Abstract
In order to meet the high precision, strong robust demands of speaker tracking system, this paper proposed a new Particle filter algorithm with unknown noise statistic characteristics. The proposed algorithm estimate and correct the statistic characteristics of the unknown noise on-line by improved Sage-Husa estimator, and produce optimal distribution function with unscented Kalman filter. Finally, it realized speaker tracking problem based on audio-visual fusion in the framework of the new algorithm. Experiment results show that the method proposed in this paper has enhanced the accuracy and robustness of speaker tracking system.
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Acknowledgments
The research was supported by Nation Natural Science Foundation of China (61263031), Natural Science Foundation of Gansu province of China (1010RJZA046).
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Cao, J., Li, J., Li, W. (2013). Speaker Tracking Based on Audio-Visual Fusion with Unknown Noise. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_25
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DOI: https://doi.org/10.1007/978-3-642-38466-0_25
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