Maximum confidence hidden Markov modeling for face recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 30, Issue 4, 2008, Pages 606-616

  Chien, Jen Tzung ^a   Liao, Chih Pin ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Classifier design and evaluation; Confidence measure; Discrimative feature extraction; Discrimative training; Face and gesture recognition; Face recognition; Hidden Markov model; Parameter learning; Pattern classifacation; Statistical

Indexed keywords

FEATURE EXTRACTION; GESTURE RECOGNITION; HIDDEN MARKOV MODELS; MATHEMATICAL TRANSFORMATIONS; MATRIX ALGEBRA; OPTIMIZATION; STATISTICAL METHODS;

DISCRIMATIVE FEATURE EXTRACTION; DISCRIMATIVE TRAINING; PARAMETER LEARNING;

FACE RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOMETRY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; FACE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PROBABILITY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRY; COMPUTER SIMULATION; FACE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 42449120172     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.70715     Document Type: Article

References (35)

1. L. Bahl, P. Brown, P. de Souza, and R. Mercer, "Maximum Mutual Information Estimation of Hidden Markov Model Parameters for Speech Recognition," Proc. IEEE Int'l Conf. Acoustic, Speech, and Signal Processing, vol. 11, pp. 49-52, 1986.
2. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection," " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, July 1997.
3. A. Ben-Yishai and D. Burshtein, "A Discriminative Training Algorithm for Hidden Markov Models," " IEEE Trans. Speech and Audio Processing, vol 12, no. 3, pp. 204-217, 2004.
4. M. Bicego, U. Castellani, and V. Murino, "Using Hidden Markov Models and Wavelets for Face Recognition," Proc. Seventh IEEE Int'l Conf. Automatic Face and Gesture Recognition, pp. 257-262, 2000.
5. L. Chen, H. Man, and A.V. Nefian, "Face Recognition Based Multi-Class Mapping of Fisher Scores," " Pattern Recognition, vol. 38, pp. 799-811, 2005.
6. L.-F. Chen, H.-Y.M. Liao, M.-T. Ko, J.-C. Lin, and G.-J. Yu, "A New LDA-Based Face Recognition System Which Can Solve the Small Sample Size Problem," " Pattern Recognition, vol. 33, no. 10, pp. 1713-1726, 2000.
7. J.-T. Chien and C.-C. Wu, "Discriminant Waveletfaces and Nearest Feature Classifiers for Face Recognition," " IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 12, pp. 1644-1649, Dec. 2002.
8. J.-T. Chien and J.-C. Junqua, "Unsupervised Hierarchical Adaptation Using Reliable Selection of Cluster-Dependent Parameters," Speech Communication, vol. 30, no. 4, pp. 235-253, 2000.
9. A.P. Dempster, N.M. Laird, and D.B. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc. Series B, vol. 39, pp. 1-38, 1977.
10. R.O. Duda and P.E. Hart, " Pattern Classification and Scene Analysis John Wiley & Sons, 1973.
11. R.A. Fisher, "The Statistical Utilization of Multiple Measurements," Annals of Eugenics, vol. 8, pp. 376-386, 1938.
12. F. Fukunaga, Introduction to Statistic Pattern Recognition. Academic Press, 1990.
13. J. Hung and L. Lee, "Data-Driven Temporal Filters for Robust Features in Speech Recognition Obtained via Minimum Classification Error (MCE)," Proc. IEEE Int'l Conf. Acoustic, Speech, and Signal Processing, vol. 1, pp. 373-376, 2002.
14. Q. Huo, Y. Ge, and Z.-D. Feng, "High Performance Chinese OCR Based on Gabor Features, Discriminative Feature Extraction and Model Training," Proc. IEEE Int'l Conf. Acoustic, Speech, and Signal Processing, vol. 3, pp. 1517-1520, 2001.
15. C. Liu, H. Jiang, and X. Li, "Discriminative Training of CDHMMs for Maximum Relative Separation Margin," Proc. IEEE Int'l Conf. Acoustic, Speech and Signal Processing, vol. 1, pp. 101-104, 2005.
16. B.-H. Juang and S. Katagiri, "Discriminative Learning for Minimum Error Classification," IEEE Trans. Signal Processing, vol. 40, no. 12, pp. 3043-3054, 1992.
17. S. Katagiri, B.-H. Juang, and C.-H. Lee, "Pattern Recognition Using a Family of Design Algorithms Based upon the Generalized Probabilistic Descent Method," Proc. IEEE, vol. 86, no. 11, pp. 2345-2373, 1998.
18. M.S. Kim, D. Kim, and S.Y. Lee, "Face Recognition Using the Embedded HMM with Second-Order Block-Specific Observations," Pattern Recognition, vol. 36, no. 11, pp. 2723-2735, 2003.
19. V.V. Kohir and U.B. Desai, "Face Recognition Using a DCT-HMM Approach," Proc. Fourth IEEE Workshop Application of Computer Vision pp. 226-231, 1998.
20. N. Kumar and A.G. Andreou, "Heteroscedastic Discriminant Analysis and Reduced Rank HMMs for Improved Speech Recognition," Speech Comm., vol. 26, pp 283-297, 1998.
21. S.S. Kuo and O.E. Agazzi, "Keyword Spotting in Poorly Printed Documents Using Pseudo 2-D Hidden Markov Model," IEEE Trans. Pattern Analysis and Machine Intelligence, vol 16, no. 8, pp. 842-848, Aug. 1994.
22. E. Levin and R. Pieraccini, "Dynamic Planar Warping for Optical Character Recognition," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 3, pp. 149-152, 1992.
23. C.-P. Liao and J.-T. Chien, "Maximum Confidence Hidden Markov Modeling," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 5, pp. 549-552, 2006.
24. A.M. Martinez and A.C. Kak, "PCA versus LDA," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, pp. 228-233, 2001.
25. D.R.H. Miller, T. Leek, and R.M. Schwartz, "A Hidden Markov Model Information Retrieval System," Proc. 22nd Ann. Int'l ACM Conf. Research and Development in Information Retrieval, pp. 214-221, 1999.
26. A.V. Nefian, "Embedded Bayesian Networks for Face Recognition," Proc. IEEE Int'l Conf. Multimedia and Exp, vol. 2, pp. 133-136, 2002.
27. A.V. Nefian and M.H. Hayes III, "An Embedded HMM-Based Approach for Face Detection and Recognition," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 6, pp. 3553-3556, 1999.
28. A.V. Nefian and M.H. Hayes III, "Maximum Likelihood Training of the Embedded HMM for Face Detection and Recognition," Proc. Int'l Conf. Image Processing, vol. 1, pp. 33-36, 2000.
29. H. Othman and T. Aboulnasr, "A Separable Low Complexity 2D HMM with Application to Face Recognifion," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 10, pp. 1229-1238, Oct. 2003.
30. H.S. Park and S.W. Lee, "A Truly 2D Hidden Markov Model for Off-Line Handwritten Character Recognition," Pattern recognition, vol. 31, no. 12, pp. 1849-1864, 1998
31. P.J. Phillips, H. Wechsler, J. Huang, and P.J. Rauss, "The FERET Database and Evaluation Procedure for Face-Recognition Algorithms," Image and Vision Computing, vol. 16, no. 5, pp. 295-306, 1998.
32. L.R. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition," Proc. IEEE, vol. 777, no. 2, pp. 257-286, 1989.
33. F.S. Samaria and S. Young, "HMM-Based Architecture for Face Identification," Image and Vision Computing, vol. 12, no. 8, pp. 537-543, 1994.
34. R.A. Sukkar and C.-H. Lee, "Vocabulary Independent Discriminative Utterance Verification for Nonkeyword Rejection in Subword Based Speech Recognition," IEEE Trans. Speech and Audio Processing, vol. 4, no. 6, pp. 420-429, 1996.
35. M. Thomae, G. Ruske, and T. Pfau, "A New Approach to Discriminative Feature Extraction Using Model Transformation," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 3, pp. 1615-1618, 2000.