High-quality Augmented Reality Research Articles

Quantitative evaluation of stereoscopic augmented reality visualization using an optical see-through head-mounted display

Purpose The objectives of the current study were to propose a calibration method for accurate augmented reality visualisation using an optical see-through head-mounted display, and to qualitatively evaluate visualisation accuracy for the application in computer assisted surgery. Methods An adaptation of stereo single-point active alignment method was proposed as the calibration procedure together with verification Three tests were performed: display of points in 3D space, on the plane, and on the surface of a skull phantom on inexperience users ( 5 participants) and experienced users ( 17 participants). Results The highest accuracy of visualization was obtained for skull phantom visualisation for an inexperienced user (3.00 mm, std 0.75 mm), while the lowest accuracy was obtained in a 3D visualisation test for an inexperienced user (22.95 mm, std 18.04 mm). The largest error was related to the depth component and amounted to 18.49 mm, std 18.10 mm for an inexperienced user. Conclusions It is possible to achieve relatively high visualisation accuracy (less than 5 mm for visualisation in space) for selected users but providing it for the group of inexperienced users seems to remain a major challenge. The accuracy of point indication can be substantially and statistically significantly increased by visualising objects on surfaces. The proposed methods and obtained results can serve as a basis for further implementation of augmented reality visualisation on an optical see-through head-mounted display in applications requiring high-quality augmented reality guidance of manual tasks.

Localization of 3D objects using model-constrained SLAM

Accurate and real-time camera localization relative to an object is needed for high-quality Augmented Reality applications. However, static object tracking is not an easy task in an industrial context where objects may be textured or not, have sharp edges or occluding contours, be relatively small or too large to be entirely observable from one point of view. This paper presents a localization solution built on a keyframe-based SLAM algorithm. This solution only requires a video stream of a 2D camera (color or grayscale) and the prior knowledge of a 3D mesh model of the object to localize (also named object of interest in this document). The 3D model provides an absolute constraint that drastically reduces the SLAM drift. It is based on 3D-oriented contour points called edgelets, dynamically extracted from the model using Analysis-by-Synthesis on the graphics hardware. This model constraint is then expressed through two different formalisms in the SLAM optimization process. The dynamic edgelet generation ensures the genericity of our tracking method, since it allows to localize polyhedral and curved objects. The proposed solution is easy to deploy, requiring no manual intervention on the model, and runs in real time on HD video streams. It is thus perfectly adapted for high-quality Augmented Reality experiences. Videos are available as supplementary material.

Physics holo.lab learning experience: using smartglasses for augmented reality labwork to foster the concepts of heat conduction

Fundamental concepts of thermodynamics rely on abstract physical quantities such as energy, heat and entropy, which play an important role in the process of interpreting thermal phenomena and statistical mechanics. However, these quantities are not covered by human visual perception, and since heat sensation is purely qualitative and easy to deceive, an intuitive understanding often is lacking. Today immersive technologies like head-mounted displays of the newest generation, especially HoloLens, allow for high-quality augmented reality learning experiences, which can overcome this gap in human perception by presenting different representations of otherwise invisible quantities directly in the field of view of the user on the experimental apparatus, which simultaneously avoids a split-attention effect. In a mixed reality (MR) scenario as presented in this paper—which we call a holo.lab—human perception can be extended to the thermal regime by presenting false-color representations of the temperature of objects as a virtual augmentation directly on the real object itself in real-time. Direct feedback to experimental actions of the users in the form of different representations allows for immediate comparison to theoretical principles and predictions and therefore is supposed to intensify the theory–experiment interactions and to increase students’ conceptual understanding. We tested this technology for an experiment on thermal conduction of metals in the framework of undergraduate laboratories. A pilot study with treatment and control groups (N = 59) showed a small positive effect of MR on students’ performance measured with a standardized concept test for thermodynamics, pointing to an improvement of the understanding of the underlying physical concepts. These findings indicate that complex experiments could benefit even more from augmentation. This motivates us to enrich further experiments with MR.

Fast and automatic city-scale environment modelling using hard and/or weak constrained bundle adjustments

To provide high-quality augmented reality service in a car navigation system, accurate 6 degrees of freedom (DoF) localization is required. To ensure such accuracy, most current vision-based solutions rely on an off-line large-scale modelling of the environment. Nevertheless, while existing solutions to model the environment require expensive equipments and/or a prohibitive computation time, we propose in this paper a complete framework that automatically builds an accurate large-scale database of landmarks using only a standard camera, a low-cost global positioning system (GPS) and a geographic information system (GIS). As illustrated in the experiments, only few minutes are required to model large-scale environments. The resulting databases can then be used by an on-line localization algorithm to ensure high-quality augmented reality experiences.

?Studierstube?: An environment for collaboration in augmented reality

We propose an architecture for multi-user augmented reality with applications in visualisation, presentation and education, which we call "Studierstube". Our system presents three-dimensional stereoscopic graphics simultaneously to a group of users wearing light weight see-through head mounted displays. The displays do not affect natural communication and interaction, making working together very effective. Users see the same spatially aligned model, but can independently control their viewpoint and different layers of the data to be displayed. The setup serves computer supported cooperative work and enhances cooperation of visualisation experts. This paper presents the client-server software architecture underlying this system and details that must be addressed to create a high-quality augmented reality setup.