The two papers in this special section are extended versions of papers originally presented at the International Symposium on Mixed and Augmented Reality (ISMAR) 2007. These two papers won awards at the symposium.

This paper describes our on-going efforts to develop an augmented reality system for enhanced pilot situational awareness in airport runways and taxiways. The system consists of a sensing component based on computer vision and an information component based on high-fidelity graphic model databases. Vision algorithms are used for a variety of guidance and warning tasks. A necessary requirement is for vision algorithms to have a real-time response.

Augmented reality (AR) presentations may be visual or auditory. Auditory presentation has the potential to provide hands-free and visually non-obstructing cues. Recently, we have developed a 3D audio wearable system that can be used to provide alerts and informational cues to a mobile user in such a manner as to appear to emanate from specific locations in the user's environment. In order to study registration errors in 3D audio AR representations, we conducted a perceptual training experiment in which visual and auditory cues were presented to observers. The results of this experiment suggest that perceived registration errors may be reduced through head movement and through training presentations that include both visual and auditory cues.

Outdoor augmented reality (AR) applications rely on hybrid tracking (GPS, digital compass, visual) for registration. RSC has developed a real-time visual tracking system that uses visual cues of buildings in an urban environment for correcting the results of a conventional tracking system. This approach relies on knowledge of a CAD model of the building. It not only provides motion estimation, but also absolute orientation/position. It is based on the "visual servoing" approach, originally developed for robotics tasks. We have demonstrated this approach in real-time at a building on the NRL campus This poster shows the approach and results. The concept can be generalized to any scenario where a CAD model is available. This system is being prepared for integration into the NRL system BARS (Battlefield Augmented Reality System).

Registration for outdoor systems for Augmented Reality (AR) cannot rely on the methods developed for indoor use (e.g., magnetic tracking, fiducial markers). Although GPS and the earth's magnetic field can be used to obtain a rough estimate of position and orientation, the precision of this registration method is not high enough for satisfying AR overlay. Computer vision methods can help to improve the registration precision by tracking visual clues whose real world positions are known. We have developed a system that can exploit horizon silhouettes for improving the orientation precision of a camera which is aligned with the user's view. It has been shown that this approach is able to provide registration even as a stand-alone system, although the usual limitations of computer vision prohibit to use it under unfavorable conditions. This paper describes the approach of registration by using horizon silhouettes. Based on the known observer location (from GPS), the 360 degree silhouette is computed from a digital elevation map database. Registration is achieved, when the extracted visual horizon silhouette segment is matched onto this predicted silhouette. Significant features (mountain peaks) are cues which provide hypotheses for the match. Several criteria are tested to find the best matching hypothesis. The system is implemented on a PC under Windows NT. Results are shown in this paper.

Autonomous rides on public roads performed by a seeing road vehicle under normal traffic conditions have been demonstrated on German Autobahnen since the beginning of 1992. Meanwhile, the new goal of autonomous driving on roads of lower order has been approached by including the turn-off at intersections. Tests have been performed on a specially designed test track including curves with radii from 35-100 m and an intersection. This paper gives a short overview on the applied algorithms as well as the control structure of the system which was developed at the Universitat der Bundeswehr Munchen. A summary of experimental results for autonomous rides points out the applicability of the approach.

An intelligent cruise control system for automatic vehicle guidance on German 'autobahnen' is discussed. Recent developments have focused on the vision system, which has reached a new level of performance, compactness and robustness by the use of high performance computers. The system has been integrated in VaMP, the autonomous vehicle of UBM. Extensive test driving on German, French and Danish 'autobahnen' has been performed. Finally, a long-distance ride from Munich (Germany) to Odense (Denmark) is discussed.

The vision system for autonomous road vehicle guidance, which has been developed during the last years at the UniBwM, is currently being ported from 5 ton vans to a family sedan (Mercedes 500 SEL). The cruising speed of 120 km/h, which the system is designed for, requires a further maximal look-ahead distance for road and obstacle recognition. For achieving high robustness, it is necessary to estimate the camera pitch angle as an additional state parameter. In this paper an approach for simultaneous estimation of pitch angle and lane width from the road image is presented, both based on Kalman filtering. The pitch angle is modelled by a damped harmonical oscillator with a given frequency /spl omega//sub 0/, a time constant r, and a pitch offset. For a change in the lane width, a linear dynamical model is assumed. The estimators are validated by numerical simulations. Evaluation of video scenes, shot from the sedan vehicle, show good results for pitch and lane width estimation.>

An integrated system for visual road vehicle guidance has been created on transputer-hardware and partly validated in normal Autobahn traffic environments. The computer vision and dynamic scene understanding components are discussed. The system is capable of recognizing horizontal and vertical curvature of the lane, lane width, number of lanes, the state of the vehicle relative to the lane, and the relative state of two other objects by recursive monocular estimation following the 4-D approach as a unifying scheme for 3-D dynamic scene understanding through motion stereo. The architecture realized on transputer hardware is described. Experimental results with a 5-ton van are discussed.>