This motivated us to investigate the problem of local stimulus disambiguation in an alternative and fundamentally distinct motion-processing model which uses global motion filters for velocity computation.
In the future, these models of motion processing may help us understand how biological details of the fruit fly's visual circuits help it to estimate motion.
"... We propose a parsimonious model of motion processing that generates direction selective responses using short-term synaptic depression and can reproduce salient features of direction selectivity found in a population of neurons in the midbrain of the weakly electric fish Eigenmannia virescens.
It also confirms predictions that V1 is critically involved in normal V5/MT+ global motion processing, consistent with a convergent model of V1 input to V5/MT+.
Thus, unlike much existing work on human activity analysis, the proposed approach is based on general color and motion processing methods, and not on specific models of the human body and its kinematics.
Previous studies have already demonstrated example front-end nonlinearity models that improve naturalistic motion processing by the HRC (Dror et al., 2001; Brinkworth and O'Carroll, 2009).
These results are highly compatible with a neurophysiologically plausible neural model of biological motion processing (Giese and Poggio 2003): a form pathway appears to analyze stimuli as discrete event snapshots, whereas a motion pathway analyzes information based on optic-flow information.
The aim of this work was to establish a principled model of optimal visual motion processing and oculomotor control in the context of sensorimotor delays.
The main point of the paper is that this model fails to account for some qualitative aspects of motion processing (responses to glider stimuli), and that relatively simple extensions of the model enable it to properly predict responses to glider stimuli, and also, substantially improve its accuracy for the naturalistic motion stimuli that are the focus of the paper.
These have included image masking models [29], cortical decompositions [30], extra-cortical motion processing [31], and foveation [29, 32 34], among others.
