Robotic Vision with the Conformal Camera: Modeling Perisaccadic Perception

Abstract

Humans make about 3 saccades per second at the eyeball's speed of 700 deg/sec to reposition the high-acuity fovea on the targets of interest to build up understanding of a scene. The brain's visuosaccadic circuitry uses the oculomotor command of each impending saccade to shift receptive fields (RFs) to cortical locations before the eyes take them there, giving a continuous and stable view of the world. We have developed a model for image representation based on projective Fourier transform (PFT) intended for robotic vision, which may efficiently process visual information during the motion of a camera with silicon retina that resembles saccadic eye movements. Here, the related neuroscience background is presented, effectiveness of the conformal camera's non-Euclidean geometry in intermediate-level vision is discussed, and the algorithmic steps in modeling perisaccadic perception with PFT are proposed. Our modeling utilizes basic properties of PFT. First, PFT is computable by FFT in complex logarithmic coordinates that also approximate the retinotopy. Second, the shift of RFs in retinotopic (logarithmic) coordinates is modeled by the shift property of discrete Fourier transform. The perisaccadic mislocalization observed by human subjects in laboratory experiments is the consequence of the fact that RFs' shifts are in logarithmic coordinates.