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Performance of Face Recognition Algorithms on Dummy Faces

  • Aruni Singh
  • Shrikant Tiwari
  • Sanjay Kumar Singh
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)

Abstract

Face recognition is becoming increasingly important in the contexts of computer vision, neuroscience, psychology, surveillance, credit card fraud detection, pattern recognition, neural network, content based video processing, assistive devices for visual impaired, etc. Face is a strong biometric trait for identification and hence criminals always try to hide their face by different artificial means such as plastic surgery, disguise and dummy. The availability of a comprehensive face database is crucial to test the performance of these face recognition algorithms. However, while existing publicly-available face databases contain face images with a wide variety of covariates such as poses, illumination, gestures and face occlusions but there is no dummy face database is available in public domain. The contributions of this paper are: i) Preparation of dummy face database of 50 subjects ii) Testing of face recognition algorithms on the dummy face database, iii) Critical analysis of four algorithms on dummy face database.

Keywords

Face recognition dummy faces biometrics 

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References

  1. 1.
    Introna, L.D., Nissenbaum, H.: Facial Recognition Technology. A Servey of Policy and Implementation Issues, CCPRGoogle Scholar
  2. 2.
    Zhao, W., Chellpa, R., Rosenfield, A., Phillips, P.J.: Face Recognition A Literature SurveyGoogle Scholar
  3. 3.
    Bert, P.J., Adelson, E.H.: The Laplacian Pyramid as Compact Image Code. IEEE Transaction on Communication, COM-31(4) (April 1983)Google Scholar
  4. 4.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Pearson Education (2009)Google Scholar
  5. 5.
    Givens, G., Beveridge, J.R., Draper, B.A., Grother, P., Phillips, P.J.: How Features of the Human Face Affect Recognition: A Statistical Comparison of Three Face Recognition Algorithms. In: Proc. IEEE Int’l Conf. Computer Vision and Pattern Recognition, vol. 2 (2004)Google Scholar
  6. 6.
    Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the Face Recognition Grand Challenge. In: Proc. IEEE Int’l Conf. on Computer Vision and Pattern Recognition, pp. 947–954 (2005)Google Scholar
  7. 7.
    Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face Recognition Algorithms. IEEE Transaction on PAMI 22(10), 1090–1104 (2000)CrossRefGoogle Scholar
  8. 8.
    Wang, P., Qiang, J., Wayman, J.L.: Modeling and Pridicting face recognition system Performance Based on analysis of similarity score. IEEE Transaction on PAMI 29 (2004)Google Scholar
  9. 9.
    Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: Face Evaluation Methodology for Face-Recognition Algorithms. Technical report NISTIR 6264 (January 1999)Google Scholar
  10. 10.
    Dong, H., Gu, N., Pohang: Asian Face Image Database PF01, Intelligent multimedia Lab. Technical Report, San 31, 790-784, KoreaGoogle Scholar
  11. 11.
    Dai, G., Qian, Y.: Face Recognition Using Novel LDA-Based AlgorithmsGoogle Scholar
  12. 12.
    Jain, A.K., Hong, L., Pankanti, S.: Biometric Identification. Communication of the ACM 43(2) (February 2000)Google Scholar
  13. 13.
    Belhumeur, P., Hespanha, J., Kriegman, D.: Eigenfaces vs Fisherfaces: class specific linear projection. IEEE Transactions on PAMI 19(7), 711–720 (1997)CrossRefGoogle Scholar
  14. 14.
    Martinez, A.M., Kak, A.C.: PCA versus LDA. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(2) (2001)Google Scholar
  15. 15.
    Turk, M., Pentland, A.: Eigenfaces for Recognition. J. Cognitive Neuroscience 3(1) (1991)Google Scholar
  16. 16.
    Samaria, F., Harter, A.: Parameterisation of a Stochastic Model for Human Face Identification. In: Proceedings of 2nd IEEE Workshop on Applications of Computer Vision, Sarasota FL (1994)Google Scholar
  17. 17.
    Sirvoich, L., Kirby, M.: A low dimensional Procedure for Characterization of Human Faces. J. Optical Soc. Am. A 4(3), 519–524 (1987)CrossRefGoogle Scholar
  18. 18.
    Cardoso, J.F.: Infomax and Maximum Likelihood for Source Separation. IEEE Letters on Signal Processing 4, 112–114 (1997)CrossRefGoogle Scholar
  19. 19.
    Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. John Wiley & Sons, New York (2001)CrossRefGoogle Scholar
  20. 20.
    Hyvärinen, A.: The Fixed-point Algorithm and Maximum Likelihood Estimation for Independent Component Analysis. Neural Processing Letters 10, 1–5 (1999)CrossRefGoogle Scholar
  21. 21.
    Liejun, W., Xizhong, Q., Taiyi, Z.: Facial Expression recognition using Support Vector Machine by modifying Kernels. Information Technology Journal 8, 595–599Google Scholar
  22. 22.
    Draper, B.A., Baek, K., Bartlett, M.S., Ross Beveridge, J.R.: Recognizing faces with PCA and ICA. Special issue on face recognitionGoogle Scholar
  23. 23.
    Swets, D.L., Weng, J.J.: Using Discriminant Eigenfaces for Image Retrival. IEEE Transaction on PAMI 18(8), 831–836 (1996)CrossRefGoogle Scholar
  24. 24.
    Yambor, W.S.: Analysis of Pca-Based and Fisher Discriminant-Based Image Recognition Algorithms. Technical Report CS-00-103 (July 2000)Google Scholar
  25. 25.
    Ahuja, M.S., Chhabra, S.: Effect of Distance Measures in Pca Based Face, Recognition. International Journal of Enterprise Computing and Business Systems 1(2) (2011) ISSN 2230-8849 (Online)Google Scholar
  26. 26.
    Agarwal, M., Jain, N., Kumar, M., Agrawal, H.: Face Recognition Using Eigen Faces and Artificial Neural Network. International Journal of Computer Theory and Engineering 2(4), 1793–8201 (2010)Google Scholar
  27. 27.
    Dagher, I.: Incremental PCA-LDA Algorithm. International Journal of Biometrics and Bioinformatics (IJBB) 4(2)Google Scholar
  28. 28.
    Draper, B.A., Baek, K., Bartlett, M.S., Ross Beveridge, J.: Recognizing Faces with PCA and ICAGoogle Scholar
  29. 29.
    Mazanec, J., Melisek, M., Oravec, M., Pavlovicov, J.: Support Vector Machines, Pca and Lda in Face Recognition. Journal of Electrical Engineering 59(4), 203–209 (2008)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Aruni Singh
    • 1
  • Shrikant Tiwari
    • 1
  • Sanjay Kumar Singh
    • 1
  1. 1.Department of Computer EngineeringIT-BHUVaranasiIndia

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