Interest Operator versus Gabor filtering for facial imagery classification

Pattern Recognition Letters

Volumn 28, Issue 8, 2007, Pages 950-956

  Cǎleanu, Cǎtǎlin ^a   Huang, De Shuang ^b   Gui, Vasile ^a   Tiponuţ, Virgil ^a   Maranescu, Valentin ^a  

^a POLITEHNICA UNIVERSITY OF TIMISOARA   (Romania)

^b INSTITUTE OF INTELLIGENT MACHINES   (China)

Author keywords

2D face recognition; Gabor filters; Interest Operator; Statistical and neural classifiers

Indexed keywords

FACE RECOGNITION; FEATURE EXTRACTION; MOBILE ROBOTS; PROBLEM SOLVING; STEREO VISION;

FACIAL RECOGNITION; GABOR FILTERING; IMAGERY CLASSIFICATION; STEREOSCOPIC VISION;

ADAPTIVE FILTERING;

EID: 33947167664     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2006.12.013     Document Type: Article

References (30)

1. Barrett W.A. A survey of face recognition algorithms and testing results. Syst. Comput. 1 (1998) 301-305
2. Brunelli, R., Poggio, T., 1992. Face recognition through geometrical features. In: Proc. of European Conf. Computer Vision (ECCV), pp. 792-800.
3. Cǎleanu, C.D., 2000. Facial Recognition using Committee of Neural Networks. In: Proc. 5th Seminar on Neural Network Applications in electrical engineering, NEUREL 2000, Belgrade, Yugoslavia, pp. 97-100.
4. Cǎleanu, C.D., 2001. Face recognition using parallel neural processing and interest operator method. Ph.D. thesis. University POLITEHNICA Timisoara.
5. Cesar, R., Bengoetxea, E., Bloch, I., 2002. Inexact graph matching using stochastic optimization techniques for facial feature recognition. In: Proc. Int. Conf. Pattern Recognition (ICPR), Quebec, Canada.
6. Daugman J.G. Uncertainty relation for resolution in space, spatial frequency and orientation optimized by 2D visual cortical filters. J. Opt. Soc. Am. 2 7 (1985) 1160-1169
7. Ekenel H.K., and Sankur B. Multiresolution face recognition. Image Vision Comput. 23 (2005) 1-9
8. Gabor D. Theory of communications. J. Int. Electr. Eng. 93 (1946) 427-457
9. Guo G., Li S.Z., and Chan K.L. Support vector machines for face recognition. Image Vision Comput. 19 (2001) 631-638
10. Haykin S. Neural Networks: A Comprehensive Foundation. second ed. (1999), Prentice Hall, Upper Saddle River, NJ
11. Hu, Y., Jiang, D., Yan, S. Zhang, L., Zhang, H., 2004. Automatic 3D reconstruction for face recognition. In: Proc. Sixth IEEE Int. Conf. on Automatic Face and Gesture Recognition, pp. 843-848.
12. Kamarainen, J.-K., Kyrki, V., Hamouz, M., Kittler, J., Kälviäinen, H., 2002. Invariant Gabor features for face evidence extraction. In: Proc. of the IAPR Workshop on Machine Vision Applications. Nara, Japan, pp. 228-231.
13. Kyrki, V., 2002. Local and global feature extraction for invariant object recognition. Ph.D. thesis. Lappeenranta University of Technology.
14. Kyrki, V., Kamarainen, J.-K., Kälviäinen, H., 2001. Content based image matching using Gabor filtering. In: Proc. of the Int. Conf. on Advanced Concepts for Intelligent Vision Systems Theory and Applications. Baden-Baden, Germany, pp. 45-49.
15. Lawrence I.S., Giles C.L., Tsoi A.C., and Bock A.D. Face recognition: A convolutional neural-network approach. IEEE Trans. Neural Networks 8 (1997) 98-113
16. Lin S.H., Kung S.Y., and Lin L.J. Face recognition/detection by probabilistic decision-based neural networks. IEEE Trans. Neural Networks 8 (1997) 113-114
17. Liu, C., Wechsler, H., 2001. A Gabor feature classifier for face recognition. In: Proc. of Eighth IEEE Int. Conf. on Computer Vision 2, July 7-14, pp. 270-275.
18. Mitchell T. Machine Learning (1997), McGraw Hill
19. Moller A.F. A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks 6 (1993) 525-533
20. Moravec H. Robot Rover Visual Navigation (1981), University of Michigan Research Press, Ann Arbor, MI
21. Nasrabadi N.M., and Choo C.Y. Hopfield Network for Stereo Vision Correspondence. In: Gupta M., and Knopf G. (Eds). Neuro-Vision Systems. Principles and Applications (1994), IEEE Press 442-449
22. Pentland A. Looking at people: sensing for ubiquitous and wearable computing. IEEE Trans. Pattern Anal. Mach. Intell. 22 1 (2000) 107-119
23. Pessoa L., and Leitao A.P. Complex cell prototype representation for face recognition. IEEE Trans. Neural Networks 10 6 (1999) 1528-1531
24. Sato, K., Shah, S., Aggarwal, L.J., 1998. Partial Face Recognition using Radial Basis Function Network. In: Proc. of the third IEEE Int. Conf. on Automatic Face and Gesture Recognition, Nara, Japan, April 14-16, pp. 288-292.
25. Turk M.A., and Pentland A.P. Eigenfaces for recognition. J. Cognit. Neurosci. 3 1 (1991) 71-86
26. Wang L.C., Der S.Z., and Nasrabadi N.M. Automatic target recognition using a feature-decomposition and data-decomposition modular neural network. IEEE Trans. Image Process. 7 8 (1998) 1113-1121
27. Wei, S.D., Lai, S.H., 2004. Robust face recognition under lighting variations. In: Proc. of the 17th Int. Conf. on Pattern Recognition, vol. 1, pp. 354-357.
28. Wiskott L., Fellous J.M., Kruger N., and Von der Malsburg C. Face Recognition by Elastic Bunch Graph Matching. Intelligent Biometric Techniques in Fingerprint and Face Recognition (1999), Springer-Verlag
29. Zhao W., Chellappa R., Rosenfeld A., and Phillips P.J. Face Recognition: A Literature Survey. ACM Comput. Surveys 35 4 (2003) 399-458
30. Zhao Z.Q., Huang D.S., and Sun B.Y. Human face recognition based on multi-features using neural networks committee. Pattern Recognit. Lett. 25 12 (2004) 1351-1358