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A Bayesian Approach to Situated Vision

  • Giuseppe Boccignone
  • Vittorio Caggiano
  • Gianluca Di Fiore
  • Angelo Marcelli
  • Paolo Napoletano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3704)

Abstract

How visual attention is shared between objects moving in an observed scene is a key issue to situate vision in the world. In this note, we discuss how a computational model taking into account such issue, can be designed in a bayesian framework. To validate the model, experiments with eye-tracked human subjects are presented and discussed.

Keywords

Visual Attention Motion Segmentation Average Observer Gaussian Pyramid Local Saliency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Giuseppe Boccignone
    • 1
  • Vittorio Caggiano
    • 1
  • Gianluca Di Fiore
    • 2
  • Angelo Marcelli
    • 1
  • Paolo Napoletano
    • 1
  1. 1.Natural Computation Lab, DIIIEUniversitá diSalernoFisciano (SA)Italy
  2. 2.Co.Ri.Tel. LabsFisciano (SA)Italy

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