Facial biometrics using nontensor product wavelet and 2d discriminant techniques

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 23, Issue 3, 2009, Pages 521-543

  Zhang, Dan ^a   You, Xinge ^b   Wang, Patrick ^c   Yanushkevich, Svetlana N ^d   Tang, Yuan Yan ^a  

^a HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^c Northeastern University   (United States)

^d UNIVERSITY OF CALGARY   (Canada)

Author keywords

Face recognition; Nontensor product wavelet; Two dimensional component analysis

Indexed keywords

BIVARIATE; FACIAL EXPRESSIONS; FACIAL FEATURE; FEATURE VECTORS; FREQUENCY COMPONENTS; HIGH FREQUENCY COMPONENTS; ILLUMINATION CHANGES; LINEAR DISCRIMINANTS; LOW-FREQUENCY COMPONENTS; NONTENSOR PRODUCT WAVELET; TENSOR PRODUCTS; TWO-DIMENSIONAL COMPONENT ANALYSIS;

BIOMETRICS; SUPPORT VECTOR MACHINES; TENSORS; TWO DIMENSIONAL;

FACE RECOGNITION;

EID: 67650694969     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001409007260     Document Type: Article

References (52)

1. R. Bolle, J. Connell, S. Pankanti, N. Ratha and A. Senior, Guide to Biometrics (Springer, 2004).
2. R. Brunelli and T. Poggio, Face recognition: features versus templates, IEEE Trans. PAMI 15(10) (1993) 1042-1052.
3. Q. Chen, C. A. Micchelli, S. Peng and Y. Xu, Multivariate filter banks having a matrix factorization, SIAM J. Matrix Anal. Appl. 25(2) (2003) 517-531.
4. Q. Chen, C. A. Micchelli and Y. Xu, Biorthogonal wavelet filter banks from block centrally symmetric matrix, Linear. Algeb. Appl. 402 (2005) 111-125.
5. C. Chen and P. Wang, Handbook of Pattern Recognition and Computer Vision (World Scientific, 2005).
6. J. T. Chien and C. C. Wu, Discriminant waveletfaces and nearest feature classifiers for face recognition, IEEE Trans. Patt. Anal. Mach. Intell. 24(12) (2002) 1644-1649.
7. A. Cohen and I. Daubechies, Non-separable bidimensional wavelet bases, Rev. Mat. Iberoamericana 9 (1993) 51-137.
8. T. Cooke, Two variations on Fisher's linear discriminant for pattern recognition, IEEE Trans. PAMI 24(2) (2002) 268-273.
9. I. Daubechies, Ten Lectures on Wavelets, Society for Industrial and Applied Mathemathics, Philadelphia (1992).
10. H. K. Ekenel and B. Sanker, Multiresolution face recognition, Imag. Vis. Comput. 23 (2005) 469-477.
11. P. Ekman and E. L. Rosenberg, What the Face Reveals: Basic and Applied Studues of Spontaneouse Expression Using the Facial Action Coding System (FACS) (Oxford University Press, 1997).
12. K. Etemad and R. Chellappa, Discriminant analysis for recognition of human, J. Opt. Soc. Am. A 14(8) (1997) 1724-1734.
13. G. C. Feng, P. C. Yuen and D. Q. Dai, Human face recognition using PCA on wavelet subband, J. Electron. Imag. 9(2) (2000) 226-233.
14. H.-H. Gao, H.-H. Yang and X.-Y. Wang, Kernel PCA based network inrusion feature extraction and dectection using svm, Proc. ICNC, Lecture Notes in Computer Science, Vol. 3611 (2005), pp. 89-94.
15. C. Garcia, G. Zikos and G. Tziritas, A wavelet-based framework for face recognition, Proc. Workshop on Advances in Facial Image Analysis and Recognition Technology, 5th European Conference on Computer Vision (ECCV'98) (1998), pp. 84-92.
16. W. He and M. J. Lai, Examples fo bivariate nonseparable compactly supported continuous wavelets, IEEE Trans. Imag. Process. 9(8) (2000) 949-953.
17. A. Jain, R. Bolle and S. Pankanti, Biometrics: Personal Identification in a Networked Society (Kluwer, 1999).
18. R. Q. Jia and C. A. Micchelli, Using the refinement equation for the construction of prewavelets V: extensibility of trigonometric polynomials, Computing 48 (1992) 61-72.
19. M. Kirby and L. Sirovich, Application of the KL procedure for the characterization of human faces, IEEE Trans. Patt. Anal. Mach. Intell. 12(1) (1990) 103-108.
20. C. Kotropoulos A. Tefas and L. Pitas, Using support vector machines to enhance the perfornance of elastic graph matching for frontal face authentication, IEEE Trans. PAMI 23(7) (2001) 735-746.
21. n, IEEE Trans. Inform. Th. 38 (1992) 533-555.
22. G. Lanckriet, A. Lambrechts, B. D. Moor, T. V. Gestel, J. Suykens and J. Vandewalle, Bayesian framework for least squares support vector machine classifiers, Gaussian processes and Kernel fisher discriminant analysis, Neural Computation (2002).
23. S.-W. Lee, P. S. P. Wang, S. N. Yanushkevich and S. W. Lee, Noniterative 3D face reconstruction based on photometric stereo, Int. J. Patt. Recogn. Artif. Intell. 22(3) (2008) 389-410.
24. Y. Luo, M. L. Gavrilova, M. C. Sousa, J. Pivovarov and S. Yanushkevich, Simulation of biometric information: the new generation of biometric systems, Proc. Int. Workshop Modeling and Simulation in Biometric Technology, Calgary, Canada (2004), pp. 87-98.
25. Y. Ma, M. Schuckers and B. Cukic, Guidelines for appropriate use of simulated data for bio-authentication research, Proc. 4th IEEE Workshop Automatic Identification Advanced Technologies, Buffalo, New York (2005), pp. 251-256.
26. T. Moriyama, T. Kanade J. Xiao and J. F. Cohn, Meticulously detailed eye model and its application to analysis of facial image, Proc. IEEE Int. Conf. Syst. Man Cybern. 24(3) (2004) 629-634.
27. K. Muller, B. Scholkopf and A. Smola, Kernel principle component analysis, Advances in Kernel Methods - Support Vector Learning, eds. B. Scholkopf, C. Burges and A. Smola (MIT Press 1999), pp. 327-352.
28. C. Nastar, The image shape spectrum for image retrieval, Technical Report, INRIA, No. 3206 (June 1997).
29. C. Nastar, B. Moghaddam and A. Pentland, Flexible images: matching and recognition using learned deformations, Comput. Vis. Imag. Underst. 65(2) (1997) 179-191.
30. V. D. M. Nhat and S. Lee, Line-based PCA and LDA approaches for face recognition, Proc. ICNC, Lecture Notes in Computer Science, Vol. 3611 (2005), pp. 101-104.
31. N. M. Orlans, D. J. Buettner and J. Marques, A survey of synthetic biometrics: capabilities and benefits, Proc. Int. Conf. Artificial Intelligence (CSREA Press, 2004), pp. 499-505.
32. M. Pantic and L. J. M. Rothkrantz, Automatic analysis of facial expressions: the state-of-the-art, IEEE Trans. PAMI 22(12) (2000) 1424-1445.
33. N. Ratha, J. Connell and R. Bolle, Enhancing security and privacy in biometrics-based authentication systems, IBM Syst. J. 40(3) (2001) 614-634.
34. S. D. Riemenschneider, R. Q. Jia and D. X. Zhou, Smoothness of multiple refinable functions and multiple wavelets, SIAM J. Matrix Anal. Appl. 21 (1999) 1-28.
35. A. Ross, K. Nandakumar and A. Jain, Handbook of multibiometrics, Int. Series on Biometrics, Springer (June 2006).
36. M. Safari, M. T. Harandi and B. N. Araabi, A SVM-based method for face recognition using a wavelet PCA representation of faces, Proc. IEEE Int. Conf. Image Processing, Singapore (2004), pp. 24-27.
37. C. Sanchez-Avila and R. Sanchez-Reillo, Iris-based biometric recognition using dyadic wavelet transform, IEEE Aerosp. Electron. Syst. Mag. 24(3) (2002) 3-6.
38. V. Shmerko, P. Phillips, G. Kukharev, W. Rogers and S. Yanushkevich, Biometric technologies, Proc. Int. Conf. Biometrics: fraud Prevention, Enchanced Service, Las Vegas, Nevada (1997), pp. 270-286.
39. L. Sirovich and M. Kirby, Low-dimensional procedure for characterization of human faces, J. Opt. Soc. Am. 4 (1987) 519-524.
40. M. Turk and A. Pentland, Eigenfaces for recognition, J. Cogn. Neurosci. 3(1) (1991) 71-86.
41. M. Vetterli, Filter banks allowing perfect reconstruction, Signal Proc. 10(3) (1986) 219-244.
42. J. Wayman, A. Jain, D. Maltoni and D. Maio, Biometric systems technology, design and performance evaluation (Springer, 2005).
43. W. S. Yambor, Analysis of PCA-based and Fisher discriminant-based image recognition, Technical Report, Department of Computer Science, Colorado State University (2000).
44. J. Yang, D. Zhang, A. F. Frangi and J. Y. Yang, Two-dimensional PCA: a new approach to appearance-based face representation and recognition, IEEE Trans. PAMI 26(1) (2004) 131-137.
45. S. N. Yanushkevich, A. Stoica, V. P. Shmerko and D. V. Popel, Biometric Inverse Problems (Taylor & Francis/CRC Press, Boca Raton, FL., 2005).
46. S. N. Yanushkevich, A. Stoica, S. N. Srihari, V. P. Shmerko and M. L. Gavrilova, Simulation of biometric information: the new generation of biometric systems, Proc. Int. Workshop Modeling and Simulation in Biometric Technology, Calgary, Canada (2004), pp. 87-98.
47. X. You, Q. Chen, D. Zhang, P. Wang and Y. Y. Tang, Face recognition based on new non-separable wavelet, Technical Report, Deparment of Computer Science, Hong Kong Baptist University (January 2007).
48. X. You, L. Du, Q. Chen and Y. Cheung, Significant difference watermarking using new non-tensor wavelet filter banks, Technical Report, Department of Electronics and Information, Huazhong University of Science and Technology, 2007.
49. X. You, D. Zhang, Q. Chen, P. Wang and Y. Y. Tang, Face representation by using non-tensor product wavelets, 18th Int. Conf. Patt. Recogn. (2006), pp. 503-506.
50. W. Zhao and R. Chelappa, Face Processing: Advanced Modeling and Methods (Elsevier, 2006).
51. B. L. Zhang, H. H. Zhang and S. S. Ge, Face recognition by applying wavelet subband representation and Kernel associative memory, IEEE Trans. Neural Networks 15(1) (2004) 166-177.
52. Z. B. Zhang, S. L. Ma and D. Y. Wu, The application of neural network and wavelet in human face illumination compensation, Proc. Adv. Neural Networks (2005), pp. 828-835.