The use of Optical See-Through (OST) technology for presenting Augmented Reality (AR) experiences is becoming more common. However, OST-AR displays require a calibration procedure, in order to determine the location of the users eyes. Currently, the predominantly cited manual calibration technique is the Single Point Active Alignment Method (SPAAM). However, with the SPAAM technique, there remains uncertainty about the causes of poor calibration results. This paper reports an experiment which examined the influence of two factors on SPAAM accuracy and precision: alignment point distribution, and user posture. Alignment point distribution is examined at user-centered reaching distances, 0.15 to 0.3 meters, as well as environment-centered room-scale distances, 0.5 to 2.0 meters. User posture likely contributes to misalignment error, and is examined at the levels of sitting and standing. In addition, a control condition replaces the user with a rigidly-mounted camera, and mounts the OST display on a precisely-adjustable tripod. The experiment finds that user-centric distributions are more accurate than environment-centric distributions, and, somewhat surprisingly, that the users posture has no effect. The control condition replicates these findings. The implication is that alignment point distribution is the predominant mode for induction of calibration error for SPAAM calibration procedures.

The use of Optical See-Through Head-Mounted Displays (OST-HMDs) for presenting Augmented Reality experiences has become more common, due to the increasing availability of lower cost head-worn device options. Despite this growth, commercially available OST hardware remains devoid of the integrated eye-tracking cameras necessary for automatically calibrating user-specific view parameters, leaving manual calibration methods as the most consistently viable option across display types. The Single Point Active Alignment Method (SPAAM) is currently the most-cited manual calibration technique, due to the relaxation of user constraints with respect to allowable motion during the calibration process. This work presents the first formal study directly investigating the effects that alignment point distribution imposes on SPAAM calibration accuracy and precision. A user experiment, employing a single expert user, is presented, in which SPAAM calibrations are performed under each of five conditions. Four of the conditions cross alignment distance (arm length, room scale) with user pose (sitting, standing). The fifth condition is a control condition, in which the user is replaced with a rigidly mounted camera; the control condition removes the effect of noise from uncontrollable postural sway. The final experimental results show no significant impact on calibration due to user pose (sitting, standing). The control condition also did not differ from the user produced calibration results, suggesting that posture sway was not a significant factor. However, both the user and control conditions show significant improvement using arm's length alignment points over room scale alignments, with an order of magnitude difference in eye location estimate error between conditions.

Optical see-through head-mounted displays (OST HMDs) are a major output medium for Augmented Reality, which have seen significant growth in popularity and usage among the general public due to the growing release of consumer-oriented models, such as the Microsoft Hololens. Unlike Virtual Reality headsets, OST HMDs inherently support the addition of computer-generated graphics directly into the light path between a user's eyes and their view of the physical world. As with most Augmented and Virtual Reality systems, the physical position of an OST HMD is typically determined by an external or embedded 6-Degree-of-Freedom tracking system. However, in order to properly render virtual objects, which are perceived as spatially aligned with the physical environment, it is also necessary to accurately measure the position of the user's eyes within the tracking system's coordinate frame. For over 20 years, researchers have proposed various calibration methods to determine this needed eye position. However, to date, there has not been a comprehensive overview of these procedures and their requirements. Hence, this paper surveys the field of calibration methods for OST HMDs. Specifically, it provides insights into the fundamentals of calibration techniques, and presents an overview of both manual and automatic approaches, as well as evaluation methods and metrics. Finally, it also identifies opportunities for future research.

The growing prevalence of hand and gesture tracking technology has led to an increased availability of consumer level devices, such as the Leap Motion controller, and also facilitated the inclusion of similar hardware into forth coming head mounted display offerings, including the Microsoft HoloLens and Moverio Pro BT-2000. In this video, we demonstrate the utility of the Leap Motion for calibrating optical see-through augmented reality systems by employing a variation on Tuceryan and Navab's Single Point Active Alignment Method [3]. We also showcase a straightforward method for calibrating the coordinate frame of the Leap Motion to a secondary tracking system by employing absolute orientation algorithms [2, 1, 4], allowing us to properly transform and visualize hand and finger tracking data from the user's viewpoint. Our combined display and coordinate frame calibration techniques produce a viable mechanism for not only intuitive interaction with virtual objects but also the creation of natural occlusion between computer generated content and the user themselves. We believe that these techniques will be pivotal in the development of novel consumer applications for next generation head mounted display hardware.

Next generation OST HMDs promise the inclusion of a variety of integrated and on-board sensors. In particular, hand tracking cameras, such as the Leap Motion, show potential for facilitating intuitive OST calibration procedures accessible to researchers, developers, and novice users alike. In this work, we evaluate hand and stylus based OST calibration utilizing tracking data from a Leap Motion. Our findings show that performance of both methods is comparable to results from prior studies using standard environment-centric methods. Also, while our hand based calibration improved through the use of more contextual reticle designs, calibrations performed with a stylus yielded the most accurate and precise results over all.

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.

Correct spatial alignment is an essential requirement for convincing augmented reality experiences. Registration error, caused by a variety of systematic, environmental, and user influences decreases the realism and utility of head mounted display AR applications. Focus is often given to rigorous calibration and prediction methods seeking to entirely remove misalignment error between virtual and real content. Unfortunately, producing perfect registration is often simply not possible. Our goal is to quantify the sensitivity of users to registration error in these systems, and identify acceptability thresholds at which users can no longer distinguish between the spatial positioning of virtual and real objects. We simulate both video see-through and optical see-through environments using a projector system and experimentally measure user perception of virtual content misalignment. Our results indicate that users are less perceptive to rotational errors over all and that translational accuracy is less important in optical see-through systems than in video see-through.

We are investigating methods for improving the robustness and consistency of the Single Point Active Alignment Method (SPAAM) optical see-through (OST) head-mounted display (HMD) calibration procedure. Our investigation focuses on two variants of SPAAM. The first utilizes a standard monocular alignment strategy to calibrate the left and right eye separately, while the second leverages stereoscopic cues available from binocular HMDs to calibrate both eyes simultaneously. We compare results from repeated calibrations between methods using eye location estimates and inter pupillary distance (IPD) measures. Our findings indicate that the stereo SPAAM method produces more accurate and consistent results during calibration compared to the monocular variant.

The current advent of consumer level optical see-through (OST) head-mounted displays (HMD's) has greatly broadened the accessibility of Augmented Reality (AR) to not only researchers but also the general public as well. This increased user base heightens the need for robust automatic calibration mechanisms suited for nontechnical users. We are developing a fully automated calibration system for two stereo OST HMD's, a consumer level and prototype model, based on the recently introduced interaction free display calibration (INDICA) method. Our current efforts are also focused on the development of an evaluation process to assess the performance of the system during use by non-expert subjects.

Summary form only given. Effectively evaluating optical see-through (OST) head-mounted display (HMD) calibration is problematic and largely relies on feedback from the user. Studies evaluating OST HMD calibration, such as those by McGarrity, Tang, and Navab et al. [2, 3, 1], utilize user interaction methods, such as touch pads, to facilitate on-line evaluation and correction of calibration results. In all of these studies, however, only the users themselves receive any visual feedback related to the calibration quality or the corrective actions taken to improve it. In this video, we present the use of standard frustum visualization to provide calibration quality information to the researcher in real time. We use a standard Single Point Active Alignment Method (SPAAM) calibration, [4], after which both the eye location estimate and resulting intrinsic values are displayed superimposed onto the user. Presenting the eye position relative to the user's head benefits studies on system error sources, and rendering on-screen visuals also allows outside observers to identify calibration issues and offer corrective suggestions. We believe that techniques, such as frustum visualization, will expand the amount of information available for evaluating calibration results, and will greatly aid those investigating new and improved calibration procedures.

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.

We have conducted an experiment to study the effect of an occluding surface on the accuracy of near field depth matching in augmented reality (AR). Our experiment was based on replicating a similar experiment conducted by Edwards et al. [2]. We used an AR haploscope [1], which allows us to independently manipulate accommodative demand and vergence angle of the visible image. Fifteen observers matched the perceived depth of an AR-presented virtual object with a physical pointer. Overall, observers overestimated depth by 5 mm or less in the presence of the occluder, while in the absence of an occluder they overestimated depth by 5 to 10 mm. The data from Edwards et al. [2] is normalized, and when we performed the same normalization procedure on our own data, our results do not agree with Edwards et al. [2]. We suspect that eye vergence explains these results.

A common problem with Optical See-Through (OST) Augmented Reality (AR) is misalignment or registration error with the amount of acceptable error being heavily dependent upon the type of application. Approximation methods, driven by user feedback, have been developed to estimate the necessary corrections for alignment errors. These calibration methods, however, are susceptable to induced error from system and environmental sources, such as human alignment error. The proposed research plan is intended to further the development of accurate and robust calibration methods for OST AR systems by quantifying the impact of specific factors shown to contribute to calibration error. An important aspect of this research will be to develop methods for examining each factor in isolation in order to determine the independent error contribution of each source. This will facilitate the establishment of acceptable thresholds for each type of error and be a meaningful step toward defining quality metrics for OST AR calibration techniques.

We conducted an experiment in an attempt to generate baseline accuracy and precision values for optical see-through (OST) head mounted display (HMD) calibration without the inclusion of human postural sway error. This preliminary work will act as a control condition for future studies into postural error reduction. An experimental apparatus was constructed to allow performance of a SPAAM calibration using 25 alignments taken using one of three distance distribution patterns: static, sequential, and magic square. The accuracy of the calibrations were determined by calculating the extrinsic X, Y, Z translation values from the resulting projection matrix. The standard deviation for each translation component was also calculated. The results show that the magic square distribution resulted in the most accurate parameter estimation and also resulted in the smallest standard deviation for each extrinsic translation component.

An experiment was conducted to investigate the utility of a number of iconographic styles in relaying ordinal depth information at vista space distances of more than 1900m. The experiment consisted of two tasks: distance judgments with respect to discrete zones, and ordinal depth determination in the presence of icon overlap. The virtual object representations were chosen based on their effectiveness, as demonstrated in previous studies. The first task is an adaptation of a previous study investigating distance judgments of occluded objects at medium field distances. We found that only one of the icon styles fared better than guessing. The second is a novel task important to situation awareness and tested two specific cases: ordinal depth of icons with 50% and 100% overlap. We found that the case of full overlap made the task effectively impossible with all icon styles, whereas in the case of partial overlap, the Ground Plane had a clear advantage.

A previous study indicated that peripheral visual information strongly affects the judgment of egocentric distances for users of immersive virtual environments. The experiment described in this document aimed to investigate if these effects could be explained in terms of changes in gait caused by visual information in the extreme periphery. Three conditions with varying degrees of peripheral occlusion were tested and participants' walking characteristics measured. The results indicate that the improvements in distance judgments, as peripheral information increases, can only partially be explained in terms of gait modification, but likely involve both changes in the characteristics of gait and other spatial or movement parameters.