An application of a particle filter to Bayesian multiple sound source tracking with audio and video information fusion

Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004

Volumn 2, Issue , 2004, Pages 805-812

  Asoh, Hideki ^a   Asano, Futoshi ^a   Yoshimura, Takashi ^a   Motomura, Yoichi ^a   Ichimura, Naoyuki ^a   Hara, Isao ^a   Ogata, Jun ^a   Yamamoto, Kiyoshi ^b  

^a NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^b UNIVERSITY OF TSUKUBA   (Japan)

Author keywords

Bayesian Multiple Target Tracking; Particle Filter; Sound Source Tracking

Indexed keywords

ACOUSTIC WAVES; APPROXIMATION THEORY; ESTIMATION; INTEGRATION; MONTE CARLO METHODS; TRACKING (POSITION); VIDEO SIGNAL PROCESSING;

BAYESIAN MULTIPLE TARGET TRACKING; PARTICLE FILTERS; SOUND SOURCE TRACKING;

SIGNAL FILTERING AND PREDICTION;

EID: 6344237097     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. A. Doucet, N. Freitas, and N. Gordon, editors. Sequential Monte Carlo Methods in Practice. Springer-Verlag, 2001.
2. G. Kitagawa. Monte carlo filter and smoother for non-gaussian nonlinear state space models. Journal of Computational and Graphical Statistics, 5:1-25, 1996.
3. M. Isard and A. Blake. Condensation - conditional density propagation for visual tracking. International Journal of Computer Vision, 28:5-28, 1998.
4. D. Fox, S. Thrun, W. Burgard, and F. Dellaert. Particle filters for mobile robot localization. In A Doucet et al., editors, Sequential Monte Carlo Methods in Practice, pages 401-428. Springer-Verlag, 2001.
5. N. Ichimura. Stochastic filtering for motion trajectory in image sequences using a monte carlo filter with estimation of hyper-parameters. In Proceedings of International Conference on Pattern Recognition (ICPR 2002), pages 68-73, 2002.
6. F. Asano, Y. Motomura, H. Asoh, T. Yoshimura, N. Ichimura, and S. Nakamura. Fusion of audio and video information for detecting speech events. In Proceedings of the Sixth International Conference on Information Fusion (Fusion 2003), pages 386-393, 2003.
7. F. Asano, Y. Motomura, H. Asoh, T. Yoshimura, N. Ichimura, K. Yamamoto, N. Kitawaki, and S. Nakamura. Detection and separation of speech segment using audio and video information fusion. In Proceedings of 8th European Conference on Speech Communication and Technology (Eurospeech 2003), pages 2257-2260, 2003.
8. B. D. O. Anderson and J. B. Moore. Optimal Filtering. Prentice-Hall, Inc., 1979.
9. A. Doucet, N. de Freitas, and N. Gordon. An introduction to sequential monte carlo methods. In A Doucet et al., editors, Sequential Monte Carlo Methods in Practice, pages 3-14. Springer-Verlag, 2001.
10. M. I. Miller and D. R. Fuhrmann. Maximum-likelihood narrow-band direction finding and the em algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing, 38:1560-1577, 1990.
11. R. O. Schmidt. Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas Propagation, AP-34:276-280, 1986.
12. T. Yoshimura, F. Asano, Y. Motomura, H. Asoh, N. Ichimura, K. Yamamoto, and S. Nakamura. Detection of speech events in real environments through fusion of audio and video information using bayesian networks. In Proceedings of 2003 International Workshop on Acoustic Echo and Noise Control (IWAENC 2003), pages 319-322, 2003.
13. J. Vermaark and A. Blake. Nonlinear filtering for speaker tracking in noisy and reverberant environments. In Proceedings of 2001 IEEE International Conference on Acoustis, Speech, and Signal Processing, 2001.
14. D. B. Ward, E. A. Lehmann, and R. C. Williamson. Particle filtering algorithms for tracking an acoustic source in a reverberant environment. IEEE Transactions on Speech and Audio Processing, 11:826-836, 2003.
15. K. Yamamoto, N. Kitawaki, F. Asano, I. Hara, J. Ogata, M. Goto, H. Furukawa, and T. Kamashima. Real-time implementation and evaluation of speech event detection and separation based on the fusion of audio and video information. In Proceedings of Embedded Signal Processing Conference at the 2004 Global Signal Processing Expo., to be published.
16. W. Ito, N. Ikoma, and H. Maeda. On association problem for sensor fusion in dynamic situation using particle filters. In Science of Modeling - The 30th Anniversary of the Information Criterion (AIC) - Proceedings: ISM Report on Reserch and Education No. 17, pages 414-415. The Institute of Statistical Mathematics, Japan, 2003.
17. A. Doucet, N. de Freitas, K. Murphy, and S. Russell. Rao-blackwellised particle filtering for dynamic bayesian networks. In Proceedings of Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI 2000), 2000.
18. D. L. Stone, C. A. Barlow, and T. L. Corwin. Bayesian Multiple Target Tracking. Artech House Publishers, 1999.
19. J. Vermaak, C. Andrieu, A. Doucet, and S. J. Godsill. Particle methods for bayesian modeling and enhancement of speech signals. IEEE Transactions on Speech and Audio Processing, 10:173-185, 2002.
20. W. Fong, S. J. Godsill, A. Doucet, and M. West. Monte carlo smoothing with application to audio signal enhancement. IEEE Transactions on Signal Processing, 50:438-449, 2002.
21. P. Heracleous, T. Yamada, S. Nakamura, and K. Shikano. Simultaneous recognition of multiple sound sources based on 3-d n-best search using micro-phone array. In Proceedings of 6th European Conference on Speech Communication and Technology (Eurospeech 1999), pages 69-72, 1999.