Aguará: An improved face recognition algorithm through gabor filter adaptation

2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings

Volumn , Issue , 2007, Pages 74-79

  Aguerrebere, C ^a   Capdehourat, G ^a   Delbracio, M ^a   Mateu, M ^a   Fernandez A ^a   Lecumberry, F ^a  

^a UNIVERSIDAD DE LA REPÚBLICA   (Uruguay)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; DIGITAL FILTERS; POWER SPECTRAL DENSITY;

EBGM-BASED ALGORITHM; FERET DATABASE; GABOR FILTERS;

FACE RECOGNITION;

EID: 34748846498     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AUTOID.2007.380596     Document Type: Conference Paper

References (15)

1. D. S. Bolme. Elastic bunch graph matching. Master's thesis, Colorado State University, Fort Collins, Colorado, USA, 2003.
2. D.J. Field. Relations between the statistics of natural images and the response profiles of cortical cells. In Journal of the Optical Society of America., volume 4, pages 2379-2394, 1987.
3. B. Kepenekci, F. B. Tek, and G. B. Akar. Occluded face recognition by using gabor features. In 3rd COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, Budapest, October 2002.
4. M. Kirby and L. Sirovich. Application of the Karhunen-Loève procedure for the characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(1):103-108, 1990.
5. M. Lades, J. C. Vorbrüggen, J. Buhmann, J. Lange, C. von der Malsburg, R. P. Würtz, and W. Konen. Distortion invariant object recognition in the dynamic link architecture. IEEE Transactions on Computers, 42:300-311, 1993.
6. B. Moghaddam, C. Nastar, and A. Pentland. Bayesian face recognition using deformable intensity surfaces. In Proceedings of the 15th Computer vision and Pattern Recognition Conference, ICVPR '96, 1996.
7. V. Perlibakas. Face recognition using principal component analysis and log-gabor filters. Image Processing and Analysis Laboratory, Computational Technologies Centre, 2006.
8. P. J. Phillips, H. Moon, S. A. Rizvi, and P. J. Rauss. The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10):1090-1104, 2000.
9. S. Rizvi, P. Phillips, and H. Moon. The FERET verification testing protocol for face recognition algorithms. Image and Vision Computing Journal, 1999.
10. M. L. Teixeira. The bayesian intrapersonal/extrapersonal classifier. Master's thesis, Colorado State University, Fort Collins, Colorado, USA, 2003.
11. M. Turk and A. P. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.
12. A. van der Schaaf. Modelling the power spectra of natural images: Statistics and information. In Natural image statistics and visual processing, chapter 2. Graduate School for Behavioural and Cognitive Neurosciences, University of Groningen.
13. L. Wiskott, J.-M. Fellous, N. Krüger, and C. von der Malsburg. Face recognition by elastic bunch graph matching. In L. C. Jain, U. Halièi, I. Hayashi, and S. B. Lee, editors, Intelligent Biometric Techniques in Fingerprint and Face Recognition, chapter 11, pages 355-396. CRC Press, 1999.
14. W. Zhao, R. Chellappa, and A. Krishnaswamy. Discriminant analysis of principal components for face recognition. In Proceedings of the 3rd International Conference on Automatic Face and Gesture Recognition, FG '98, pages 336-341, Nara, Japan, April 14-16 1998.
15. W. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld. Face recognition: A literature survey. ACM Computing Surveys, 35(4):399-458, 2003.