Empirical Models Based on Free-Modulus Magnitude Estimation of Perceived Presence in Virtual Environments

Abstract

A series of 3 studies was conducted to test free-modulus magnitude estimation as a measure of perceived presence in virtual environments (VEs) and to model the first-and second-order effects of 11 VE system parameters on perceived presence across 5 subtasks. Sequential experimentation techniques were used to build 4 empirical models using polynomial regression. An integrated empirical model of data combined across 2 experiments demonstrated that all significant factors had a positive effect on perceived presence. Three of these parameters - field of view, sound, and head tracking - had almost 3 times as much influence on presence than the other 4 significant parameters, which were visual display resolution, texture mapping, stereopsis, and scene update rate. Sequential experimentation was an efficient tool for building empirical models of perceived presence, but the subjective nature of this phenomenon and individual differences made data bridging across sequential studies problematic. It was concluded that magnitude estimation is a useful measure of perceived presence, and the resulting polynomial regression models can be used to facilitate VE system design decisions. This research has broad application in the selection and design of VE system components and overall design of VE systems.