Classifier Fusion: Combination Methods For Semantic Indexing in Video Content

1. Kuncheva, L., Bezdek, J.C., Duin, R.: Decision templates for multiple classifier fusion: an experiemental comparaison. Pattern Recognition 34, 299–314 (2001)

   Article  MATH  Google Scholar 

2. Rastrigin, L., Erenstein, R.: Method of collective recognition. Energoizdat (1982)

   Google Scholar 

3. Jacobs, R., Jordan, M., Nowlan, S., Hinton, G.: Adaptive mixtures of local experts. Neural Computation 3, 1409–1431 (1991)

   Article  Google Scholar 

4. Xu, L., Krzyzak, A., Suen, C.: Methods of combining multiple classifiers and their application to hardwriting recognition. IEEE Trans. Sys. Man. Cyber. 22, 418–435 (1992)

   Article  Google Scholar 

5. Duin, R., Tax, D.: Experiements with classifier combining rules. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 16–29. Springer, Heidelberg (2000)

   Chapter  Google Scholar 

6. Jain, A., Duin, R., Mao, J.: Combination of weak classifiers. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(1) (2000)

   Google Scholar 

7. Kuncheva, L.: Fuzzy versus nonfuzzy in combining classifiers designed by bossting. IEEE Transactions on fuzzy systems 11(6) (2003)

   Google Scholar 

8. Chou, K., Tu, L., Shyu, I.: Performances analysis of a multiple classifiers system for recognition of totally unconstrained handwritten numerals. In: 4th International Workshop on Frontiers of Handwritten Recognition, pp. 480–487 (1994)

   Google Scholar 

9. Achermann, B., Bunke, H.: Combination of classifiers on the decision level for face recognition. Technical repport of Bern University (1996)

   Google Scholar 

10. Ho, T.: A theory of multiple classifier systems and its application to visual and word recognition. PhD thesis, Phd thesis of New-York University (1992)

    Google Scholar 

11. Cybenko, G.: Approximations by superposition of a sigmoidal function. Mathematics of Control, Signal and Systems 2, 303–314 (1989)

    Article  MATH  MathSciNet  Google Scholar 

12. Paalanen, P., Kamarainen, J., Ilonen, J., Kalviainen, H.: Feature representation and discrimination based on gaussian mixture model probability densities. Research Report, Lappeenranta University of Technology (1995)

    Google Scholar 

13. Souvannavong, F., Merialdo, B., Huet, B.: Multi modal classifier fusion for video shot content retrieval. In: Proceedings of WIAMIS (2005)

    Google Scholar 

14. Freud, Y., Schapire, R.: Experiments with a new boosting algorithms. In: Machine Learning: Proceedings of the 13th International Conference (1996)

    Google Scholar 

15. Skurichina, M., Duin, R.: Bagging for linear classifiers. Pattern Recognition 31(7), 909–930 (1998)

    Article  Google Scholar 

16. Ma, W., Zhang, H.: Benchmarking of image features for content-based image retrieval. In: Thirtysecond Asilomar Conference on Signals, System and Computers, pp. 253–257 (1998)

    Google Scholar 

17. Carson, C., Thomas, M., Belongie, S.: Blobworld: A system for region-based image indexing and retrieval. In: Third international conference on visual information systems (1999)

    Google Scholar 

18. Souvannavong, F., Merialdo, B., Huet, B.: Latent semantic analysis for an effective region based video shot retrieval system. In: Proceedings of ACM MIR (2004)

    Google Scholar 

19. Wang, R., Huang, T.: Fast camera motion analysis from mpeg domain. In: Proceedings of IEEE ICIP, pp. 691–694 (1999)

    Google Scholar 

20. TRECVID, Digital video retrieval at NIST, http://www-nlpir.nist.gov/projects/trecvid/

21. Chang, S., Hsu, W., Kennedy, L., Xie, L., Yanagawa, A., Zavesky, E., Zhang, D.: Video seach and high level feature extraction. In: Proceedings of Trecvid (2005)

    Google Scholar 

22. Zheng, Y.Y.C.: Run time information fusion in speech recognition. In: Proc. of ICSLP (2002)

    Google Scholar 

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