Interaction with large stereoscopic displays : Fitts and multiple object tracking studies for virtual reality

• Main Author: Rajendran, Vasanth Kumar
• Language: English
• Published: University of British Columbia 2013
• Online Access: http://hdl.handle.net/2429/43788

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.