Near-field virtual reality allows users to interact with virtual objects within arm's reach of the user. Environments for near-field VR are well suited for direct precise interaction by taking advantage of the user's hand-eye co-ordination.

The field of ubiquitous computing envisages an era when the average consumer owns hundreds or thousands of mobile and embedded computing devices. These devices will perform actions based on the context of their users, and therefore ubiquitous systems will gather, collate and distribute much more personal information about individuals than computers do today. Much of this personal information will be considered private, and therefore mechanisms which allow users to control the dissemination of these data are vital. Location information is a particularly useful form of context in ubiquitous computing, yet its unconditional distribution can be very invasive.

In this paper, we describe a new optical tracker algorithm Jbr the tracking of interaction devices in virtual and augmented reality. The tracker uses invariant properties of marker patterns to efficiently identt.' and reconstruct the pose of these interaction devices. Since invariant properties are sensitive to noise in the 2D marker positions, an off-line training session is used to determine deviations in these properties. These deviations are taken into account when searching Jbr the patterns once the tracker is used.

This paper presents an approach to use a semitransparent display as a kind of window into a patient in the context of medical Augmented Reality (AR) applications. Besides the presentation of the non-off-the-shelf display, the tracking aspects of such an application are in focus of the work presented. In order to allow augmentations of real objects by virtual ones on the display, the user (i.e. physician), the display, the object (i.e. patient) and optional instruments have to be tracked. If required, a tracking system consisting of more than one subsystem, e.g. optical tracking combined with electromagnetic tracking, is used to satisfy all the needs of such a medical application. 1

This paper presents novel methods for increasing the robustness of visual tracking systems by incorporating information from inertial sensors. We show that more can be achieved than simply combining the sensor data within a statistical filter. In particular we show how, in addition to using inertial data to provide predictions for the visual sensor, this data can also be used to provide an estimate of motion blur for each feature and this can be used to dynamically tune the parameters of each feature detector in the visual sensor. This allows the system to obtain useful information from the visual sensor even in the presence of substantial motion blur. Finally, the visual sensor can be used to calibrate the parameters of the inertial sensor to eliminate drift.

this report, we can say that research toward system that are able to track natural markers/landmarks is still an open problem, fruitful, and attractive. The mobility of a such tracking system is also an open problem. Almost all systems are fixed in the environment and they cannot move freely without extra efforts (e.g., new calibration): they gain to be more flexible and lightweight

Complex Assembly and Maintenance tasks in industrial environments are excellent domains for Augmented Reality (AR) applications. The need for good training and the access to large amounts of documentation are conditions making the use of AR techniques most promising. The basic idea of Augmented Reality is to bring additional information as seamlessly as possible into the view of a user. In this paper an AR system for training and assisting in maintaining equipment in industrial context is presented. The key hardware features of the system are an optical see-through Head Mounted Display, which superimposes the augmentations in the view of the user; the tracking system, which gives the system the poses of user and equipment; and a special stand for the installation of the whole application. Aspects of the usage of an infrared optical tracking system and the calibration procedures needed for good results of the virtual overlays are discussed. Finally a scenario-based concept, which takes users step by step through training or maintenance tasks, is described.

Augmented Reality - best described as adding computer-generated virtual content to the real environment -- needs more adjustments to work properly than immersive virtual environments. To be perceived as an augmentation of reality, the virtual environment has to be properly aligned to the real world. This registration process has to be done at least once for every hardware set-up, but may have to be repeated in part or completely for each user, prop or device to be included both in the real and the virtual world. In this paper, we propose a comprehensive process for registration and calibration tasks necessary to implement correct augmentation. This includes procedures for calibrating projective and head-mounted displays, tracking systems, tracked input devices and props. Our method unifies the necessary tasks of world-toaugmentation alignment, display calibration and registration of tracked and static props in one, interactive set-up process, which can easily be conducted by the untrained user.

We present a system for planar augmented reality based on a new real-time affine region tracker. Instead of tracking fiducial points, we track planar local image patches, and bring these into complete correspondence, so a virtual texture can directly be added to them. Moreover, the local image patches can be extracted in an invariant way, even without any a priori information from previous frames. Hence it is possible to use them as natural beacons, that can be used to recognize the scene and to identify the individual patches. This results in a powerful system, that can work without artificial markers or fiducial points and with a minimal amount of user interference.

expensive, intrusive, cumbersome and brittle nature of the sensors that are required to detect user's intent. While optical tracking, being wireless with respect to the user's body, has been regarded as one solution to this usability aspect, the traditional problems of establishing marker correspondence and resolving their occlusions in real time still remain. One avenue of efforts to address these problems is to simply add more and more hardware (or processing power), making the tracking system too expensive for general usage, while another major effort looks to directly track human body parts, but usually suffers from the inability to track point features. In this paper, we present a relatively inexpensive (e.g. runs on a high-end PC), but reasonably accurate real time optical motion tracking system, called the "POSTRACK", that can still find a wide range of applications for VR. POSTRACK uses four cheap &bit grayscale cameras attached with infrared LED's, and the user wears several (1-5) highly reflective markers. The markers are "designed" to be very easy to wear (snap-on), and even fashionable. The four cameras are calibrated using well known algorithms, and the initial marker assignments are found by a simple heuristic based on the normal human posture, while the fundamental matrices are used to find blob correspondence and compute the 3D positions of the markers. Since the snap-on markers are rather large and their positions are computed from their image centroids (which constantly change), the computed 3D position data are jittery, more so than other trackers that use much smaller marker sizes, or compared to magnetic trackers. While the technology is old (i.e. uses standard vision and stereo algorithms), the engineering of the POSTRACK strikes a good balance bet...