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A Particle Filtering Algorithm for Audiovisual Speaker Localisation

In modern and innovative videoconference systems and human machine interfaces, localisation techniques play an important role for automatic camera and beamformer steering. Conventional acoustical and visual localisation techniques can be combined to form an audiovisual joint location estimate providing a more robust localisation of the active person. Tracking algorithms such as the well-known Kalman or extended Kalman filter and also particle filters can serve to further improve the location estimates. This paper is about a problem-specific SIR particle filtering algorithm applied to an existing audiovisual speaker localisation. The performance of the suggested algorithm will be evaluated using real audiovisual data based on experiments. It turns out that the proposed algorithm is able to improve the audiovisual location estimates.