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 [BibTeX] [Marc21]
Multimodal Multispeaker Probabilistic Tracking in Meetings
Type of publication: Idiap-RR
Citation: gatica05c
Number: Idiap-RR-66-2004
Year: 2004
Institution: IDIAP
Address: Martigny, Switzerland
Note: in Proc. Int. Conf. on Multimodal Interfaces (ICMI,',','), Trento, Oct. 2005.
Abstract: Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track the location and speaking activity of multiple speakers in a multisensor meeting room, equipped with a small microphone array and multiple uncalibrated cameras. Our framework is based on a mixed-state dynamic graphical model defined on a multiperson state-space, which includes the explicit definition of a proximity-based interaction model. The model integrates audio-visual (AV) data through a novel observation model. Audio observations are derived from a source localization algorithm. Visual observations are based on models of the shape and spatial structure of human heads. Approximate inference in our model, needed given its complexity, is performed with a Markov Chain Monte Carlo particle filter (MCMC-PF,',','), which results in high sampling efficiency. We present results -based on an objective evaluation procedure- that show that our framework (1) is capable of locating and tracking the position and speaking activity of multiple meeting participants engaged in real conversations with good accuracy; (2) can deal with cases of visual clutter and partial occlusion; and (3) significantly outperforms a traditional sampling-based approach.
Userfields: ipdmembership={speech, vision}, language={English},
Projects Idiap
Authors Gatica-Perez, Daniel
Lathoud, Guillaume
Odobez, Jean-Marc
McCowan, Iain A.
Crossref by gatica05c-conf
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Total mark: 0
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