CFP last date
22 April 2024
Reseach Article

Study of different Trends and Techniques in Face Recognition

by Divyakant T. Meva, C. K. Kumbharana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 8
Year of Publication: 2014
Authors: Divyakant T. Meva, C. K. Kumbharana
10.5120/16811-6548

Divyakant T. Meva, C. K. Kumbharana . Study of different Trends and Techniques in Face Recognition. International Journal of Computer Applications. 96, 8 ( June 2014), 1-4. DOI=10.5120/16811-6548

@article{ 10.5120/16811-6548,
author = { Divyakant T. Meva, C. K. Kumbharana },
title = { Study of different Trends and Techniques in Face Recognition },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 8 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number8/16811-6548/ },
doi = { 10.5120/16811-6548 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:21:10.558936+05:30
%A Divyakant T. Meva
%A C. K. Kumbharana
%T Study of different Trends and Techniques in Face Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 8
%P 1-4
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

History of Face recognition is old enough to be mature. In 1960s, face recognition became semi-automated. In 1970s, face recognition took another step in automation. In 1988, first semi-automated facial recognition system was deployed. In 2001, automated face recognition captured attention of public at SuperBowl event to capture surveillance images. Now a day, every country in the world is using this technology for different purposes. In this paper, we have discussed some novel techniques and algorithms for face recognition of the current trends.

References
  1. Zhao W. et al. , Face Recognition – A Literature Survey, ACM Computing Surveys, Vol. 35, No. 4, December 2003, pp. 399–458
  2. Turk, M. and Pentland, A. , Eigenfaces for recognition, J. Cogn. Neurosci. 3, 1991, 72–86
  3. Moghaddam, B. and Pentlad, A. , Probabilistic visual learning for object representation, IEEE Trans. Patt. Anal. Mach. Intell. 19,1997, 696– 710.
  4. Belhumeur P N, Hespanha J P and Kreigman D J, Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Patt. Anal. Mach. Intell. 19, 2007, 711–720.
  5. Liu C, Andwechsler H, Evolutionary pursuit and its application to face recognition, IEEE Trans. Patt. Anal. Mach. Intell. 22, 2000a. , 570–582
  6. Lin, S. H. , Kung, S. Y. , And Lin, L. J. , Face recognition/ detection by probabilistic decision based neural network, IEEE Trans. Neural Netw. 8, 1997, 114–132
  7. Kelly, M. D. , Visual identification of people by computer, Tech. rep. AI-130, Stanford AI Project, Stanford, CA.
  8. Samaria, F. And Young, S. , HMM based architecture for face identification, Image Vis. Comput. 12, 1994, 537–583.
  9. Lawrence, S. , Giles, C. L. , Tsoi, A. C. , And Back, A. D. , Face recognition: A Convolutional neural-network approach. IEEE Trans. Neural Netw. 8, 1997, 98–113
  10. Pentland, A. , Moghaddam, B. , Starner, T. , View-based And modular eigenspaces for face recognition. In Proceedings, IEEE Conference on Computer Vision and Pattern Recognition, 1994.
  11. Heisele, B. , Serre, T. , Pontil, M. , And Poggio, T. , Component-based face detection. In Proceedings, IEEE Conference on Computer Vision and Pattern Recognition, 2001.
  12. Liau et al. , " New parallel Methods of Face Recognition", Advances in Face Recognition, I-Tech, 2008, pp 15-26
  13. Taranpreet Singh Ruprah, "Face Recognition Based on PCA Algorithm", Special Issue of International Journal of Computer Science & Informatics, ISSN: 2231–5292, Vol. - II, Issue-1, 2 , pp 221 - 225
  14. Muhammad Akmal Khan et al. , "Face Recognition using Sub – Holistic PCA", British Journal of Science, September 2011, Vol. 1 (1), pp. 111- 120
  15. Craw, I. , Tock, D. & Bennett, A. Finding Face Features, in 'European Conference on Computer Vision', 1992, pp. 92–96.
  16. Manjunath, B. , Chellappa, R. & von der Malsburg, C. (1992), 'A Feature Based Approach to Face Recognition', IEEE Conference Proceedings on Computer Vision and Pattern Recognition pp. 373–378.
  17. Lades, M. , Vorbr¨uggen, J. , Buhmann, J. , Lange, J. , von der Malsburg, C. ,W¨urtz, R. & Konen,W. , 'Distortion invariant object recognition in the dynamic link architecture', IEEE Transactions on Computers 42(3),1993, 300–311.
  18. Wiskott, L. , Fellous, J. , Kr¨uger, N. & von der Malsburg, C. , Face recognition by elastic bunch graph matching, in L. C. Jain et al. , ed. , 'Intelligent Biometric Techniques in Fingerprint and Face Recognition',1999,CRC Press, chapter 11, pp. 355–396.
  19. Sarala Ramkumar & Silambarasan Kaliamoorthi, "A Hybrid Approach to Face Recognition under Varying Illumination", IJCSET, April 2011, Vol. 1, Issue 3,113-117
  20. Rui Huang et al, " A Hybrid Face Recognition Method using Markov Random Fields".
Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition holistic approach feature based approach hybrid methods PCA LDA LFA FDA HMM