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Vision-Based Speaker Detection Using Bayesian Networks

11 years 4 months ago
Vision-Based Speaker Detection Using Bayesian Networks
The development of user interfaces based on vision and speech requires the solution of a challenging statistical inference problem: The intentions and actions of multiple individuals must be inferred from noisy and ambiguous data. We argue that Bayesian network models are an attractive statistical framework for cue fusion in these applications. Bayes nets combine a natural mechanism for expressing contextual information with efficient algorithms for learning and inference. We illustrate these points through the development of a Bayes net model for detecting when a user is speaking. The model combines four simple vision sensors: face detection, skin color, skin texture, and mouth motion. We present some promising experimental results.
James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
Added 12 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 1999
Where CVPR
Authors James M. Rehg, Kevin P. Murphy, Paul W. Fieguth
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