A Bayesian model for estimating observer translation and rotation from optic flow and extra-retinal input.
We present a Bayesian ideal observer model that estimates observer translation and rotation from optic flow and an extra-retinal eye movement signal. The model assumes a rigid environment and noise in velocity measurements, and that eye movement provides a probabilistic cue for rotation. The model can simulate human heading perception across a range of conditions, including: translation with simulated vs. actual eye rotations, environments with various depth structures, and the presence of independently moving objects.
Saunders
Jeffrey A
JA
Department of Psychology, University of Hong Kong, Hong Kong. jsaun@hkucc.hku.hk
Niehorster
Diederick C
DC
D001499:Bayes Theorem; D005133:Eye Movements / Q000502:physiology*; D006801:Humans; D009039:Motion Perception / Q000502:physiology*; D057849:Optic Flow / Q000502:physiology*; D012160:Retina / Q000502:physiology*