Perception des objets en mouvement
Composition bayésienne du flux optique et du mouvement de l'observateur

Francis Colas 1
1 E-MOTION - Geometry and Probability for Motion and Action
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes
Abstract : Perception can be seen as collecting and confronting various pieces of information in order to understand the environment. One uses many semsory modalities each one consisting of many kind of information. One of these is the optic flow, the displacement of the projected image on the retina.
Optic flow allows for the extraction of part of the geometry of the observed scene. However, it is a very complex problem due to its inverse, ill-posed and uncertain nature.
These issues can be dealt with using the Bayesian programming formalism. It is based on the probabilities, to handle uncertainty and the ill-posed problem, and on Bayes rule, to solve the inversion.
We propose a Bayesian model of the perception of planes from optic flow based on few explicit assumptions. These assumptions are mainly the rigidity, which assumes the observation of a rigid plane is more probable than of a collection of independently-moving points, and the stationarity, which assumes the motion of the plane is more probably small.
We validate our model using five experiments from the literature. For each one, we explain in details the inner workings of our model and the assumptions conditionning a good reproduction of the experimental results. Finally, we show how to adapt our model to an experiment of perception of a corrgated surface by optic flow. We also present a Bayesian model to generate the input of our perception model and generalise the integration of our model into a more complete system.
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Submitted on : Thursday, June 15, 2006 - 11:41:33 AM
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Francis Colas. Perception des objets en mouvement
Composition bayésienne du flux optique et du mouvement de l'observateur. Autre [cs.OH]. Institut National Polytechnique de Grenoble - INPG, 2006. Français. ⟨tel-00080229⟩

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