Semi-supervised learning for semantic video retrieval

Proceedings of the 6th ACM International Conference on Image and Video Retrieval, CIVR 2007

Volumn , Issue , 2007, Pages 154-161

  Ewerth, Ralph ^a   Freisleben, Bernd ^a  

^a PHILIPPS UNIVERSITY MARBURG   (Germany)

Author keywords

Semantic video retrieval; Semi supervised learning

Indexed keywords

BROADCASTING; COMPUTER NETWORKS; IMAGE RETRIEVAL; MULTIMEDIA SERVICES; SUPPORT VECTOR MACHINES;

CONTEXTUAL INFORMATION; MULTIMEDIA RETRIEVAL; SEMANTIC VIDEO RETRIEVAL; SEMI-SUPERVISED LEARNING;

SEMANTIC WEB;

EID: 36849060178     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1282280.1282308     Document Type: Conference Paper

References (24)

1. Amir, A., Argillander, J., Campbell, M., Haubold, A., Iyengar, G., Ebadollahi, S., Kang, F., Naphade, M. R., Natsev, A., Smith, J.R., Tesic, J., and Volkmer, T. IBM Research TRECVID-2005 Video Retrieval System, in TREC Video Retrieval Online Proceedings, (2005), http://www-nlpir.nist.gov/projects/tvpubs/ tv.pubs.org.html
2. Blum, A. and Mitchell, T. Combining Labeled and Unlabeled Data with Co-Training. In Proceedings of the 11th Conference on Computational Learning Theory, Madison, Wisconsin, USA, 1998, 92-100.
3. Brown, G. Wyatt, J., Harris, R., and Yao, X. Diversity Creation Methods: A Survey and Categorisation. In Information Fusion 6 (2005), Elsevier, 2005, 5-20.
4. Chang, C.-C. and Lin, C.-J. LIBSVM: A Library for Support Vector Machines, 2001. http://www.csie.ntu.edu.tw/~cjlin/libsvm
5. Dorai, C. and Venkatesh, S. Media Computing -Computational Media Aesthetics. Kluwer Academic Publishers, Boston, 2002.
6. Ewerth, R. and Freisleben, B. Self-Supervised Learning for Robust Video Indexing. In Proc. of the IEEE Conference on Multimedia & Expo 2006, Toronto, 2006, 1749-1752.
7. Ewerth, R., Muhling, M., and Freisleben, B. Self-Supervised Learning of Face Appearances in TV Casts and Movies. In Proceedings of the IEEE Symposium on Multimedia, San Diego, CA, USA, 2006, 78-85.
8. Freund, Y. and Schapire, R. E. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. In Journal of Computer and System Sciences, 55(1), 1997, 119-139.
9. Gemert, J., Geusebroek, J., Veenman, C., Snoek, C., and Smeulders, A. Robust Scene Categorization by Learning Image Statistics in Context. In Proceedings of Int'l Workshop on Semantic Learning Applications in Multimedia, in conjunction with CVPR'06, New York, USA, 2006.
10. Jeannin, S. and Mory, B. Video Motion Representation for Improved Content Access. In IEEE Transactions on Consumer Electronics, Vol. 46, No. 3, 2000, 645-655.
11. Kuncheva, L. I., Whitaker, C. J., Shipp, C. A., and Duin, R. P. W. Limits on the Majority Vote Accuracy in Classifier Fusion. In Pattern Analysis and Applications, 6, 2003, Springer-Verlag, 22-31.
12. Lu, L., Jiang, H., and Zhang, H.-J. A Robust Audio Classification and Segmentation Method. In Proc. of the ACM Conf. on Multimedia 2001, Ottawa, Canada, 203-211.
13. Manjunath, B. S., Ohm, J.-R., Vasudevan, V., and Yamada, A. Color and Texture Descriptors. In IEEE Transactions on Circuits and Systems for Video Technology, Vol. 11, No. 6, 2001, 703-715.
14. Naphade, M. R. and Smith, J. R. On the Detection of Semantic Concepts at TRECVID. In Proceedings of the ACM Conference on Multimedia, 2004, New York, 660-667.
15. Phillips, P.J., Grother, P., Micheals, R. J., Blackburn, D. M., Tabassi, E., and Bone, M. Face Recognition Vendor Test 2002. Evaluation Report IR 6965, National Institute of Standards and Technology, www.itl.nist.gov/iad/894.03/ face/face.html, March 2003.
16. Smith, J. R., Naphade, M. R., and Natsev, A. Multimedia Semantic Indexing Using Model Vectors. In Proceedings of the IEEE International Conference on Multimedia & Expo 2003, Volume 2, Baltimore, Maryland, USA, 2003, 445-448.
17. Snoek, C. G. M., Worring, M., Geusebroek, J.-M., Koelma, D. C., Seinstra, F. J., and Smeulders, A. W. M. The Semantic Pathfinder: Using an Authoring Metaphor for Generic Multimedia Indexing. In IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 28(10), 2006, 1678-1689.
18. Snoek, C. G. M., Worring, M., van Gemert, J. C., Geusebroek, J.-M., and Smeulders, A. W.M. The Challenge Problem for Automated Detection of 101 Semantic Concepts in Multimedia. In Proceedings of ACM the Conference on Multimedia, Santa Barbara, USA, 2006, 421-430.
19. TRECVID: TREC Video Retrieval Evaluation Series. http://www-nlpir.nist. gov/projects/trecvid/
20. Viola, P. and Jones, M. Robust Real-Time Face Detection. In International Journal of Computer Vision, Volume 57 (2), (2004), Kluwer Academic Publishers, 2004, 137-154.
21. Wu, J., Ding, D., Hua, X.-S., and Zhang, B. Tracking Concept Drifting with an Online-Optimized Incremental Learning Framework. In Proc. of the 7th ACM Int'l Workshop on Multimedia Information Retrieval, 2005, Singapore, 33-40.
22. Yan, R. and Hauptmann, A. G. Co-Retrieval: A Boosted Reranking Approach for Video Retrieval. In Proc. of the Int'l Conf. on Image and Video Retrieval, Dublin, Ireland, 2004, 60-69.
23. Yan, R. and Naphade, M. Co-Training Non-Robust Classifiers for Video Semantic Concept Detection. In Proceedings of the IEEE International Conference on Image Processing 2005, Vol. 1, Singapore, 1205-1208.
24. Yan, R. and Naphade, M. Semi-Supervised Cross Feature Learning for Semantic Concept Detection in Videos. In Proc. of the IEEE Int'l Conf. on Computer Vision and Pattern Recognition, 2005, Vol. 1, San Diego, CA, USA, 657-663.