The effect of translational ego-motion on the perception of high fidelity animations

Abstract

The quality of the graphics displayed in motion simulators can play a signficant role in improving a user's training experience in such devices. However, the computation of high-fidelity graphics using traditional rendering approaches takes a substantial amount of time, precluding their use in such an interactive environment. This paper investigates exploiting how the human visual system deals with motion, to drive a selective rendering system. Such a selective renderer computes perceptually important parts of a scene in high quality and the remainder of the scene at a lower quality, and thus at a much reduced computational cost, without the user being aware of this quality difference. In this study we concentrate on translational motion and show, even for this less dramatic form of motion, a viewer's perception of a scene can be significantly effected.