Bayesian Modality Fusion : Probabilistic Integration of Multiple Vision Algorithms for Head Tracking

  title={Bayesian Modality Fusion : Probabilistic Integration of Multiple Vision Algorithms for Head Tracking},
  author={Kentaro Toyama and Eric Horvitz},
We describe a head-tracking system that harnesses Bayesian modality fusion, a technique for integrating the analyses of multiple visual tracking algorithms within a probabilistic framework. At the heart of the approach is a Bayesian network model that includes random variables that serve as context-sensitive indicators of reliability of the different tracking algorithms. Parameters of the Bayesian model are learned from data in an offline training phase using ground-truth data from a Polhemus… CONTINUE READING
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