Locality versus globality: Query-driven localized linear models for facial image computing

IEEE Transactions on Circuits and Systems for Video Technology

Volumn 18, Issue 12, 2008, Pages 1741-1752

  Fu, Yun ^a   Li, Zhu ^b   Yuan, Junsong ^c   Wu, Ying ^c   Huang, Thomas S ^d  

^a BBN TECHNOLOGIES   (United States)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c Northwestern University   (United States)

^d UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Discriminating power coefficient (DPC); Face recognition; Globality; Head pose estimation; Human centered computing (HCC); Locality; Mixture of experts model; Subspace learning

Indexed keywords

ADAPTIVE ALGORITHMS; EDUCATION; FACE RECOGNITION; FEATURE EXTRACTION; GESTURE RECOGNITION; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LEARNING SYSTEMS; MODAL ANALYSIS;

DISCRIMINATING POWER COEFFICIENT (DPC); GLOBALITY; HEAD POSE ESTIMATION; HUMAN-CENTERED COMPUTING (HCC); LOCALITY; SUBSPACE LEARNING;

LEARNING ALGORITHMS;

EID: 56849094284     PISSN: 10518215     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSVT.2008.2004933     Document Type: Article

References (38)

1. M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni, "Locality- sensitive hashing scheme based on p-stable distribution," in Proc. SCG '04, 2004, pp. 253-262.
2. S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, pp. 2323-2326, 2000.
3. X. He and P. Niyogi, "Locality preserving projections," presented at the NIPS'03, 2003.
4. X. He, S. Yan, Y. Hu, P. Niyogi, and H.-J. Zhang, "Face recognition using laplacianfaces," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 3, pp. 328-340, Mar. 2005.
5. Y. Fu and T. S. Huang, "Locally linear embedded eigenspace analysis," [Online]. Available: www.ifp.uiuc.edu/~yun.fu2/papers/LEA-Yun05. pdf, IFP-TR, UIUC, 2005
6. Y. Fu and T. S. Huang, "Graph embedded analysis for head pose estimation," in IEEE Conf. FG'06, Southampton, U.K., 2006, pp. 3-8.
7. Y. Fu, J. Yuan, Z. Li, T. S. Huang, and Y. Wu, "Query-driven locally adaptive Fisher faces and expert-model for face recognition," in IEEE Conf. ICIP'07, 2007, pp. 141-144.
8. Y. Fu, Z. Li, T. S. Huang, and A. K. Katsaggelos, "Locally adaptive subspace and similarity metric learning for visual data clustering and retrieval," Comp. Vis. Image Understand, vol. 110, no. 3, pp. 390-402, 2008.
9. Z. Li, Y. Fu, J. Yuan, T. S. Huang, and Y. Wu, "Query driven localized linear discriminant models for head pose estimation," in Proc. IEEE Conf ICME'07, 2007, pp. 1810-1813.
10. Z. Li, L. Gao, and A. K. Katsaggelos, "Locally embedded linear subspaces for efficient video indexing and retrieval," in Proc. IEEE Conf. ICME'06, 2006, pp. 1765-1768.
11. M. Liu, S. Yan, Y. Fu, and T. S. Huang, "Flexible X-Y patches for face recognition," in Proc. IEEE Conf. ICASSP'08, 2008, pp. 2113-2116.
12. G.-D. Guo and C. Dyer, "Patch-based image correlation with rapid filtering," presented at the IEEE Conf. CVPR'07, 2nd Beyond Patches Workshop, Minneapolis, MN, Jun. 18-23, 2007.
13. A. Gionis, P. Indyk, and R. Motwani, "Similarity search in high dimensions via hashing," in Proc. VLDB'99, 1999, pp. 518-529.
14. S. Z. Li and A. K. Jain, Handbook of Face Recognition. New York: Springer-Verlag, 2005.
15. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning. New York: Springer-Verlag, 2002.
16. A. M. Martinez and A. C. Kak, "PCA versus LDA," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 2, pp. 228-233, 2001.
17. B. Moghaddam, T. Jebara, and A. Pentland, "Bayesian face recognition," Pattern. Recognit., vol. 33, no. 11, pp. 1771-1782, 2000.
18. P. J. Phillips, H. Moon, P. J. Rauss, and S. Rizvi, "The FERET evaluation methodology for face recognition algorithms," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 10, pp. 1090-1104, 2000.
19. F. Samaria and A. C. Harter, "Parameterisation of a stochastic model for human face identification," in Proc. IEEE Conf. WACV'94, 1994, pp. 138-142.
20. M. A. Turk and A. P. Pentland, "Face recognition using Eigenfaces," in Proc. IEEE Conf. CVPR'91, 1991, pp. 586-591.
21. R. Xiao, W. J. Li, Y. D. Tian, and X. O. Tang, "Joint boosting feature selection for robust face recognition," in Proc. IEEE Conf. CVPR'06, 2006, pp. 1415-1422.
22. M. H. Yang, "Face recognition using kernel methods," presented at the NIPS'01, 2001.
23. J. Ham, D. D. Lee, S. Mika, and B. Schölkopf, "A kernel view of the dimensionality reduction of manifolds," in Proc. ICML'04, 2004, pp. 369-376.
24. S. Yan, D. Xu, B. Zhang, H.-J. Zhang, Q. Yang, and S. Lin, "Graph embedding and. extensions: A general framework for dimensionality reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 1, pp. 40-51, 2007.
25. H. Zhang, A. C. Berg, M. Maire, and J. Malik, "SVM-KNN: Discriminative nearest neighbor classification for visual category recognition," in Proc. IEEE Conf. CVPR'06, 2006, pp. 2126-2136.
26. A. Jaimes, N. Sebe, and D. Gatica-Perez, "Human-centered computing: A multimedia perspective," in Proc. ACM Conf. Multimedia, 2006, pp. 855-864.
27. P. N. Belhumeur, J. P. Hepanha, and D. J. Kriegman, "Eigenfaces versus Fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, 1997.
28. J. Letissier and N. Gourier, "The pointing'04 data sets," presented at the IEEE ICPR Pointing'04 Workshop, 2004.
29. N. Gourier, D. Hall, and J. L. Crowley, "Estimating face orientation from robust detection of salient facial features," presented at the IEEE ICPR Pointing'04 Workshop, 2004.
30. D. B. Graham and N. M. Allinson, "Characterizing virtual eigensignatures for general purpose face recognition," Face Recognition: From Theory to Applications, ser. NATO ASI Series F, vol. 163, Computer & Systems Sciences, pp. 446-456, 1998.
31. K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft, "When is "nearest neighbor" meaningful?," in Proc. 7th Int. Conf. Database Theory, 1999, pp. 217-235.
32. B. Heisele and V. Blanz, "Morphable models for training a component-based face recognition system," in Face Processing, Advanced Modeling and Methods, W. Zhao and R. Chellapa, Eds. New York: Elsevier, 2006, pp. 439-462.
33. Y. Gao, Y. Wang, X. Feng, and X. Zhou, "Face recognition using most discriminative local and global, features," in Proc. IEEE Conf ICPR '06, 2006, vol. 1, pp. 351-354.
34. K. Huang, H. Yang, I. King, and M. R. Lyu, "Local learning versus Global learning: An introduction to maxi-min margin machine," in Support Vector Machines: Theory and Applications. New York: Springer-Verlag, 2005, vol. 177/2005, Studies in Fuzziness and Soft Computing, pp. 113-132.
35. V. de Silva and J. Tenenbaum, "Global versus local methods in non-linear dimensionality reduction," in Proc. NIPS'02, 2002, pp. 705-712.
36. T.-K. Kim and J. Kittler, "Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 3, pp. 318-327, Mar. 2005.
37. N. Kambhatla and T. K. Leen, "Dimension reduction by local principal component analysis," Neural Comput., vol. 9, no. 7, pp. 1493-1516, 1997.
38. A. Weingessel and K. Hornik, "Local PCA algorithms," IEEE Trans. Neural Netw., vol. 11, no. 6, pp. 1242-1250, 2000.