Gossip-based computation of a Gaussian mixture model for distributed multimedia indexing

IEEE Transactions on Multimedia

Volumn 10, Issue 3, 2008, Pages 385-392

  Nikseresht, Afshin ^a   Gelgon, Marc ^a  

^a UNIVERSITÉ DE NANTES   (France)

Author keywords

Classification; Distributed computing; Multimedia indexing; Probability density estimation

Indexed keywords

CLASSIFICATION (OF INFORMATION); DISTRIBUTED COMPUTER SYSTEMS; INDEXING (OF INFORMATION); MATHEMATICAL MODELS; MULTIMEDIA SERVICES; PROBABILITY DENSITY FUNCTION;

MODEL PARAMETERS; MULTIMEDIA INDEXING; PROBABILITY DENSITY ESTIMATION;

GAUSSIAN DISTRIBUTION;

EID: 41549113050     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2008.917343     Document Type: Conference Paper

References (23)

1. H. Akaike, "A new look at the statistical model identification problem," IEEE Trans. Automat. Contr., vol. AC-19, pp. 716-723, 1974.
2. H. Attias, "A variational Bayesian framework for graphical models," in Proc. Neural Information Processing Systems (NIPS) Conf., Denver, CO, Nov. 1999.
3. S. A. Berrani, L. Amsaleg, and P. Gros, "Robust content-based image searches for copyright protection," in Proc. ACM Workshop on Multimedia Databases, New Orleans, LA, Nov. 2003, pp. 70-77.
4. C. Biernacki, G. Celeux, and G. Govaert, "Choosing starting values for the em algorithm for getting the highest likelihood in multivariate Gaussian mixture models," Comput. Statist. Data Anal., vol. 41, pp. 561-575, 2003.
5. C. Bishop, Neural networks for Pattern Recognition. New York: Oxford Univ. Press, 1995.
6. S. Boyd, A. Ghosh, B. Prabhakar, and D. Shah, "Randomized gossip algorithms," IEEE Trans. Inform. Theory, vol. 52, pp. 2508-2330, Jun. 2006.
7. F. Cozman, M. Cirelo, T. S. Huang, I. Cohen, and N. Sebe, "Semisupervised learning of classifiers: theory, algorithms and their applications to human-computer interaction," IEEE Trans. Pattern Anal. Machine Intell., vol. 26, no. 12, pp. 1553-1567, Dec. 2004.
8. P. T. Eugster, R. Guerraoui, A.-M. Kermarrec, and L. Massoulié, "From epidemics to distributed computing," IEEE Comput., vol. 37, no. 5, 2003.
9. R. Fablet, P. Bouthemy, and P. Perez, "Non parametric motion characterization using causal probabilistic models for video indexing and retrieval," IEEE Trans. Image Processing, vol. 11, no. 4, pp. 393-407, Apr. 2001.
10. J. Goldberger and S. Roweis, "Hierarchical clustering of a mixture model," in Proc. Neural Information Processing Systems (NIPS'2004), 2004, pp. 505-512.
11. R. Hammoud and R. Mohr, "Gaussian mixture densities for video object recognition," in Proc. Int. Conf. on Pattern Recognition (ICPR'2000), Barcelona, Spain, Aug. 2000, pp. 71-75.
12. D. Kempe, A. Dobra, and J. Gehrke, "Gossip-based computation of aggregate information," in Proc. IEEE Symp. on Foundations of Computer Science, Cambridge, MA, Oct. 2003.
13. W. Kowalczyk and N. Vlassis, "Newscast EM," in Proc. Neural Information Processing Systems (NIPS). Cambridge, MA: MIT Press, 2005, vol. 17.
14. D. MacKay, "Bayesian interpolation," Neural Comput., vol. 4, no. 3, pp. 415-447, 1992.
15. D. Milojicic, V. Kalogeraki, R. Lukose, L. Nagaraja, J. Pruyne, B. Richard, S. Rollins, and Z. Xu, Peer-to-Peer Computing Hewlett-Packard, 2002, Tech. Rep. 2002-57.
16. W. T. Muller, M. Eisenhardt, and A. Henrich, "Efficient content-based P image retrieval using peer content descriptions," Proc. SPIE, vol. 5304, pp. 57-68, Dec. 2003.
17. R. Nowak, "Distributed EM algorithms for density estimation and clustering in sensor networks," IEEE Trans. Signal Processing, vol. 51, no. 8, pp. 2245-2253, Aug. 2003.
18. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman, Towards Category-Level Object Recognition. New York: Springer, 2006.
19. D. Reynolds, "Speaker identification and verification using Gaussian, speaker models," Speech Commun., vol. 17, pp. 91-108, 1995.
20. C. Schmid, "Weakly supervised learning of visual models and its application to content-based retrieval," Int. J. Comput. Vis., vol. 1, no. 56, pp. 7-16, 2004.
21. C. Tang, S. Dwarkadas, and Z. Xu, "On scaling latent semantic indexing on large peer-to-peer systems," in Proc. of ACM SIGIR (SIG on Information Retrieval, Sheffield, U.K., Jul. 2004, pp. 145-153.
22. J. J. Verbeek, J. R. J. Nunnink, and N. Vlassis, "Accelerated EM-based clustering of large datasets," Data Mining Knowl. Discovery, to be published.
23. L. Xie and P. Perez, "Slightly supervised learning of part-based appearance models," in Proc. IEEE Workshop of Learning in Computer Vision and Pattern Recognition, Washington, DC, Jun. 2004.