Most current augmented reality (AR) displays present content at a fixed focal demand. At the same time, real-world stimuli can occur at a variety of focal distances. To integrate information, users need to switch eye focus between virtual and real-world information continuously. Previously, Gabbard, Mehra, and Swan (2018) examined these issues, using a text-based visual search task on a monocular AR display. This thesis replicated and extended the previous experiment by including a new experimental variable stereopsis (stereo, mono) and fully crossing the variables of context switching and focal distance switching, using AR haploscope. The results from the monocular condition indicate successful replication, which is consistent with the hypothesis that the findings are a general property of AR. The outcome of the stereo condition supports the same adverse effects of context switching and focal distance switching. Further, participants have better performance and less eye fatigue in the stereo condition compared to the monocular condition.

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.