Face recognition with learning-based descriptor

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2010, Pages 2707-2714

  Cao, Zhimin ^a   Yin, Qi ^b   Tang, Xiaoou ^a,c   Sun, Jian ^d  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b TSINGHUA UNIVERSITY   (China)

^c SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^d MICROSOFT RESEARCH ASIA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE MATCHING; DATA SETS; DESCRIPTORS; DISCRIMINATIVE ABILITY; ENCODING METHODS; FACE DESCRIPTOR; FACE REPRESENTATIONS; GENERALIZATION ABILITY; POSE VARIATION; RECOGNITION RATES; TRAINING EXAMPLE;

COMPUTATIONAL METHODS; COMPUTER VISION; ENCODING (SYMBOLS);

FACE RECOGNITION;

EID: 77955988832     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5539992     Document Type: Conference Paper

References (33)

1. T. Ahonen, A. Hadid, and M. Pietikainen. Face Recognition with Local Binary Patterns. Lecture Notes in Computer Science, pages 469-481, 2004.
2. T. Ahonen and M. Pietikäinen. Image description using joint distribution of filter bank responses. Pattern Recognition Letters, 30(4):368-376, 2009.
3. V. Blanz and T. Vetter. Face recognition based on fitting a 3D morphable model. IEEE Transactions on pattern analysis and machine intelligence, 25(9):1063-1074, 2003.
4. C. Chang and C. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www. csie. ntu. edu. tw/cjlin/libsvm, 2001.
5. J. Cui, F. Wen, R. Xiao, Y. Tian, and X. Tang. Easy Album: an interactive photo annotation system based on face clustering and re-ranking. In Proc. of the SIGCHI conference on human factors in computing systems, page 376, 2007.
6. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proc. CVPR, 2005.
7. Y. Freund, S. Dasgupta, M. Kabra, and N. Verma. Learning the structure of manifolds using random projections. In NIPS, 2007.
8. R. Gross, I. Matthews, J. Cohn, T. Kanade, and S. Baker. Multi-PIE. In International Conference on Automatic Face and Gesture Recognition, 2008.
9. M. Guillaumin, J. Verbeek, C. Schmid, I. LEAR, and L. Kuntzmann. Is that you? Metric learning approaches for face identification. In Proc. ICCV, 2009.
10. G. Hua and A. Akbarzadeh. A robust elastic and partial matching metric for face recognition. In Proc. ICCV, 2009.
11. P. Hua, G. Viola and S. Drucker. Face recognition using discriminatively trained orthogonal rank one tensor projections. In Proc. CVPR, 2007.
12. G. Huang, M. Ramesh, T. Berg, and E. Learned-Miller. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. University of Massachusetts, Amherst, Technical Report 07-49, 2007.
13. N. Kumar, A. Berg, P. Belhumeur, and S. Nayar. Attribute and Simile classifiers for face verification. In Proc. ICCV, 2009.
14. T. Leung and J. Malik. Representing and recognizing the visual appearance of materials using three-dimensional textons. International Journal of Computer Vision, 43(1):29-44, 2001.
15. L. Liang, R. Xiao, F. Wen, and J. Sun. Face Alignment via Component-based Discriminative Search. In Proc. ECCV, 2008.
16. D. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110, 2004.
17. T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on pattern analysis and machine intelligence, 24(7):971-987, 2002.
18. P. Phillips, H. Moon, S. Rizvi, and P. Rauss. The FERET evaluation mthodology for face-recognition algorithms. IEEE Transactions on pattern analysis and machine intelligence, 22(10):1090-1104, 2000.
19. N. Pinto, J. DiCarlo, and D. Cox. How far can you get with a modern face recognition test set using only simple features. In Proc. CVPR, 2009.
20. Y. Taigman, L. Wolf, T. Hassner, and I. Tel-Aviv. Multiple One-Shots for utilizing class label information. In BMVC, 2009.
21. X. Tan and B. Triggs. Enhanced local texture feature sets for face recognition under difficult lighting conditions. Lecture Notes in Computer Science, 4778:168, 2007.
22. E. Tola, V. Lepetit, and P. Fua. A fast local descriptor for dense matching. In Proc. CVPR, 2008.
23. M. Turk and A. Pentland. Face Recognition using Eigenfaces. In Proc. CVPR, 1991.
24. M. Varma and A. Zisserman. Texture classification: Are filter banks necessary? In Proc. CVPR, 2003.
25. X. Wang and X. Tang. A unified framework for subspace face recognition. IEEE Transactions on pattern analysis and machine intelligence, 26(9):1222-1228, 2004.
26. X. Wang and X. Tang. Random sampling for subspace face recognition. International Journal of Computer Vision, 70(1):91-104, 2006.
27. S. Winder and M. Brown. Learning local image descriptors. In Proc. CVPR, 2007.
28. S. Winder, G. Hua, and M. Brown. Picking the best DAISY. In Proc. CVPR, 2009.
29. L. Wiskott, J. Fellous, N. Krüger, and C. Von der Malsburg. Face recognition by elastic bunch graph matching. IEEE Transactions on pattern analysis and machine intelligence, 19(7):775-779, 1997.
30. L. Wolf, T. Hassner, and Y. Taigman. Descriptor based methods in the wild. In Faces in Real-Life Images Workshop in ECCV, 2008.
31. L. Wolf, T. Hassner, and Y. Taigman. Similarity scores based on background samples. In Proc. ACCV, 2009.
32. J. Wright and G. Hua. Implicit elastic matching with random projections for pose-variant face recognition. In Proc. CVPR, 2009.
33. L. Zhang, R. Chu, S. Xiang, S. Liao, and S. Li. Face detection based on multi-block lbp representation. Lecture Notes in Computer Science, 4642:11, 2007.