Taking into Account Self-Motion in Depth While Assessing External Motion in Depth

Abstract

During sideways movement of an observer, optic flow parsing – in which an object’s speed is extracted from all the other movement present in the scene – has been shown to be incomplete, with an overestimation of self-motion and an underestimation of object speed, especially when target and observer move in opposite directions (Jörges & Harris, 2022). Here I assess the efficiency of optic flow parsing for an object moving in depth while the observer is also moving either towards or away from the object. Participants were asked to compare the speed of a sphere moving towards or away from them relative to a ball moving sideways either while they were stationary or during visually simulated self-motion. The data showed flow parsing in depth to be incomplete. Curiously, the underestimation of object speed was largely irrespective of whether the ball and the observer moved in the same or opposite directions. These findings may be accounted for by a Bayesian model that includes a “Regression to the Mean Speed” prior.