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Vision-Based Speaker Detection Using Bayesian Networks

建立日期：2018/02/21
  • 作者： James M. Rehg等
  • 出處： 2006-02-14 Cambridge Research Lab Compaq Computer Corporation
  • 內容： The development of perceptual user interfaces requires the solution of a challenging statistical inference problem:The intentions and actions of multiple individuals must beinferred from noisy and ambiguous vision and speech data.We argue that Bayesian network models are an attractive statistical
    framework for cue fusion in PUI 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.promising experimental results.

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