A bayesian model for the measurement of visual velocity.

Several models have been proposed for how the brain measures velocity from the output of motion-energy units. These models make some unrealistic assumptions such as the use of Gabor-shaped temporal filters, which are non causal, or flat spatial spectra, which are invalidated by existing data. We present a Bayesian model of velocity perception, which makes more realistic assumptions and allows the estimation of local retinal velocity regardless of the specific mathematical form of the spatial and temporal filters used. The model is consistent with several aspects of speed perception, such as the dependence of perceived speed on contrast.