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).

Presented are two methods for the determination of the parameters of motion of a sensor, given the vector flow field induced by an imaging system governed by a perspective transformation of a rigid scene. Both algorithms integrate global data to determine motion parameters. The first (the flow circulation algorithm) determines the rotational parameters. The second (the FOE search algorithm) determines the translational parameters of the motion independently of the first algorithm. Several methods for determining when the function has the appropriate form are suggested. One method involves filtering the function by a collection of circular-surround zero-mean receptive fields. The other methods project the function onto a linear space of quadratic polynomials and measures the distance between the two functions. The error function for the first two methods is a quadratic polynomial of the candidate position, yielding a very rapid search strategy.>