A 3D tracking experiment of latency and its compensation methods in virtual environments

摘要

In this paper, we conducted an experiment on the latency and its compensation methods in a virtual reality application using an HMD and a 3D head tracker. Our purpose is to make a comparison both in the simulation and in the real task among four tracker prediction methds: the Grey system theory based prediction proposed in 1994, the Kalman filtering which is sell-known and wide-spreading since 1991, a simple linear extrapolation, and the basic method witout prediction. IN our 3D target tracing task that invvoled eight subjects, who used their head mtiom to trace a flying target in random motion, we have found that when the system latency is 120mas, two prediction methods, Kalman filtering (not inertial-based) and Grey system prediction, are significantly better than the one without prediction, and the former two methods are equallty well in performance. Typical motion trajectories of four methods in simulation are plotted, and jittering effects are examined. In terms of jittering at 120ms prediction length, Kalman filtering was valuated to have the largest.