Cross-domain multi-event tracking via CO-PMHT

ACM Transactions on Multimedia Computing, Communications and Applications

Volumn 10, Issue 4, 2014, Pages

  Zhang, Tianzhu ^a,b   Xu, Changsheng ^a,b  

^a INSTITUTE OF AUTOMATION   (China)

^b China Singapore Institute of Digital Media   (Singapore)

Author keywords

CO PMHT; Cross domain; Multi event tracking; Multi modality; PMHT

Indexed keywords

SEMANTICS;

CO-PMHT; CROSS-DOMAIN; EVOLUTIONARY PROCESS; EXPERIMENTAL EVALUATION; MULTI-HYPOTHESIS TRACKING; MULTI-MODALITY; PMHT; POSTERIOR PROBABILITY;

EVOLUTIONARY ALGORITHMS;

EID: 84905258215     PISSN: 15516857     EISSN: 15516865     Source Type: Journal    
DOI: 10.1145/2602633     Document Type: Article

References (31)

1. J. Allan. 2002. Topic Detection and Tracking: Event Based Information Retrieval. Kluwer Academic Press.
2. Y. Bar-Shalom, F. Daum, and J. Huang. 2009. The probabilistic data association filter. IEEE Control Syst. Mag. 29, 6, 82-100.
3. D. M. Blei, A. Y. Ng, and M. I. Jordan. 2003. Latent dirichlet allocation. J. Mach. Learn. Res. 3, 3-4, 993-1022.
4. H. L. Chieu and Y. K. Lee. 2004. Query based event extraction along a timeline. In Proceedings of the 27th Annual ACM SIGIR International Conference on Research and Development in Information Retrieval.
5. I. Cox and S. Hingorani. 1979. An efficient implementation of reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Trans. Pattern Anal. Mach. Intell. 24, 6, 843-854.
6. A. Dempster, N. Laird, and D. Rubin. 1977. Maximum likelihood from incomplete data via the em algorithm. J. Royal Statist. Soc. B39, 1, 1-38.
7. P. Duygulu, J. Y. Pan, and D. A. Forsyth. 2005. Towards auto-documentary: Tracking the evolution of news stories. In Proceedings of the 12th Annual ACM International Conference on Multimedia (Multimedia'05). 820-827.
8. J. R. Kender and M. R. Naphade. 2005. Visual concepts for news story tracking: Analyzing and exploiting the nist trecvid video annotation experiment. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). 1174-1181.
9. Z. Knan, T. Balch, and F. Dellaert. 2005. MCMC-based particle filtering for tracking a variable number of interacting targets. IEEE Trans. Pattern Anal. Mach. Intell. 27, 11, 82-100.
10. S. Kullback and R. A. Leibler. 1951. On information and sufficiency. Ann. Math. Statist. 22, 1, 79-86.
11. R. Kumar, U. Mahadevan, and D. Sivakumar. 2004. A graph-theoretic approach to extract storylines from search results. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
12. F. Lin and C.-H. Liang. 2008. Storyline-based summarization for news topic retrospection. Decis. Support Syst. 45, 4, 473-490.
13. L. Liu, L. Wang, and X. Liu. 2011. In defense of soft assignment coding. In Proceedings of the IEEE International Conference on Computer Vision (ICCV'11). 2486-2493.
14. S. Liu, S. Yan, T. Zhang, C. Xu, J. Liu, and H. Lu. 2012. Weakly-supervised graph propagation towards collective image parsing. IEEE Trans. Multimedia 14, 2, 361-373.
15. J. Makkonen, H. A. Myka, and M. Salmenkivi. 2004. Simple semantics in topic detection and tracking. Inf. Retr. 7, 3-4, 347-368.
16. G. Salton and C. Buckley. 1988. Term-weighting approaches in automatic text retrieval. Inf. Process. Manag. 24, 5, 513-523.
17. G. Salton, A. Wong, and C. S. Yang. 1975. A vector space model for automatic indexing. Comm. ACM 18, 1, 613-620.
18. H. Shitrit, J. Berclaz, F. Fleuret, and P. Fua. 2011. Tracking multiple people under global appearance constraints. In Proceedings of the IEEE International Conference on Computer Vision (ICCV'11). 1-8.
19. R. L. Streit and T. E. Luginbuhl. 1995. Probabilistic multi-hypothesis tracking. Tech. rep. NUWC-NPT 10, 428, Naval Undersea Warfare Center, Newport, RI.
20. X.Wu, C.-W. Ngo, and A. G. Hauptmann. 2008. Multimodal news story clustering with pairwise visual near-duplicate constraint. IEEE Trans. Multimedia 10, 4, 188-199.
21. L. Xie, L. S. Kennedy, S.-F. Chang, A. Divakaran, H. Sun, and C.-Y. Lin. 2004. Discovering meaningful multimedia patterns with audio-visual concepts and associated text. In Proceedings of the International Conference on Image Processing (ICIP'04). 2383-2386.
22. J. Xing, H. Ai, and S. Lao. 2009. Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'09). 1-8.
23. Y. Yang, J. Carbonell, R. Brown, T. Pierce, B. Archibald, and X. Liu. 1999. Learning approaches for detecting and tracking news events. IEEE Intell. Syst. Appl. Intell. Inf. Retr. 14, 4, 32-43.
24. Q. Yu and G. Medioni. 2009. Multiple-target tracking by spatio-temporal monte carlo markov chain data association. IEEE Trans. Pattern Anal. Mach. Intell. 31, 12, 1-110.
25. Y. Zhai and M. Shah. 2005. Tracking news stories across different sources. In Proceedings of the 13th Annual ACM International Conference on Multimedia (Multimedia'05). 2-10.
26. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. 2012a. Low-rank sparse learning for robust visual tracking. In Proceedings of the 12th European Conference on Computer Vision (ECCV'12).
27. T. Zhang, C. Xu, G. Zhu, S. Liu, and H. Lu. 2012b. A generic framework for video annotation via semi-supervised learning. IEEE Trans. Multimedia 14, 4, 1206-1219.
28. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. 2012c. Robust visual tracking via multi-task sparse learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'12). 2042-2049.
29. T. Zhang, B. Ghanem, S. Liu, and N. Ahuja. 2013a. Robust visual tracking via structured multi-task sparse learning. Int. J. Comput. Vis. 101, 2, 367-383.
30. T. Zhang, B. Ghanem, S. Liu, C. Xu, and N. Ahuja. 2013b. Low-rank sparse coding for image classification. In Proceedings of the IEEE International Conference on Computer Vision (ICCV'13).
31. T. Zhang, S. Liu, C. Xu, and H. Lu. 2013c. Mining semantic context information for intelligent video surveillance of traffic scenes. IEEE Trans. Industr. Informat. 9, 1, 149-160.