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Reseach Article

Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach

by Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 5
Year of Publication: 2012
Authors: Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj
10.5120/7625-0685

Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj . Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach. International Journal of Computer Applications. 49, 5 ( July 2012), 26-33. DOI=10.5120/7625-0685

@article{ 10.5120/7625-0685,
author = { Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj },
title = { Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 5 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number5/7625-0685/ },
doi = { 10.5120/7625-0685 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:45:30.564953+05:30
%A Sonali Navghare
%A Shubhangi Giripunje
%A Preeti Bajaj
%T Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 5
%P 26-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The bio-inspired computation algorithms are the excellent tools for global optimization. These algorithms are very easy to understand and simple to implement. These algorithms especially dominate the classical optimization methods. Particle Swarm Optimization (PSO) is a global optimization algorithm that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. This paper presents facial emotion recognition system using PSO for different video clips with different cameras, at different distances and light intensity changes. The analysis is done for recognizing "Happy" emotion from other emotions. The comparison of facial emotion recognition system using other techniques and PSO is done. It is found that PSO has better results over other techniques in terms of accuracy and time required.

References
  1. V. Miranda and N. Fonseca, "EPSO -- Evolutionary Particle Swarm Optimization, a New Algorithm with Applications in Power Systems", Proceedings of the Asia Pacific IEEE/PES Transmission and Distribution Conference and Exhibition, 2002, vol. 2, pp. 745-750.
  2. M. Settles and B. Rylander. , "Neural Network Learning using Particle Swarm Optimizers", Advances in Information Science and Soft Computing, 2002, pp. 224-226.
  3. M. G. Omran, A. P. Engelbrecht, and A. Salman, "Particle Swarm Optimization Method for Image Clustering", International Journal on Pattern Recognition and Artificial Intelligence, , 2005, vol. 19, no. 3, pp. 297-322.
  4. Salman, I. Ahmad, and S. Al-Madani, "Particle Swarm Optimization for Task Assignment Problem", Microprocessors and Microsystems, 2002, vol. 26, no. 8, pp. 363-371.
  5. M. Suwa, N. Sugie, and K. Fujimora. A preliminary note on pattern recognition of human emotional expression. In International Joint Conference on Pattern Recognition, pages 408–410, 1978.
  6. Y. Yacoob, H. -M. Lam, and L. Davis. Recognizing faces showing expressions. In Proc. Int. Workshop on Automatic Face- and Gesture-Recognition, pages 278–283, Zurich, Switserland, 1995.
  7. C. M. Lee, S. Narayanan, and R. Pieraccini, "Recognition of negative emotions from the speech signal," in Proc. Automatic Speech Recognition and Understanding, Dec 2001.
  8. V. Petrushin, "Emotion in speech: Recognition and application to call centers," Artificial Neural Net. In Engr. (ANNIE '99), 1999.
  9. R. Plutchik, The Psychology and Biology of Emotion, HarperCollins College, New York, NY, 1994.
  10. 10. Chul Min Lee and Shrikanth Narayanan, "Emotion Recognition Using a Data-Driven Fuzzy Inference System" Eurospeech, 2003, Geneva
  11. Esau, N. , Wetzel, E. , Kleinjohann, L. , Kleinjohann, B. , "Real-Time Facial Expression Recognition Using a Fuzzy Emotion Model" Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007, 23-26 July 2007 , 1 – 6.
  12. Amav Bhavsar and Hima M. Patel, "Facial Expression Recognition Using Neural Classifier and Fuzzy Mapping", IEEE Indicon 2005 Conference, Chennai, India, 11-13 Dec. 2005.
  13. Adnan Khashman, "A Modified Backpropagation Learning Algorithm With Added Emotional Coefficients", IEEE Transactions On Neural Networks, VOL. 19, NO. 11, November 2008.
  14. Chatterjee, S. ; Hao Shi, "A Novel Neuro Fuzzy Approach to Human Emotion Determination", International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2010, 282 – 287.
  15. Shuaishi Liu, Yantao Tian, Cheng Peng, Jinsong Li, "Facial Expression Recognition Approach Based on Least Squares Support Vector Machine with Improved Particle Swarm Optimization Algorithm", Proceedings of the 2010 IEEE International Conference on Robotics and Biomimetics December 14-18, 2010, Tianjin, China.
  16. R. Eberthart, and J. Kennedy, "A new optimizer using particle swarm theory," in Proceeding of the 6th international symposium on micro machine and human science. 1995, pp. 39–43.
  17. Bashir Mohammed Ghandi, R. Nagarajan and Hazry Desa, "Particle Swarm Optimization Algorithm for Facial Emotion Detection", IEEE Symposium on Industrial Electronics and Applications, October 4-6, 2009, Malaysia.
  18. Bashir Mohammed Ghandi, R. Nagarajan and Hazry Desa, "Facial Emotion Detection using GPSO and Lucas-Kanade Algorithms", International Conference on Computer and Communication Engineering (ICCCE 2010), 11-13 May 2010, Kuala Lumpur, Malaysia
  19. B. D. Lucas and T. Kanade, "An iterative image registration technique with an application to stereo vision," in Proceedings of Imaging Understanding Workshop, pp. 121–130, 1981.
  20. Ketki Patil, Prof S D Giripunje, Dr Preeti Bajaj, "Facial expression recognition and Head Tracking in Video Using Gabor Filter", Third International Conference on Emerging Trends in Engineering and Technology, 2010.
  21. Mahima Agrawal, Prof S. D. Giripunje, "Recognitizing Facial Expression using PCA and Genetic Algorithm", ICCSI-2011(International Conference on Computer Science and Informatics) organized by IIMT, Bhubaneswar.
Index Terms

Computer Science
Information Sciences

Keywords

Bio-inspired Computing Particle Swarm Optimization Lucas-Kanade algorithm