Making the most of the self-quotient image in face recognition

2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013

Volumn , Issue , 2013, Pages

  Arandjelovic, Ognjen ^a  

^a DEAKIN UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC FACE RECOGNITION; BIOLOGICALLY INSPIRED; DISSIMILARITY MEASURES; FACIAL EXPRESSIONS; ILLUMINATION CHANGES; ILLUMINATION INVARIANT; RETRIEVAL SYSTEMS; SELF-QUOTIENT IMAGE;

FACE RECOGNITION;

EID: 84881506442     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FG.2013.6553708     Document Type: Conference Paper

References (30)

1. S. M. Mavadati, M. T. Sadeghi, and J. Kittler. Fusion of visible and synthesized near infrared information for face authentication. ICIP, pages 3801-3804, 2010.
2. Y. Yan and Y-J. Zhang. Encyclopedia of Artificial Intelligence, chapter State-of-the-Art on Video-Based Face Recognition, pages 1455-1461. IGI Global, 2009.
3. M. Everingham, J. Sivic, and A. Zisserman. Taking the bite out of automatic naming of characters in TV video. IVC, 27(5)545-559, 2009.
4. O. Arandjelovic and A. Zisserman. Automatic face recognition for film character retrieval in feature-length films. CVPR, 1860-867, 2005.
5. V. Blanz, S. Romdhani, and T. Vetter. Face identification across different poses and illuminations with a 3D morphable model. FG, pages 202-207, 2002.
6. S. Zhou, G. Aggarwal, R. Chellappa, and D. Jacobs. Appearance characterization of linear lambertian objects, generalized photometric stereo, and illumination-invariant face recognition. TPAMI, 29(2)230-245, 2007.
7. N. Faggian, A. Paplinski, and T-J. Chin. Face recognition from video using active appearance model segmentation. ICPR, pages 287-290, 2006.
8. R. Gross, I. Matthews, and S. Baker. Active appearance models with occlusion. IVC, 1(6)593-604, 2006.
9. C. Shan. Video Search and Mining, chapter Face Recognition and Retrieval in Video, pages 235-260. Springer, 2010.
10. B. V. K. Vijayakumar, X. Chunyan, and S. Marios. Correlation filters for large population face recognition. SPIE, 653965390F1-65390F12, 2007.
11. M. Nishiyama and O. Yamaguchi. Face recognition using the classified appearance-based quotient image. FG, pages 49-54, 2006.
12. B. Duc, S. Fischer, and J. Bigun. Face authentication with Gabor information on deformable graphs. TIP, 8(4)504-516, 1999.
13. C. Kotropoulos, A. Tefas, and I. Pitas. Frontal face authentication using morphological elastic graph matching. TIP, 9(4)555-560, 2000.
14. D. S. Bolme. Elastic bunch graph matching. Master's thesis, Colorado State University, 2003.
15. S. Arca, P. Campadelli, and R Lanzarotti. A face recognition system based on local feature analysis. LNCS, 2688182-189, 2003.
16. M. S. Bartlett, J. R. Movellan, and T. J. Sejnowski. Face recognition by independent component analysis. TNN, 13(6)1450-1464, 2002.
17. Y. Wang, Y. Jia, C. Hu, and M. Turk. Non-negative matrix factorization framework for face recognition. IJPRAI, 19(4)495-511, 2005.
18. O. G. Sezer, Y. Altunbasak, and A. Ercil. Face rec ognition with independent component based super-resolution. VCIP, 2006.
19. A. Stergiou, A. Pnevmatikakis, and L. Polymenakos. EBGM vs. subspace projection for face recognition. VISAPP, 2006.
20. O. Arandjelovic and R. Cipolla. Automatic cast listing in feature-length films with anisotropic manifold space. CVPR, 21513-1520, 2006.
21. E. H. Land. The retinex theory of color vision. Scientific American, 237(6)108-128, 1977.
22. R. Gross, I. Matthews, and S. Baker. An image preprocessing algorithm for illumination invariant face recognition. AVBPA, pages 10-18, 2003.
23. H. Wang, S. Z. Li, and Y. Wang. Generalized quotient image. CVPR Workshops, pages 819-824, 2004.
24. T. Chen, W. Yin, X. Zhou, D. Comaniciu, and T. Huang. Total variation models for variable lighting face recognition. TPAMI, 28(9)1519-1524, 2006.
25. A. S. Georghiades, P. N. Belhumeur, and D. J. Kriegman. From few to many Illumination cone models for face recognition under variable lighting and pose. TPAMI, 23(6)643-660, 2001.
26. K. Lee, J. Ho, and D. Kriegman. Nine points of light Acquiring subspaces for face recognition under variable lighting. CVPR, 1519-526, 2003.
27. X. Xie and K.-M. Lam. Face recognition under varying illumination based on a 2D face shape model. PR, 38(2)221-230, 2005.
28. P. Dunker and M. Keller. Illumination normalization for face recognition-A comparative study of conventional vs. perception-inspired algorithms. BIOSIGNALS, 2237-243, 2008.
29. O. Arandjelovic and R. Cipolla. A new look at filtering techniques for illumination invariance in automatic face recognition. FG, pages 449-454, 2006.
30. Y Adini, Y. Moses, and S. Ullman. Face recognition The problem of compensating for changes in illumination direction. TPAMI, 19(7)721-732, 1997.