A common factor among current generation optical see-through augmented reality systems is fixed focal distance to virtual content. In this work, we investigate the issue of focus blur, in particular, the blurring caused by simultaneously viewing virtual content and physical objects in the environment at differing focal distances. We examine the application of dynamic sharpening filters as a straight forward, system independent, means for mitigating this effect improving the clarity of defocused AR content. We assess the utility of this method, termed SharpView, by employing an adjustment experiment in which users actively apply varying amounts of sharpening to reduce the perception of blur in AR content. Our experimental results validate the ability of our SharpView model to improve the visual clarity of focus blurred content, with optimal performance at focal differences well suited for near field AR applications.

With the growing availability of optical see-through (OST) head-mounted displays (HMDs) there is a present need for robust, uncomplicated, and automatic calibration methods suited for non-expert users. This work presents the results of a user study which both objectively and subjectively examines registration accuracy produced by three OST HMD calibration methods: (1) SPAAM, (2) Degraded SPAAM, and (3) Recycled INDICA, a recently developed semi-automatic calibration method. Accuracy metrics used for evaluation include subject provided quality values and error between perceived and absolute registration coordinates. Our results show all three calibration methods produce very accurate registration in the horizontal direction but caused subjects to perceive the distance of virtual objects to be closer than intended. Surprisingly, the semi-automatic calibration method produced more accurate registration vertically and in perceived object distance overall. User assessed quality values were also the highest for Recycled INDICA, particularly when objects were shown at distance. The results of this study confirm that Recycled INDICA is capable of producing equal or superior on-screen registration compared to common OST HMD calibration methods. We also identify a potential hazard in using reprojection error as a quantitative analysis technique to predict registration accuracy. We conclude with discussing the further need for examining INDICA calibration in binocular HMD systems, and the present possibility for creation of a closed-loop continuous calibration method for OST Augmented Reality.