.783413+05:30
%A Parimita Saikia
%A Karen Das
%T Head Gesture Recognition using Optical Flow based Classification with Reinforcement of GMM based Background Subtraction
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 25
%P 5-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper describes a technique of real time head gesture recognition system. The method includes Gaussian mixture model (GMM) accompanied by optical flow algorithm which provided us the required information regarding head movement. The proposed model can be implemented in various control system. We are also presenting the result and implementation of both mentioned method.

References
  1. Prateem Chakraborty, Prashant Sarawgi, Ankit Mehrotra, Gaurav Agarwal, Ratika Pradhan "Hand Gesture Recognition: A Comparative Study", Proceedings of the International MultiConference of Engineers and Computer Scientists 2008 Vol I IMECS 2008, 19-21 March, 2008, Hong Kong.
  2. Kazumoto TANAKA "Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph", IJCSI International Journal of Computer Science Issues, Vol. 6, No. 2, 2009.
  3. Sujitha Martin, Cuong Tran, Ashish Tawari, Jade Kwan and Mohan Trivedi "Optical flow based Head Movement and Gesture Analysis in Automotive Environment", 2012 15th International IEEE Conference on Intelligent Transportation Systems Anchorage, Alaska, USA, September 16-19, 2012.
  4. Siddharth S. Rautaray, Anupam Agrawal, "Real time hand gesture recognition System for dynamic applications" International Journal of UbiComp (IJU), Vol. 3, No. 1, January 2012.
  5. Hee-Deok Yang, A-Yeon Park and Seong-Whan Lee "Gesture Spotting and Recognition for Human–Robot Interaction" IEEE Transactions On Robotics, Vol. 23, No. 2, April 2007.
  6. Thanarat Horprasert, David Harwood, and Larry S. Davis, "A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection".
  7. Michael B. Holte, Cuong Tran, Mohan M. Trivedi, , and Thomas B. Moeslund, "Human Pose Estimation and Activity Recognition From Multi-View Videos: Comparative Explorations of Recent Developments", IEEE Journal Of Selected Topics In Signal Processing, Vol. 6, No. 5, September 2012
  8. C. Lodato, and S. Lopes "An Optical Flow Based Segmentation Method for Objects Extraction" International Journal of Engineering and Applied Sciences 1:4: 2005
  9. Miss. Shweta K. Yewale, ProfMr. Pankaj K. Bharne "Artificial Neural Network Approach For Hand Gesture Recognition", International Journal of Engineering Science and Technology (IJEST).
  10. Sushmita Mitra, And Tinku Acharya, "Gesture Recognition: A Survey" IEEE Transactions on Systems, Man, And Cybernetics—Part C: Applications And Reviews, Vol. 37, No. 3, May 2007.
  11. Tushar Agrawal Subhasis Chaudhuri "gesture recognition using position and appearance features"
  12. Berthold K. P. Horn and Brian G. Rhunck ,"Determining Optical Flow" Artificial Intelligence 17 (198 I ) 18. 5-203
  13. Anubhav Srivastava, Pranshi Agarwal, Swati Agarwal & Usha Sharma "Gesture Recognition System", International Journal Of Electronics Signals And Systems (Ijess) Issn: 2231- 5969, Vol-1 Iss-4, 2012
  14. Darun Kesrarat and Vorapoj Patanavijit " Tutorial of Motion Estimation Based on Horn-Schunk Optical Flow Algorithm in MATLAB" , Review Article
  15. Oleksiy Busaryev, John Doolittle "Gesture Recognition with Applications", CSE 634 Class Project Report
  16. J. Barron, "Incorporating Optical Flow into Tinatoo"l. , Tina Memo 2004-013.
  17. Carman Neustaedter "An Evaluation of Optical Flow using Lucas and Kanade's Algorithm" Neustaedter, 2002
  18. Qing Chen, Nicolas D. Georganas, Emil M. Petriu,"Real-Time Vision-Based Hand Gesture Recognition Using Haar-Like Features", Instrumentation and Measurement Technology Conference – IMTC 2007
  19. Rafael A. B. de Queiroz, Gilson A. Giraldi, Pablo J. Blanco, Raúl A. Feijóo, "Determining Optical Flow using a Modified Horn and Schunck's Algorithm", IWSSIP 2010 - 17th International Conference on Systems, Signals and Image Processing .
  20. Louis-Philippe Morency, Trevor Darrell "Head Gesture Recognition in Intelligent Interfaces The Role of Context in Improving Recognition"
  21. Qing Chen, Nicolas D. Georganas, Emil M. Petriu Real-time Vision-based Hand Gesture Recognition Using Haar-like Features" Instrumentation and MeasurementTechnology Conference – IMTC 2007
  22. Miss. Shweta k. Yewale, mr. Pankaj k. Bharne, "Artificial neural network Approach for hand gesture Recognition" International Journal of Engineering Science and Technology (IJEST)
  23. E. Kollorz and J. Hornegger, "Gesture recognition with a time-of-flight camera", Workshop in Conjunction with DAGM'07
  24. Sebastian Loehmann," Sneaking Interaction Techniques into Electric Vehicles", AutomotiveUI'12, October 17-19, Portsmouth, NH, USA
  25. Chris Stauffer, W. E. l Grimson , "Adaptive background mixture models for real-time tracking", The Artificial Intelligence Laboratory Massachusetts Institute of Technology
  26. Subra Mukherjee ,Karen Das," An adaptive gmm approach to background subtraction for application in real time surveillance", ISSN: 2319 - 1163 Volume: 2 Issue: 1 25 – 29
Index Terms

Computer Science
Information Sciences

Keywords

Head gesture GMM background subtraction optical flow