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The effects of fidelity on navigation in virtual environments

By Simon Lessels


Virtual environments (VEs) offer huge potential for a wide range of applications including the transfer of spatial knowledge from virtual spaces to real world places; beneficial in situations where it would be impractical, too expensive or dangerous, to acquire that knowledge from the real environment. Research has shown that people can acquire near perfect spatial knowledge about real world environments from threedimensional (3D) VEs. However, the rate of learning is substantially slower, and the information less accurate, than that acquired from the real world. It is often assumed that poor navigational ability in VEs is due to the reduced fidelity of the VE system, fidelity is defined as how closely the various components of the VE system resemble those of the real world. This thesis attempts to better understand the effects of, and the relationship between, three aspects of VE fidelity, field of view, visual scene characteristics and the movement interface. Four experimental studies showed that a wide FOV, a high fidelity visual scene, and a simple movement interface, modestly increased participants' ability to navigate effciently in a desktop VE. However, a study that required participants to physically walk around a VE, displayed via a tracked head mounted display (HMD), showed dramatic performance benefits over the use of stationary desktop displays, and a rotationally tracked HMD that required abstract input for translational movement. Proprioceptive and vestibular feedback allowed participants to navigate a VE as efficiently as they did in a real world study. The potential of VEs for spatial applications, such as learning real world spaces, will not be realised without understanding the effects of the VE system on participants' performance and behaviour. The studies reported in this thesis not only provide much needed empirical results that could be of great benefit to VE application designers, but will also be of interest to researchers investigating human navigation

Publisher: School of Computing (Leeds)
Year: 2005
OAI identifier:

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