Bayesian Methods

• A. Vailaya, A. Jain, and HJ Zhang, "On Image Classification: City Images vs. Landscapes," Pattern Recognition Journal, Pattern Recognition, Vol. 31, No. 12, pp. 1921-1935, 1998. [link]
• A. Vailaya, M. Figueiredo, A. Jain, and HJ Zhang, "A Bayesian Framework for Semantic Classification of Outdoor Vacation Images," IEEE Trans. Image Processing, Vol. 10, No. 1, pp. 157-172, Jan. 2001. [link]

EM

• Jeff Bilms, "A Gentle Tutorial of the EM Algorithm and its Application to Parameter
  Estimation for Gaussian Mixture and Hidden Markov Models," ICSI TR-97-021
  April 1998. [link]

Factor Graph, Bayesian Networks

• M. Napahde, I. V. Kozintsev and T. Huang, "A Factor Graph Framework for
  Semantic Video Indexing," IEEE TCSVT 2002. [link]
• Z. Ghahraman, "Learning Dynamic Bayesian Networks," in book - Adaptive Processing of Sequences and Data Structures, edited by Gori and Giles, Springer-Verlag, 1998. [link]

Boosting

• Yoav Freund and Robert E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," In Computational Learning Theory: Eurocolt ’95, pages 23–37. Springer-Verlag, 1995. [link]
• K. Tieu and P.Viola, "Boosting Image Retrieval," CVPR 2000. [link]
• Paul Viola and Michael Jones, "Rapid object detection using a boosted cascade of simple features," CVPR, 2001. [link]

Maximum Entropy Model

• D. Beeferman and A. Berger and J. D. Lafferty, "Statistical Models for Text Segmentation," Machine Learning, p. 177-210, vol. 34, 1999. [link]
• W. Hsu, S.-F. Chang, A Statistical Framework for Fusing Mid-level Perceptual Features in News Story Segmentation, IEEE International Conference on Multimedia & Expo (ICME) 2003. [link]

SVM, Active Learning, and Extensions

• Christopher J. C Burges, "A Tutorial on Support Vector Machines for Pattern Recognition,"
  Journal of Data Mining and Knowledge Discovery, pp. 121-167, 1998. [link]
• S. Tong and E. Chang, "Support Vector Machine Active Learning for Image Retrieval," ACM International Conference on Multimedia, pp.107-118, Ottawa, October 2001. [link]
• Multi-camera Spatio-temporal Fusion and Biased Sequence-data Learning for Security Surveillance,
  G. Wu, Y. Wu, L. Jiao, Y.-F. Wang, and E. Chang, ACM International Conference on Multimedia, Berkeley, November 2003. [link]
• Guodong Guo and Stan.Z. Li, "Content-based Audio Classification and Retrieval by Support Vector Machines," IEEE Trans. on Neural Networks. Vol.14, No.1, pp.209-215. January 2003.
  
• M. E. Tipping, "The relevance vector machine," In Advances in Neural Information Processing Systems, San Mateo, CA, 2000. Morgan Kaufmann. [link] (extension of SVM for getting sparsity)

Markov Random Field

• Benzougar, A.; Bouthemy, P.; Fablet, R., "MRF-based moving object detection from MPEG coded video," 2001. International Conference on Image Processing,Volume: 3 , Oct. 2001. [link]
• Fablet, R.; Bouthemy, P., "Non parametric motion recognition using temporal multiscale Gibbs models," CVPR Dec. 2001. [link]

HMM

• L.R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proceedings of the IEEE, Volume: 77, Issue: 2, Feb 1989, pp. 257-286. [link]
• Jeff Bilmes, What HMMs can do, U. Washington Tech Report, Feb 2002. [link]
• Bourlard's EPFL matlab lab manual on HMMs. [link]
  
• J. Huang, Z. Liu, and Y. Wang, "Joint Video Scene Segmentation and Classification based on Hidden Markov Model," Proc. IEEE International Conference on Multimedia and Expo (ICME 2000), New York, Aug. 2000. [link]
• L. Xie, S.-F. Chang, A. Divakaran and H. Sun, "Structure Analysis of Soccer Video with Hidden Markov Models," ICASSP-2002, Orlando, FL, USA, May 2002. [link]

HMM Variations

• Z. Ghahramani and M. Jordan. Factorial Hidden Markov models. Machine Learning, 29, 1997. [link]
• J. Kwon and K. Murphy, "Modeling Freeway Traffic with Coupled HMMs," [link]
• M. Brand and N. Oliver and A. Pentland, "Coupled hidden markov models for complex action recognition", CVPR 97. [link]
• Shai Fine, Yoram Singer, Naftali Tishby, "The Hierarchical Hidden Markov Model: Analysis and
  Applications, J. of Machine Learning, Vol. 32, pp. 41-62, 1998.[link]
• L. Xie, S.-F. Chang, A. Divakaran and H. Sun, Unsupervised Mining of Statistical Temporal Structures in Video, Book Chapter in Video Mining, A. Rosenfeld, D. Doremann and D. Dementhon Eds, Kluwer Academic
  Publishers, June 2003 . [link]
• Kevin Murphy and Mark Paskin., "Linear Time Inference in Hierarchical HMMs," NIPS '01 (Neural Info. Proc. Systems). [link]

Hidden Markov SVM

• Y. Altun, I. Tsochantaridis, T. Hofmann, "Hidden Markov Support Vector Machines," 20th International Conference on Machine Learning (ICML), 2003. [link]

Hierarchical Mixture Model

• T. Hofmann. Learning and representing topic. A hierarchical mixture model for word occurrence in
  document databases. In Workshop on learning from text and the web, CMU, 1998. [link]
• K. Barnard and D. A. Forsyth. Learning the semantics of words and pictures. In International
  Conference on Computer Vision, pages II:408–415, 2001. [link]

Machine Translation

• P. F. Brown, S. A. Della Pietra, V. J. Della Pietra, and R. L. Mercer. The mathematics of machine
  translation: Parameter estimation. Computational Linguistics, 19(10):263–311, 1993. [link]
• P. Duygulu, Kobus B., J. F. G de Freitas, and D. A. Forsyth. Object recognition as machine translation:
  Learning a lexicon for a fixed image vocabulary. In The Seventh European Conference on
  Computer Vision, pages IV:97–112, 2002. [link]

Multimedia Knowledge and Classification

• M. Ciaramita, T. Hofmann, M. Johnson, "Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge," 18th International Joint Conference on Artificial Intelligence (IJCAI), 2003. [link]
• A. B. Benitez and S.-F. Chang, Image Classification Using Multimedia Knowledge Networks, Proceeding of the International Conference on Image Processing (ICIP-2003), Barcelona, Spain, Sep 14-17, 2003. [link]

TREC Video

• B. Adams, G. Iyengar, Ching-Yung Lin, Milind Naphade, Chalapathy Neti, Herriet Nock and John R. Smith, "Semantic Indexing of Multimedia Content Using Visual, Audio and Text Cues," EURASIP Journal on Applied Signal Processing, Feb 2003 . (pre-print) [link]
• Ching-Yung Lin, Belle L. Tseng, Milind Naphade, Apostol Natsev and John R.
  S mith, "VideoAL: A Novel End-to-End MPEG-7 Automatic Labeling System,"
  IEEE Intl. Conf. on Image Processing (ICIP), Barcelona, Spain, September
  2003. [link] [user manual]
• Annotation forum [link]

Other

• Anil K. Jain, etc., "Statistical Pattern Recognition: A Review," IEEE Tran. on Pattern Analysis and Machine Intelligence, vol 22, No 1, Jan. 2000. [link]
• A K Jain, etc., "Data clustering: A Review," ACM Computing Surveys, vol. 31, no. 3, Sept. 1999. [link]
• Tong, S., & Koller, D. (2000). Support vector machine active learning with applications to text classification, Proceedings of the Seventeenth International Conference on Machine Learning (pp. 999- 1006). San-Francisco: Morgan Kaufmann. [link]
• Rui, Y., Huang, T. S., Ortega, M., , Mehrotra, S.: Relevance feedback: A
  power tool in interactive content-based image retrieval. IEEE Trans. on
  Circuits and Systems for Video Technology 8(5) (Sep. 1998):644--655
  http://citeseer.nj.nec.com/rui98relevance.html
• G. Salton and C. Buckley. Improving retrieval performance by relevance
  feedback. Journal of the American Society for Information Science, pages
  288--297, 1990 http://citeseer.nj.nec.com/context/21661/0