This paper surveys the field of Augmented Reality, in which 3-D virtual objects are integrated into a 3-D real environment in real time. It describes the medical, manufacturing, visualization, path planning, entertainment and military applications that have been explored. This paper describes the characteristics of Augmented Reality systems, including a detailed discussion of the tradeoffs between optical and video blending approaches. Registration and sensing errors are two of the biggest problems in building effective Augmented Reality systems, so this paper summarizes current efforts to overcome these problems. Future directions and areas requiring further research are discussed. This survey provides a starting point for anyone interested in researching or using Augmented Reality. 1. Introduction 1.1 Goals This paper surveys the current state-of-the-art in Augmented Reality. It describes work performed at many different sites and explains the issues and problems encountered when ...

We present a new tracking system for augmented reality and virtual set applications, based on an inertial navigation system aided by ultrasonic time-of-flight range measurements to a constellation of wireless transponder beacons. An extended Kalman filter operating on 1-D range measurements allows the inertial sensors to filter out corrupt range measurements and perform optimal smoothing and prediction, while at the same time using the pre-screened range measurements to correct the drift of the inertial system. The use of inside-out ultrasonic tracking allows for tetherless tracking over a building-wide range with no acoustic propagation latency. We have created a simulation to account for error sources in the ultrasonic ranging system. The fully implemented tracking system is tested and found to have accuracy consistent with the simulation results. The simulation also predicts that with some further compensation of transducer misalignment, accuracies better than 2 mm can be achieved.

An optoelectronic head-tracking system for head-mounted displays is described. The system features a scalable work area that currently measures 10' x 12', a measurement update rate of 20-100 Hz with 20-60 ms of delay, and a resolution specification of 2 mm and 0.2 degrees. The sensors consist of four head-mounted imaging devices that view infrared lightemitting diodes (LEDs) mounted in a 10' x 12' grid of modular 2' x 2' suspended ceiling panels. Photogrammetric techniques allow the head's location to be expressed as a function of the known LED positions and their projected images on the sensors. The work area is scaled by simply adding panels to the ceiling's grid. Discontinuities that occurred when changing working sets of LEDs were reduced by carefully managing all error sources, including LED placement tolerances, and by adopting an overdetermined mathematical model for the computation of head position: space resecfion by collinearity. The working system was demonstrated in the Tomorrow's Realities gallery at the ACM SIGGRAPH '91 conference.

NICHOLAS MICHAEL VALLIDIS. WHISPER: A Spread Spectrum Approach to Occlusion in Acoustic Tracking.

Tracking for virtual environments is necessary to record the position and the orientation of real objects in physical space and to allow spatial consistency between real and virtual objects. This paper presents a top-down classification of tracking technologies aimed more specifically at head tracking, organized in accordance with their physical principles of operation. Six main principles were identified: time of flight (TOF), spatial scan, inertial sensing, mechanical linkages, phase-difference sensing, and direct-field sensing. We briefly describe each physical principle and present implementations of that principle. Advantages and limitations of these implementations are discussed and summarized in tabular form. A few hybrid technologies are then presented and general considerations of tracking technology are discussed.

The paper is a survey of existing position tracker technologies for Head Mounted Display (HMD) systems. The four major categories of position trackers, magnetic, acoustic, optical and mechanical, are discussed. The chief characteristics, advantages, disadvantages and examples of each cat-egory are described. A set of metrics for comparing the performance of position trackers is identi ed. The expected future trends in the eld are also discussed. 1.

Current HMD applications are hampered by the limitations of head-tracking technologies now in use. Commercially available magnetic, optical, acoustic, and mechanical head-trackers suffer from various problems such as vulnerability to interference, line-of-sight restrictions, jitter, latency, small range, and high cost. This paper presents inertial-sensor-based hybrid tracking technology that was developed to combat all these problems. Two commercially available products, the IS-300 and the IS-600, are described, both based on the same miniature triaxial inertial sensor device. The IS-300 is a sourceless 3-DOF orientation tracker, using gravimetric tilt-sensing to prevent any gyroscopic drift in pitch and roll, and optional geo-magnetic compassing to prevent any gyroscopic drift in yaw. The IS-600 is a hybrid acousto-inertial 6-DOF position and orientation tracking system. It tracks changes in orientation and position by integrating the outputs of its gyros and accelerometers, and corrects drift using a room-referenced ultrasonic time-of-flight range measuring system. This paper overviews the theory of operation of both systems, and reports bench-testing results designed to evaluate the resolution, accuracy, and latency of each system.

A practical and robust head-position tracking method using computer vision is presented. By combining two simple image processing techniques, this tracker can report the position of the user's head in real time. Whole image processing is performed by software running on normal mid-range workstations. This tracker can support desk top virtual reality (also referred to as "fish tank VR"), thereby enabling a user to use a wide range of 3D systems without having to put on any equipment. An experiment conducted by the author suggests this tracker can improve the human's ability in understanding complex 3D structures presented on the display. 1 Introduction One of the major drawbacks in virtual reality (VR) is its cumbersome devices. A typical VR system requires a user to wear goggles and a position tracker on the head for 3D immersion, and a DataGlove for gesture recognition. Although VR has great potential, such equipment prevents users from accessing its capability in normal situations. ...

Current motion tracking technologies fail to provide accurate wide area tracking of multiple users without interference and occlusion problems. These limitations make difficult the construction of a practical and intuitive interface, which allows humans to be inserted into networked virtual environments in a fully immersive manner. Advances in the field of miniature sensors make possible inertial/magnetic tracking of human body limb segment orientation without the limitations of current systems. Due to implementation challenges, inertial/magnetic sensors have not previously been used successfully for full body motion capture. This research proposes to overcome these challenges using multi-axis sensors combined with a quaternion-based complementary filter algorithm capable of continuously correcting for drift and following motion through all orientations without singularities. Primarily,

Estimation of camera pose is an integral part of augmented reality systems. Vision-based methods offer a flexible and accurate method for this estimation. Current vision based methods rely on markers to reduce the computation and increase robustness of the pose estimation. However, this limits the algorithm’s applicability while being expensive since the markers also require maintenance. Alternatively, reconstructed scene features can be used for pose estimation but this can lead to a loss of accuracy. To avoid this we propose a two-stage balanced tracking method which does not require any visual markers in the scene. The first stage of our method is based on the sequential recovery of structure from motion which allows the system to learn the scene from a few frames in which the markers are visible. In the next stage, the learned features are used for camera tracking. The system ensures greater accuracy and reduces error drift due to its use of the HEIV estimator which is provably unbiased to the first degree. We also make use of a novel method for the detection and removal of outliers which are unavoidable in such systems. The experiments show the superiority of our method when compared to a nonlinear method based on Levenberg-Marquardt minimization. 1