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Reseach Article

A Heuristic based RBFN for Location and Rotation Invariant Clear and Occluded Face Identification

Published on March 2014 by Goutam Sarker, Shruti Sharma
International Conference on Advances in Computer Engineering and Applications
Foundation of Computer Science USA
ICACEA - Number 1
March 2014
Authors: Goutam Sarker, Shruti Sharma
6f97aeb7-16f9-4cdb-8899-a144652f028a

Goutam Sarker, Shruti Sharma . A Heuristic based RBFN for Location and Rotation Invariant Clear and Occluded Face Identification. International Conference on Advances in Computer Engineering and Applications. ICACEA, 1 (March 2014), 30-36.

@article{
author = { Goutam Sarker, Shruti Sharma },
title = { A Heuristic based RBFN for Location and Rotation Invariant Clear and Occluded Face Identification },
journal = { International Conference on Advances in Computer Engineering and Applications },
issue_date = { March 2014 },
volume = { ICACEA },
number = { 1 },
month = { March },
year = { 2014 },
issn = 0975-8887,
pages = { 30-36 },
numpages = 7,
url = { /proceedings/icacea/number1/15613-1401/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Computer Engineering and Applications
%A Goutam Sarker
%A Shruti Sharma
%T A Heuristic based RBFN for Location and Rotation Invariant Clear and Occluded Face Identification
%J International Conference on Advances in Computer Engineering and Applications
%@ 0975-8887
%V ICACEA
%N 1
%P 30-36
%D 2014
%I International Journal of Computer Applications
Abstract

This paper describes a robust and efficient method for rotation and location independent identification and localization of facial images using one modified Radial Basis Function Network (RBFN) which embeds a new Heuristic Based Clustering (HBC) and Back Propagation (BP) learning. HBC in RBFN determines the natural number of clusters or groups on the basis of 'person-view'. BP network learns to identify a 'person' irrespective of his view. The method successfully performs location invariant upright and rotated facial identification in different views and expressions with or without occlusion. The learning as well as identification with standard facial database is fast, efficient, effective and the accuracy as well as precision of the system with Holdout Method is moderate.

References
  1. G. L Marcialis and F. Roli, "Fusion of appearance based on face recognition algorithm", . Pattern Analysis and Applications,v. 7. No 2,Springer-verlag London(2004) pp 151-163.
  2. W. Zhao, R. Chellappa, A. Rosenfeld, P. J. Phillips, "Face Recognition: A literature Survey", UMD CFAR Technical Report CAR-TR-948,(2000).
  3. G. Sarker, "A Heuristic Based Hybrid Clustering for Natural Classification", International Journal of Computer, Information Technology and Engineering (IJCITAE), Vol. 1 No. 2, Dec. 2007, pp. 79-86.
  4. G. Sarker, "A Heuristic Based Hybrid Clustering", Journal of the Institution of Engineers, Computer Engineering Division, Vol 89, November 2008, pp. 7- 10.
  5. G. Sarker, "A Heuristic Based Hybrid Clustering for Natural Classification in Data Mining", 20th Indian Engineering Congress, organized by The Institution of Engineers (India), December 15-18,2005,Kolkata,INDIA, paper no. 4.
  6. G. Sarker, "A Heuristic Based Hybrid Clustering for Natural Classification", International Conference of Computer & Devices for Communication CODEC-06 held on December 18-20,2006, Kolkata organized by Institute of Radio physics & Electronics, University of Calcutta.
  7. G. Sarker, "An Optimal Back propagation Network for Face Identification and Localization",International Journal of Computers and Applications,Vol. 35, Issue 2, 2013, ACTA Press, Canada.
  8. G. Sarker, "An Unsupervised Learning Network for Face Identification and Localization", International Journal if Computer, Information Technology and Engineering (IJCITAE), Vol. 6, No 2, pp-83-89, Dec 2012.
  9. G. Sarker, "An Unsupervised Learning Network for Face Identification and Localization", International Conference on Communications , Devices and Intelligent Systems (CODIS), Dec 28 and 29, 2012, Kolkata pp 652-655.
  10. G. Sarker, "A Probabilistic Framework of Face Detection", IJCITAE, Vol. 4, No. 1 pp 1-17, 2010.
  11. G. Sarker, "A Multilayer Network for Face Detection and Localization", Vol. 5, No. 2 pp 41-53, 2011.
  12. G. Sarker, K. Roy, "An RBF network with Optimal Clustering for Face Identification", International Conference on Information & Engineering Science- 2013 (ICIES-2013),Feb. 21-23 2013, organized by IMRF, Vijayawada, Andhra Pradesh.
  13. G. Sarker, K. Roy, "A Modified RBF network with Optimal Clustering for Face Identification and Localization", International Conference on Advanced Engineering and Technology , held at Kolkata on 15th Feb. 2013, pp. 32-37
  14. G. Sarker, S. Kundu, "A Modified Radial Basis Function Network for Fingerprint Identification and Localization", International Conference on Advanced Engineering and Technology , held at Kolkata on 15th Feb. 2013, pp. 26-31.
  15. G. Sarker, "A competitive Learning Network for Face Detection and Localization", accepted for publication in the International Journal of Computer, Information Technology and Engineering (IJCITAE), June, 2013.
  16. K. Roy, G. Sarker, "A Location Invariant Face Identification and Localization with Modified RBF Network", published in ICCS 2013, 21-22 September, 2013, Burdwan pp 23-28.
  17. S. Kundu, G. Sarker, "A Modified Radial Basis Function Network for Occluded Fingerprint Identification and Localization", IJCITAE, 7(2), pp 103-109, 2013.
  18. D. Bhakta, G. Sarker, "A Radial Basis Function Network for Face Identification and Subsequent Localization", International Conference on Computer Science and Information Technology (ICCSIT), pp. 1-6, 10th March 2013.
  19. Ferdnand van der Heijden, "Edge and Line Feature Extraction Based on Covariance Model", IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 11, NO. I, JANUARY 1995.
  20. Ming-Hsuan Yang, Member, IEEE, David J. Kriegman,Senior Member, IEEE, and Narendra Ahuja, Fellow, IEEE "Detecting Faces in Images: A Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 24, NO. 1, JANUARY 2002.
  21. Haiyuan Wu, Qian Chen, and Masahiko Yachida, "Face Detection From Color Images Using Fuzzy Pattern Matching Method", IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 21, NO. 6, JUNE 1999.
  22. M. A. Turk and A. P Pentland, "Eigen faces for Recognition", Journal of Cognitive Neuroscience, v. 3, No. 1, pp. 71-86, 1991.
  23. F. Behloul, B. P. F. Lelieveldt, A. Boudraa, J. H. C. Reiber, "Optimal design of radial basis function neural networks for fuzzy-rule extraction in high dimensional data", The Journal of the Pattern Recognition Society.
  24. M. J. Er, S. Wu, J. Lu and H. L. Toh "Face Recognition with RBF Neural Networks", IEEEtran on Neural Networks, v. 13, No 3(2002), pp 697-710.
  25. J. Park and J. Wasnberg, "Universal Approximator Using Radial Basis Function Network" Neural Computation, v. 3, pp 246-257, 1991.
  26. J. Moody and C. J. Draken, "Fast Learning in Network of Locally Tuned Processing Units", Neural Computation, v. 1, pp 281-294, 1989
  27. S. Lee and R. M. Kil, "A Gaussian Potential with Hierarchically Self Organizing Learning", Neural Networks, v. 4, pp. 207-224, 1991.
  28. F. Girosi and T. Poggio, "Networks and The Best Approximation Property", Biological Cybernetics, v. 63, pp. 169-176, 1990.
  29. Xianquan Zhang , Zhenjun Tang, Jinhui Yu, Mingming Guo, "A Fast Convex Hull Algorithm for Binary Image", Informatica 34 (2010) pp. 369-376.
  30. M. Hamouz, J. Kittler,J. -K. Kamarainen,P. Paalanen,H. Ka "lvia" inen, and J. Matas, Member,IEEE Computer Society "Feature-Based Affine-Invariant locaization of Faces",IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 27, NO. 9, SEPTEMBER 2005.
  31. ShujaatAli,Jagannath University, Jaipur, Rajasthan, "Novel fast and Efficient Face Recognition Technique", International Journal of IT, Engineering and Applied Sciences Research (IJIEASR)Volume 1, No. 1, October 2012,ISSN: 2319-4413.
  32. Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", Pearson Education, Second Edition.
  33. H. A. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face Detection", IEEE Transactions PAMI, vol. 20,no. 1, pp. 23-38,Jan. ,1998.
  34. H. A. Rowley, S. Baluja, and T. Kanade, "Rotation Invariant Neural Network-Based Face Detection", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'98), 1998, pp. 38.
  35. Khairul Azha A. Aziz,Ridza Azri Ramlee,Ahmad Nizam Jahari,Melaka,Malaysia,Shahrum Shah Addullah,Skudai,Malaysia "Face Detection Using Radial Basis Function Neural Network With Variance Spread Value", 2009 International Conference of Soft Computing and Pattern Recognition.
Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Hbc Bp Network Rbfn Holdout Method Accuracy