In this paper we describe the first stand-alone Augmented Reality (AR) system with self-tracking running on an unmodified personal digital assistant (PDA) with a commercial camera. The project exploits the ready availability of consumer devices with a minimal need for infrastructure. The application provides the user with a three-dimensional augmented view of the environment. Our system achieves good overlay registration accuracy by using a popular marker-based tracking toolkit (ARToolKit), which runs directly on the PDA. We introduce an optional client/server architecture that is based on wireless networking and is able to dynamically and transparently offload the tracking task in order to provide better performance in select areas. The hardware/software framework is modular and can be easily combined with many elements of an existing AR framework. As a demonstration of the effectiveness, we present a 3D navigation application that guides a user through an unknown building to a chosen location.

ledermann @ ims.tuwien.ac.at Abstract. Augmented Reality (AR) can naturally complement mobile computing on wearable devices by providing an intuitive interface to a three-dimensional information space embedded within physical reality. Unfortunately, current wearable AR systems are relatively complex, expensive, fragile and heavy, rendering them unfit for large-scale deployment involving untrained users outside constrained laboratory environments. Consequently, the scale of collaborative multi-user experiments have not yet exceeded a handful of participants. In this paper, we present a system architecture for interactive, infrastructure-independent multi-user AR applications running on off-the-shelf handheld devices. We implemented a four-user interactive game installation as an evaluation setup to encourage playful engagement of participants in a cooperative task. Over the course of five weeks, more than five thousand visitors from a wide range of professional and socio-demographic backgrounds

The continuing proliferation of handheld computing devices holds out the promise for a new generation of computing applications that could enrich our experience of the world around us. Yet many issues must be overcome for this vision to be realized: What applications will enrich our lives? What kinds of interfaces will make them usable in dynamic, social settings? How should the devices themselves be designed? What kind of infrastructure can best support the development and delivery of application services? The UCSD ActiveCampus Project has been investigating these questions in the university campus setting, on the premise that the learning activities of busy students and professors on a large university campus could provide a meaningful application driver for our research in handheld computing. A university is an institution for learning, through both research and teaching. It gathers the learners into a physically proximate community, so that learning can be enhanced b

In this work we investigate building indoor location based applications for a mobile augmented reality system. We believe that augmented reality is a natural interface to visualize spacial information such as position or direction of locations and objects for location based applications that process and present information based on the user's position in the real world. To enable such applications we construct an indoor tracking system that covers a substantial part of a building. It is based on visual tracking of fiducial markers enhanced with an inertial sensor for fast rotational updates. To scale such a system to a whole building we introduce a space partitioning scheme to reuse fiducial markers throughout the environment. Finally we demonstrate two location based applications built upon this facility, an indoor navigation aid and a library search application.

Augmented Reality (AR) provides a natural interface to the "calm" pervasive technology anticipated in large-scale Ubiquitous Computing environments. However, the range of classic AR applications has been limited by the scope, range and cost of sensors used for tracking. Hybrid tracking approaches can go some way to extending this range. We propose an approach, called Ubiquitous Tracking, in which data from widespread and diverse heterogeneous tracking sensors is automatically and dynamically fused, and then transparently provided to applications. A formal model represents spatial relationships between objects as a graph attributed with quality-of-service parameters. This paper presents a software implementation, in which a dynamic data flow network of distributed software components is thereby constructed in response to queries and optimisation criteria specified by applications. This implementation is demonstrated using a small laboratory example, and larger setups modelled in a simulation environment.

The traditional university campus is designed to foster a thriving community of learners, but modernity has introduced many stresses. Mobile computing holds the potential to strengthen a campus's traditional institutions of community through a process of indirect mediation. This paper introduces ActiveCampus, a suite of personal services for sustaining an educational community.

In this paper, we propose a method of personal positioning for a wearable Augmented Reality (AR) system that allows a user to freely move around indoors and outdoors. The user is equipped with selfcontained sensors, a wearable camera, an inertial head tracker and display. The method is based on sensor fusion of estimates for relative displacement caused by human walking locomotion and estimates for absolute position and orientation within a Kalman filtering framework. The former is based on intensive analysis of human walking behavior using self-contained sensors. The latter is based on image matching of video frames from a wearable camera with an image database that was prepared beforehand.

We present a mobile augmented reality (AR) system to guide a user through an unfamiliar building to a destination room. The system presents a world-registered wire frame model of the building labeled with directional information in a see-through heads-up display, and a three-dimensional world-in-miniature (WIM) map on a wrist-worn pad that also acts as an input device. Tracking is done using a combination of wall-mounted ARToolkit markers observed by a head-mounted camera, and an inertial tracker. To allow coverage of arbitrarily large areas with a limited set of markers, a structured marker re-use scheme based on graph coloring has been developed.

Tracking accuracy in a location-aware mobile system can change dynamically as a function of the user’s location and other variables specific to the tracking technologies used. This is especially problematic for mobile augmented reality systems, which ideally require extremely precise position tracking for the user’s head, but which may not always be able to achieve that level of accuracy. While it is possible to ignore variable positional accuracy in an augmented reality user interface, this can make for a confusing system; for example, when accuracy is low, virtual objects that are nominally registered with real ones may be too far off to be of use. To address this problem, we describe an experimental mobile augmented reality system that: (1) employs multiple position-tracking technologies, including ones that apply heuristics based on environmental knowledge; (2) coordinates these concurrently monitored tracking systems; and (3) automatically adapts the user interface to varying degrees of confidence in tracking accuracy. We share our experiences with managing these multiple tracking technologies, employing various techniques to facilitate smooth and reasonable ‘‘hand-offs’ ’ between the cooperating systems. We present these results in the context of a

Tracking is an indispensable part of any virtual reality and augmented reality application. While the need for quality of tracking, in particular for high performance and fidelity, has led to a large body of past and current research, little attention is typically paid to software engineering aspects of tracking software. To address this issue we describe a software design and implementation that applies the pipes-and-filter architectural pattern to provide a customizable and flexible way of dealing with tracking data and configurations. The contribution of this work cumulates in the development of a generic data flow network library called OpenTracker to deal specifically with tracking data. The flexibility of the data flow network approach is demonstrated in a set of development scenarios and prototype applications in the area of mobile augmented reality. 1