The role of classifiers in multimedia content management

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5021, Issue , 2003, Pages 89-99

  Naphade, Milind R ^a   Smith, John R ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Machine Learning; Pattern Classification; Semantic Indexing; TREC Video

Indexed keywords

LEARNING SYSTEMS; PATTERN RECOGNITION; SEMANTICS;

MULTIMEDIA CONTENT MANAGEMENT;

MULTIMEDIA SYSTEMS;

EID: 0038732686     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.479746     Document Type: Conference Paper

References (47)

1. M. Naphade, T. Kristjansson, B. Frey, and T. S. Huang, quot;Probabilistic multimedia objects (multijects): A novel approach to indexing and retrieval in multimedia systems,quot; in Proceedings of IEEE International Conference on Image Processing, 3, pp. 536-540, (Chicago, IL), Oct. 1998.
2. M. Naphade, C. Lin, and J. Smith, quot;Learning semantic multimedia representations from a small set of examples,quot; in IEEE International Confernce on Multimedia and Expo, (Lussane, Switzerland), Aug 2002.
3. M. Naphade, S. Basu, J. Smith, C. Lin, and B. Tseng, quot;Modeling semnatic concepts to support query by keywords in video,quot; in IEEE International Confernce on Image Processing, (Rochester, NY), Sep 2002.
4. M. Naphade, R. Mehrotra, A. M. Ferman, J. Warnick, T. S. Huang, and A. M. Tekalp, quot;A high performance shot boundary detection algorithm using multiple cues,quot; in Proceedings of IEEE International Conference on Image Processing, 2, pp. 884-887, (Chicago, IL), Oct. 1998.
5. M. R. Naphade, A Probabilistic Framework for mapping audio-visual features to high-level semantics in terms of concepts and context. PhD thesis, University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, May 2001.
6. M. R. Naphade, M. M. Yeung, and B. L. Yeo, quot;A novel scheme for fast and efficient video sequence matching using compact signatures,quot; in Proceedings of SPIE Storage and Retrieval for Multimedia Databases, 3972, pp. 564-572, Jan. 2000.
7. D. Zhong and S. F. Chang, quot;Spatio-temporal video search using the object-based video representation,quot; in Proceedings of IEEE International Conference on Image Processing, 1, pp. 21-24, (Santa Barbara, CA), Oct. 1997.
8. W. Wolf, quot;Hidden Markov model parsing of video programs,quot; in Proceedings of International Conference on Accoustics Signal and Speech Processing, 1997.
9. A. M. Ferman and A. M. Tekalp, quot;Probabilistic analysis and extraction of video content,quot; in Proceedings of IEEE International Conference on Image Processing, (Kobe, Japan), Oct. 1999.
10. M. Naphade and T. Huang, quot;Discovering recurring events in video using unsupervised methods,quot; in IEEE International Conference on Image Processing, (Rochester, NY), 2002.
11. V. Kobla, D. DeMenthon, and D. Doermann, quot;Identifying sports video using replay, text and camera motion features,quot; in Proceedings of SPIE Storage and Retrieval for Media Databases, 3972, pp. 332-343, (San Jose, Ca), Jan. 2000.
12. G. Iyengar and A. Lippman, quot;Models for automatic classification of video sequences,quot; in SPIE Conference on Storage and Retrieval for Still Image and Video Databases, pp. 216-227, 1998.
13. S. Fischer, R. Lienhart, and W. Effelsberg, quot;Automatic recognition of film genres,quot; in Proceedings of ACM Multimedia, pp. 295-304, (San Francisco, CA), April 1995.
14. M. Brand, N. Oliver, and A. Pentland, quot;Coupled hidden Markov models for complex action recognition,quot; in Proceedings of Computer Vision and Pattern Recognition, pp. 994-999, 1997.
15. J. Nam, A. Cetin, and A. Tewfik, quot;Speaker identification and video analysis for hierarchical video shot classification,quot; in Proceedings of IEEE International Conference on Image Processing, 2, pp. 550-555, (Santa Barbara, CA), Oct. 1997.
16. M. R. Naphade and T. S. Huang, quot;Stochastic modeling of soundtrack for efficient segmentation and indexing of video,quot; in Proceedings of SPIE Storage and Retrieval for Multimedia Databases, 3972, pp. 168-176, Jan. 2000.
17. M. Akutsu, A. Hamada, and Y. Tonomura, quot;Video handling with music and speech detection,quot; IEEE Multimedia 5(3), pp. 17-25, 1998.
18. D. Ellis, Prediction-driven computational auditory scene analysis. PhD thesis, MIT, Cambridge, MA, 1996.
19. P. Jang and A. Hauptmann, quot;Learning to recognize speech by watching television,quot; IEEE Intelligent Systems Magazine 14(5), pp. 51-58, 1999.
20. E. Wold, T. Blum, D. Keislar, and J. Wheaton, quot;Content-based classification search and retrieval of audio,quot; IEEE Multimedia 3(3), pp. 27-36, 1996.
21. T. Zhang and C. Kuo, quot;An integrated approach to multimodal media content analysis,quot; in Proceedings of SPIE, IS&T Storage and Retrieval for Media Databases, 3972, pp. 506-517, (San Jose, Ca), Jan. 2000.
22. Z. Liu, Y. Wang, and T. Chen, quot;Audio feature extraction and analysis for scene segmentation and classification,quot; VLSI Signal processing Systems for Signal, Image and Video Technology 20, pp. 61-79, Oct. 1998.
23. Y. Wang, Z. Liu, and J. Huang, quot;Multimedia content analysis using audio and visual information,quot; IEEE Signal Processing Magazine 17, pp. 12-36, Nov. 2000.
24. H. Wactlar, T. Kanade, M. Smith, and S. Stevens, quot;Intelligent access to digital video: The informedia project,quot; IEEE Computer Digital Library Intiaive special issue, May. 1996.
25. Y. Nakamura and T. Kanade, quot;Semantic analysis for video contents extraction - spotting by association in news video,quot; in Proceedings of ACM International Multimedia Conference, Nov. 1997.
26. D. D. Saur, Y. P. Tan, S. R. Kulkarni, and P. J. Ramadge, quot;Automated analysis and annotation of basketball video,quot; in Proceedings of SPIE Symposium, 3022, pp. 176-187, 1997.
27. J. Foote, J. Boreczky, and L. Wilcox, quot;Finding presentations in recorded meetings using audio and video features,quot; in IEEE International Conference on Speech Accoustics and Signal Processing, pp. 3029-3032, 1999.
28. B. Clarkson and A. Pentland, quot;Unsupervised clustering of ambulatory audio and video,quot; in Proceedings of IEEE International Conference on Accoustics Speech and Signal Processing, (Phoenix, AZ), 1999.
29. M. R. Naphade, R. Wang, and T. S. Huang, quot;Supporting audiovisual query using dynamic programming,quot; in ACM Multimedia, pp. 411-420, Oct. 2001.
30. J. Rehg, K. Murphy, and P. Fieguth, quot;Vision-based speaker detection using bayesian networks,quot; in Proceedings of Computer Vision and Pattern Recognition, 2, pp. 110-116, (Fort Collins, CO), June 1999.
31. M. R. Naphade and T. S. Huang, quot;Recognizing high-level audio-visual concepts using context,quot; in IEEE International Conference on Image Processing, 3, pp. 46-49, (Thessaloniki, Greece), Oct 2001.
32. M. R. Naphade, A. Garg, and T. S. Huang, quot;Duration dependent input output Markov models for audio-visual event detection,quot; in IEEE International Conference on Multimedia and Expo, (Tokyo, Japan), August 2001.
33. M. Naphade, quot;Statistical techniques in video data management,quot; in IEEE Multimedia Signal Processing Workshop, (US Virgin Islands), Dec 2002.
34. H. V. Poor, An Introduction to Signal Detection and Estimation, Springer-Verlag, New York, 2 ed., 1999.
35. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis, Wiley Eastern, New York, 1973.
36. L. R. Rabiner, quot;A tutorial on hidden Markov models and selected applications in speech recognition,quot; Proceedings IEEE 77, pp. 257-286, Feb. 1989.
37. A. P. Dempster, N. M. Laird, and D. B. Rubin, quot;Maximum likelihood from incomplete data via the EM algorithm,quot; Proceedings of the Royal Statistical Society B(39), pp. 1-38, 1977.
38. V. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, 1995.
39. D. Bertsekas, Nonlinear Programming, Athena Scientific, Belmont, MA, 1995.
40. M. Naphade, C. Lin, J. Smith, B. Tseng, and S. Basu, quot;Learning to annotate video databases,quot; in SPIE Conference on Storage and Retrieval on Media Databases, (San Jose, CA), 2002.
41. S. Srinivasan, D. Ponceleon, A. Amir, and D. Petkovic, quot;What is that video anyway? In search of better browsing,quot; in Proceedings of IEEE International Conference on Multimedia and Expo, pp. 388-392, (New York), July 2000.
42. J. Smith, S. Srinivasan, A. Amir, S. Basu, G. Iyengar, C. Lin, M. Naphade, D. Ponceleon, and B. Tseng, quot;Integrating features, models, and semantics for content-based retrieval,quot; NIST video-TEC notebook, 2001.
43. M. R. Naphade, I. Kozintsev, and T. S. Huang, quot;A factor graph framework for semantic video indexing,quot; IEEE Transactions on Circuits and Systems for Video Technology 12, pp. 40-52, Jan 2002.
44. A. K. Jain and A. Vailaya, quot;Shape-based retrieval: A case study with trademark image databases.quot; Pattern Recognition 31(9), pp. 1369-1390, 1998.
45. A. K. Jain, A. Vailaya, and W. Xiong, quot;Query by video clip,quot; Multimedia Systems, Special Issue on Video Libraries 7(5), pp. 369-384, 1999.
46. S. Dudani, K. Breeding, and R. McGhee, quot;Aircraft identification by moment invariants,quot; IEEE Transactions on Computers C-26, pp. 39-45, Jan. 1977.
47. T. Joachims, quot;Making large-scale svm learning practical,quot; in Support Vector Learning, B. Schlkopf, C. Burges, and A. Smola, eds., MIT Press, 1999.