Active Exploration Using Bayesian Models for Multimodal Perception

  • João Filipe Ferreira
  • Cátia Pinho
  • Jorge Dias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5112)


In this text we will present a novel solution for active perception built upon a probabilistic framework for multimodal perception of 3D structure and motion — the Bayesian Volumetric Map (BVM). This solution applies the notion of entropy to promote gaze control for active exploration of areas of high uncertainty on the BVM so as to dynamically build a spatial map of the environment storing the largest amount of information possible. Moreover, entropy-based exploration is shown to be an efficient behavioural strategy for active multimodal perception.


Bayesian Model Active Exploration Sensor Model Probabilistic Framework Active Perception 
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 2008

Authors and Affiliations

  • João Filipe Ferreira
    • 1
  • Cátia Pinho
    • 1
  • Jorge Dias
    • 1
  1. 1.ISR — Institute of Systems and RoboticsFCT-University of CoimbraCoimbraPortugal

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