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Virtual content on optical see-through head-mounted displays (OST-HMDs) appears dim in bright environments. In this paper, we demonstrate how a liquid crystal (LC) filter can be used to dynamically increase the perceived brightness of the virtual content. Continuously adjusting the LC filter opacity attenuates the real scene and increases the perceived brightness without being noticed by the user...
In this paper we describe a new method for determining gaze depth in a head mounted eye-tracker. Eye-trackers are being incorporated into head mounted displays (HMDs), and eye-gaze is being used for interaction in Virtual and Augmented Reality. For some interaction methods, it is important to accurately measure the x-and y-direction of the eye-gaze and especially the focal depth information. Generally,...
Properly calibrating an optical see-through head-mounted display (OST-HMD) and maintaining a consistent calibration over time can be a very challenging task. Automated methods need an accurate model of both the OST-HMD screen and the user's constantly changing eye-position to correctly project virtual information. While some automated methods exist, they often have restrictions, including fixed eye-cameras...
The human visual system always focuses at a distinct depth. Therefore, objects that lie at different depths appear blurred, a phenomenon known as Depth of Field (DoF); as the user's focus depth changes, different objects come in and out of focus. Augmented Reality (AR) is a technology that superimposes computer graphics (CG) images onto a user's view of the real world. A commonly used AR display device...
Localizing the user from a feature database of a scene is a basic and necessary step for presentation of localized augmented reality (AR) content. Commonly such database depicts a single appearance of the scene, due to time and effort required to prepare it. To account for appearance changes under different lighting we propose to generate the feature database from a simulated appearance of the scene...
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...
We present a framework that enables 6DoF camera localization in outdoor environments by providing visual feature descriptors with an Absolute Spatial Context (ASPAC). These descriptors combine visual information from the image patch around a feature with spatial information, based on a model of the environment and the readings of sensors attached to the camera, such as GPS, accelerometers, and a digital...
In recent years optical see-through head-mounted displays (OST-HMDs) have moved from conceptual research to a market of mass-produced devices with new models and applications being released continuously. It remains challenging to deploy augmented reality (AR) applications that require consistent spatial visualization. Examples include maintenance, training and medical tasks, as the view of the attached...
The human eyes perceive our surroundings and are one of, if not our most important sensory organs. Contrary to our other senses the eyes not only perceive but also provide information to a keen observer. However, thus far this has been mainly used to detect reflection of infrared light sources to estimate the user's gaze. The reflection of the visible spectrum on the other hand has rarely been utilized...
We present an approach which enables real-time augmentation of an environment composed of materials with different texture and reflectance properties without the need of application-specific hardware or extensive preparation. Our solution uses a set of RGB images of a reconstructed model to optimize the reflectance parameters and light location. Each image is decomposed into its specular and diffuse...
We introduce an in-situ lighting and reflectance estimation method that does not require specific light probes and/or preliminary scanning. Our method uses images taken from multiple viewpoints while data accumulation and lighting and reflectance estimations run in the background of the primary AR system. As a result, our method requires little in the way of manipulations for image collection because...
We introduce the first publicly available test dataset for outdoor handheld camera localization comprising over 45,000 real camera images of an urban environment captured under natural camera motions and different illumination settings. For all these images the dataset not only contains readings of the sensors attached to the camera, but also ground truth information on the geometry and texture of...
Photometric registration is one of the more challenging problems related to augmented reality (AR) because the simultaneous estimations of both lighting and reflectance are especially difficult problems due to large number of parameters and ill-posed problems. As a result, most currently utilized lighting and reflectance estimation methods employ light probes such as mirror spheres, omnidirectional...
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