Learning to estimate user interest utilizing the variational Bayes estimator

  • Authors:
  • Taiji Suzuki;Kazuyuki x. Kazuyuki Aihara;Takamasa Koshizen;Hiroshi Tsujino

  • Affiliations:
  • University of Tokyo;University of Tokyo;Honda Research Institute Japan Co. Ltd .;Honda Research Institute Japan Co. Ltd .

  • Venue:
  • ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
  • Year:
  • 2005

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Abstract

Many studies of Man-machine interaction using eye trackers have been tackled over recent decades. In this paper, we present a new learning system to estimate user interest with gaze sensory information. In short, a statistical learning scheme, especially the variational bayes (VB), is incorporated for building probabilistic model parameters, dealing with the uncertainty of estimated user interest. Several computational results show how the VB can cope with user interest estimation, by selectively modeling their uncertainty.