With the widespread deployment of fast data connections and availability of a variety of sensors for different modalities, the potential of remote collaboration has greatly increased. While the now ubiquitous video conferencing applications take advantage of some of these capabilities, the use of video between remote users is limited to passively watching disjoint video feeds and provides no means for interaction with the remote environment. However, collaboration often involves sharing, exploring, referencing, or even manipulating the physical world, and thus tools should provide support for these interactions.

We suggest that augmented reality is an intuitive and user-friendly paradigm to communicate information about the physical environment, and that integration of computer vision and augmented reality facilitates more immersive and more direct interaction with the remote environment than what is possible with today's tools.

In this dissertation, we present contributions to realizing this vision on several levels. First, we describe a conceptual framework for unobtrusive mobile video-mediated communication in which the remote user can explore the live scene independent of the local user's current camera movement, and can communicate information by creating spatial annotations that are immediately visible to the local user in augmented reality. Second, we describe the design and implementation of several, increasingly more flexible and immersive user interfaces and system prototypes that implement this concept. Our systems do not require any preparation or instrumentation of the environment; instead, the physical scene is tracked and modeled incrementally using monocular computer vision. The emerging model then supports anchoring of annotations, virtual navigation, and synthesis of novel views of the scene. Third, we describe the design, execution and analysis of three user studies comparing our prototype implementations with more conventional interfaces and/or evaluating specific design elements. Study participants overwhelmingly preferred our technology, and their task performance was significantly better compared with a video-only interface, though no task performance difference was observed compared with a "static marker'' interface. Last, we address a particular technical limitation of current monocular tracking and mapping systems which was found to be impeding and present a conceptual solution; namely, we describe a concept and proof-of-concept implementation for automatic model selection which allows tracking and modeling to cope with both parallax-inducing and rotation-only camera movements.

We suggest that our results demonstrate the maturity and usability of our systems, and, more importantly, the potential of our approach to improve video-mediated communication and broaden its applicability.