An important research question for optical see through AR is, “how accurately and precisely can a virtual object’s perceived location be measured in three dimensional space?” Previously, a method was developed for measuring the perceived 3D location of virtual objects using Microsoft HoloLens1 display. This study found an unexplained rightward perceptual bias on horizontal plane; most participants were right eye dominant, and consistent with the hypothesis that perceived location is biased in eye dominance direction. In this thesis, a replication study is reported, which includes binocular and monocular viewing conditions, recruits an equal number of left and right eye dominant participants, uses Microsoft HoloLens2 display. This replication study examined whether the perceived location of virtual objects is biased in the direction of dominant eye. Results suggest that perceived location is not biased in the direction of dominant eye. Compared to previous study’s findings, overall perceptual accuracy increased, and precision was similar.

In augmented reality, information is often distributed between real and virtual contexts, and often appears at different distances from the viewer. This raises the issues of (1) context switching, when attention is switched between real and virtual contexts, (2) focal distance switching, when the eye accommodates to see information in sharp focus at a new distance, and (3) transient focal blur, when information is seen out of focus, during the time interval of focal distance switching. This dissertation research has quantified the impact of context switching, focal distance switching, and transient focal blur on human performance and eye fatigue in both monocular and binocular viewing conditions. Further, this research has developed a novel font that when seen out-of-focus looks sharper than standard fonts. This SharpView font promises to mitigate the effect of transient focal blur. Developing this font has required (1) mathematically modeling out-of-focus blur with Zernike polynomials, which model focal deficiencies of human vision, (2) developing a focus correction algorithm based on total variation optimization, which corrects out-of-focus blur, and (3) developing a novel algorithm for measuring font sharpness. Finally, this research has validated these fonts through simulation and optical camera-based measurement. This validation has shown that, when seen out of focus, SharpView fonts are as much as 40 to 50% sharper than standard fonts. This promises to improve font legibility in many applications of augmented reality.