Exhibition Program

Visual motion has critical roles for quickly adjusting posture, eyes, and limbs in dynamic interactions with environments. By behavioral experiments and synthetic model simulations, we have tried to reveal fundamental mechanisms of implicit visuomotor processing. It is difficult to retrieve detailed information about the scene from highly blurred image. However, we found that blurred image sequence can provide higher estimation accuracy of rapid self-motion than the original image sequence. Interestingly, implicit motor responses of hands and eyes are highly sensitive for low-spatial frequency stimuli. These results suggest that the brain knows the importance of low-spatial frequency component to code the high-speed self-motion from the statistical relationship between visual motion and head/posture fluctuation. This type of visuomotor control would be helpful to realize a novel visual processing for moving robot.