Efficient processing of MRFs for unconstrained-pose face recognition

IEEE 6th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2013

Volumn , Issue , 2013, Pages

  Arashloo, Shervin Rahimzadeh ^a   Kittler, Josef ^b  

^a URMIA UNIVERSITY   (Iran)

^b UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMETRICS; INFERENCE ENGINES; OPTIMIZATION; STATISTICAL MECHANICS;

DUAL DECOMPOSITION; EXPERIMENTAL EVALUATION; GRAPH CONSTRUCTION; MATCHING MODELS; MULTI-RESOLUTION APPROACH; NODE ATTRIBUTE; OPTIMISATIONS; STATE-OF-THE-ART PERFORMANCE;

FACE RECOGNITION;

EID: 84893721002     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BTAS.2013.6712721     Document Type: Conference Paper

References (58)

1. S. Arashloo, J. Kittler, and W. Christmas. Facial feature localization using graph matching with higher order statistical shape priors and global optimization. In Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, pages 1-8, 2010.
2. S. R. Arashloo and J. Kittler. Pose-invariant face matching using mrf energy minimization framework, page 5669. Springer, 2009.
3. S. R. Arashloo and J. Kittler. Energy normalization for pose-invariant face recognition based on mrf model image matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(6):1274- 1280, 2011.
4. S. R. Arashloo, J. Kittler, and W. J. Christmas. Pose-invariant face recognition by matching on multi-resolution mrfs linked by supercoupling transform. Comput. Vis. Image Underst., 115(7):1073- 1083, July 2011.
5. A. Ashraf, S. Lucey, and T. Chen. Learning patch correspondences for improved viewpoint invariant face recognition. In CVPR 2008, pages 1-8, June 2008.
6. A. Asthana, T. K. Marks, M. J. Jones, K. H. Tieu, and M. Rohith. Fully automatic pose-invariant face recognition via 3d pose normalization. Computer Vision, IEEE International Conference on, 937- 944, 2011.
7. H. Bay, T. Tuytelaars, and L. V. Gool. Surf: Speeded up robust features. In In ECCV, pages 404-417, 2006. (Pubitemid 44029795)
8. A. C. Berg and J. Malik. Geometric blur for template matching. In CVPR 2001, pages 607-614, 2001.
9. D. P. Bertsekas. Nonlinear Programming. Athena Scientific, 2nd edition, Sept. 1999.
10. V. Blanz and T. Vetter. Face recognition based on fitting a 3d morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25:2003, 2003.
11. M. Bober, M. Petrou, and J. Kittler. Nonlinear motion estimation using the supercoupling approach. IEEE Trans. Pattern Anal. Mach. Intell., 20(5):550-555, 1998. (Pubitemid 128741335)
12. K. Bonnen, B. Klare, and A. K. Jain. Component-based representation in automated face recognition. IEEE Transactions on Information Forensics and Security, 8(1):239-253, 2013.
13. Y. Boykov, O. Veksler, and R. Zabih. Fast approximate energy minimization via graph cuts. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 23(11):1222-1239, Nov. 2001. (Pubitemid 33137959)
14. A. Brunton, C. Shu, and G. Roth. Belief propagation on the gpu for stereo vision. In Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision, CRV '06. IEEE Computer Society, 2006.
15. C.-H. Chan. Multi-scale Local Binary Pattern Histogram for Face Recognition. PhD thesis, 2008.
16. T. Cootes, G. Edwards, and C. Taylor. Active appearance models. PAMI, IEEE Transactions on, 23(6):681-685, Jun 2001.
17. J. R. delSolar, R. Verschae, and M. Correa. Recognition of faces in unconstrained environments: A comparative study. EURASIP J. Adv. Signal Process, pages 1-19, 2009.
18. P. Felzenszwalb and D. Huttenlocher. Efficient belief propagation for early vision. I:261-268, 2004.
19. H. Gao, H. K. Ekenel, and R. Stiefelhagen. Pose normalization for local appearance-based face recognition. In Proceedings of the Third International Conference on Advances in Biometrics, ICB '09, pages 32-41, Berlin, Heidelberg, 2009. Springer-Verlag.
20. B. Gidas. A Renormalization Group Approach to Image Processing Problems. IEEE Trans. Pattern Anal. Mach. Intell., 11(2):164-180, Feb. 1989.
21. D. Gonzalez-Jimenez and J. Alba-Castro. Toward pose-invariant face recognition through point distribution models and facial symmetry. Information forensics and security, 2(3):413-429, 2007. (Pubitemid 47290576)
22. G. B. Huang, V. Jain, and E. Learned-Miller. Unsupervised Joint Alignment of Complex Images. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pages 1-8, 2007.
23. G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07-49, University of Massachusetts, Amherst, October 2007.
24. S. U. Hussain, T. Napoleon, and F. Jurie. Face Recognition using Local Quantized Patterns. In British Machive Vision Conference, page 11 pages, Guildford, United Kingdom, 2012.
25. T. Kanade and A. Yamada. Multi-subregion based probabilistic approach toward pose-invariant face recognition, 2003. ISCIRA, pages 954-959.
26. T. Kim and J. Kittler. Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image. PAMI, 27(3):318-327, 2005. (Pubitemid 40377325)
27. V. Kolmogorov. Convergent Tree-Reweighted Message Passing for Energy Minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10):1568-1583, Oct. 2006. (Pubitemid 46405078)
28. N. Komodakis. Towards More Efficient and Effective LP-Based Algorithms for MRF Optimization. In ECCV 2010, volume 6312 of Lecture Notes in Computer Science, chapter 38, pages 520-534. Springer Berlin/Heidelberg, 2010.
29. N. Komodakis, N. Paragios, and G. Tziritas. MRF energy minimization and beyond via dual decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33:531-552, 2011.
30. D. G. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60(2):91-110, Nov. 2004.
31. K. Messer, J. Matas, J. Kittler, and K. Jonsson. Xm2vtsdb: The extended m2vts database. In In Second International Conference on Audio and Video-based Biometric Person Authentication, pages 72- 77, 1999.
32. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis & Machine Intelligence, 27(10):1615-1630, 2005. (Pubitemid 41555406)
33. E. Nowak. Learning visual similarity measures for comparing never seen objects. In Proc. IEEE CVPR, 2007.
34. T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. PAMI, IEEE Transactions on, 24(7):971-987, Jul 2002. (Pubitemid 34835471)
35. N. Osia and T. Bourlai. Holistic and partial face recognition in the mwir band using manual and automatic detection of face-based feature, 2012. IEEE International Conference on Technologies for Homeland Security,, Waltham, MA, U.S.A.
36. B.-G. Park, K.-M. Lee, and S.-U. Lee. Face recognition using face- ARG matching. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 27(12):1982-1988, 2005. (Pubitemid 43051394)
37. A. Pentland, B. Moghaddam, and T. Starner. View-based and modular eigenfaces for face recognition, 1994. CVPR, pages 84-91.
38. J. P. 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.
39. N. Pinto, J. J. DiCarlo, and D. D. Cox. How far can you get with a modern face recognition test set using only simple features? In IEEE Computer Vision and Pattern Recognition, 2009.
40. S. Prince, J. Warrel, J. Elder, and F. Felisberti. Appearance based face recognition and light fields. PAMI, 26(4):449-465, 2004.
41. C. Sanderson and B. C. Lovell. Multi-Region Probabilistic Histograms for Robust and Scalable Identity Inference. In M. Tistarelli and M. S. Nixon, editors, ICB, volume 5558 of Lecture Notes in Computer Science, pages 199-208. Springer, 2009.
42. H. J. Seo and P. Milanfar. Face verification using the lark representation. IEEE Transactions on Information Forensics and Security, 6(4):1275-1286, 2011.
43. G. Sharma, S. Ul Hussain, and F. Jurie. Local Higher-Order Statistics (LHS) for Texture Categorization and Facial Analysis. In ECCV - European Conference on Computer Vision, Florence, Italie, Aug. 2012.
44. A. Shekhovtsov, I. Kovtun, and V. Hlavac. Efficient MRF deformation model for non-rigid image matching. Computer Vision and Image Understanding, 112:91-99, 2008.
45. R. Singh, M. Vatsa, A. Ross, and A. Noore. A mosaicing scheme for pose-invariant face recognition. Systems, man and Cybernetics, 37(5):1212-1225, 2007. (Pubitemid 47541885)
46. P. Strandmark, F. Kahl, and T. Schoenemann. Parallel and distributed vision algorithms using dual decomposition. Comput. Vis. Image Underst., 115(12):1721-1732, Dec. 2011.
47. T. Suzuki, Y. Amano, and T. Hashizume. Picking the best daisy. SICE Annual Conference 2010 Proceedings of, pages 2960-2964, 2010.
48. X. Tan and B. Triggs. Enhanced local texture feature sets for face recognition under difficult lighting conditions. In AMFG, pages 168- 182, 2007.
49. J. Tena, R. Smith, M. Hamouz, J. Kittler, A. Hilton, and J. Illingworth. 2d face pose normalisation using a 3d morphable model. In International Conference on Video and Signal Based Surveillance, pages 1-6, September 2007.
50. E. Tola, V. Lepetit, and P. Fua. Daisy: An efficient dense descriptor applied to wide baseline stereo. IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 32(5), 2010.
51. M. A. Turk and A. P. Pentland. Face recognition using eigenfaces. In Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 586-591. IEEE Comput. Sco. Press, 1991.
52. M. Wainwright, T. Jaakkola, and A. Willsky. Map estimation via agreement on trees: message-passing and linear programming. Information Theory, IEEE Transactions on, 51(11):3697-3717, Nov. 2005. (Pubitemid 41622574)
53. R. Wang, Z. Lei, M. Ao, and S. Li. Bayesian face recognition based on markov random field modeling, 2009. ICB, pages 42-51.
54. T. Werner. Revisiting the linear programming relaxation approach to gibbs energy minimization and weighted constraint satisfaction. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(8):1474- 1488, August 2010.
55. L. Wiskott, J. Fellous, N. Kuiger, and C. von der Malsburg. Face recognition by elastic bunch graph matching. PAMI, 19(7):775-779, 1997. (Pubitemid 127762270)
56. L. Wolf, T. Hassner, and Y. Taigman. Y.: Descriptor based methods in the wild. In In: Faces in Real-Life Images Workshop in ECCV. (2008) (b) Similarity Scores based on Background Samples. 6
57. L. Wolf, T. Hassner, and Y. Taigman. Similarity Scores based on Background Samples. In Asian Conference on Computer Vision (ACCV), 2009.
58. W. Zhao, R. Chellappa, A. Rosenfeld, and P. J. Phillips. Face Recognition: A Literature Survey. ACM Computing Surveys, pages 399- 458, 2003.