Abstract
Two studies measured human performance in virtual
environments, one for mid-air pointing and one for multiple object
tracking. Mid-air pointing is similar to pointing in everyday life:
it relies on the human sensorimotor system and it
is unconstrained by contact with a surface or object.
Multiple object tracking is the
perceptual and cognitive process of maintaining awareness of the
individual identities of a set of objects that are changing their
relative locations within a visual scene. Both tasks are often components
of training or simulation systems in virtual environments. We
investigated how performance in each is affected by the virtual
environment and how that might be used to better calibrate virtual
environments for optimal "real world" performance.
Fitts's Law predicts movement time as a function of movement amplitude
and target width. It is used to evaluate pointing performance in
computer applications, including those for virtual environments. It has
proven extremely robust. However, alternative two-part models, such as
Welford's, are sometimes more accurate. One-part models consider only
the ratio of movement amplitude and target width; two-part models treat
each as independent variables.
We conducted a Fitts-style study of pointing performance in a
virtual environment that varied physical distance to the
screen and virtual distance to the targets. We found that Welford-style
two-part models predicted pointing time significantly better than
did Fitts-style one-part models using an F-test on the
goodness of fit (R²). The separable
contributions of movement amplitude and target width were
captured in a parameter derived from the two-part models that varies linearly
with the virtual distance to targets. We describe how to use
the parameter to calibrate a VR environment for pointing tasks.
We designed a second study of multiple object tracking in VR
environments to determine whether tracking performance might differ in a
virtual environment. Results from a pilot experiment were not
conclusive. Tracking accuracy for 3D followed the same pattern as for
2D; so, additional studies will be required to determine if there are
differences.
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