Visual motion processing and human tracking behavior

Abstract : The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize tracking performance across time, a quick estimate of the object's global motion properties needs to be fed to the oculomotor system and dynamically updated. Concurrently, performance can be greatly improved in terms of latency and accuracy by taking into account predictive cues, especially under variable conditions of visibility and in presence of ambiguous retinal information. Here, we review several recent studies focusing on the integration of retinal and extra-retinal information for the control of human smooth pursuit. By dynamically probing the tracking performance with well established paradigms in the visual perception and oculomotor literature we provide the basis to test theoretical hypotheses within the framework of dynamic probabilistic inference. We will in particular present the applications of these results in light of state-of-the-art computer vision algorithms.
Type de document :
Chapitre d'ouvrage
Biologically Inspired Computer Vision, 2015, 9783527680863. 〈10.1002/9783527680863.ch12〉
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Contributeur : Laurent Perrinet <>
Soumis le : mercredi 23 novembre 2016 - 16:05:38
Dernière modification le : vendredi 25 mai 2018 - 01:40:31
Document(s) archivé(s) le : mardi 21 mars 2017 - 07:40:06


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Anna Montagnini, Laurent Perrinet, Guillaume S Masson. Visual motion processing and human tracking behavior. Biologically Inspired Computer Vision, 2015, 9783527680863. 〈10.1002/9783527680863.ch12〉. 〈hal-01400748〉



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