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Bayesian Modelling of Perception of Structure from Motion

  • Francis Colas
  • Pierre Bessière
  • Jacques Droulez
  • Mark Wexler
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 46)

Abstract

We use multiple sensory modalities to perceive our environment. One of these is optic flow, the displacement and deformation of the image on the retina. It is generally caused by a relative motion between an observer and the objects in the visual scene. As optic flow depends largely on three-dimensional (3D ) shapes and motions, it can be used to extract structure from motion (the sfm problem). Motion parallax and the kinetic depth effect are special cases of this phenomenon, noticed by Von Helmholtz (1867), and experimentally quantified by Wallach and O’Connell (1953).

Keywords

Bayesian Model Angular Speed Object Plane Reversal Rate Motion Parallax 
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

  • Francis Colas
    • 1
  • Pierre Bessière
    • 2
  • Jacques Droulez
    • 3
  • Mark Wexler
    • 3
  1. 1.INRIA Rhônes-Alpes - E-Motion 
  2. 2.CNRS - Grenoble Université 
  3. 3.Collège de France - LPPA 

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