Augmented reality x-ray vision allows users to see through walls and view real occluded objects and locations. We present an augmented reality x-ray vision system that employs multiple view modes to support new visualizations that provide depth cues and spatial awareness to users. The edge overlay visualization provides depth cues to make hidden objects appear to be behind walls, rather than floating in front of them. Utilizing this edge overlay, the tunnel cut-out visualization provides details about occluding layers between the user and remote location. Inherent limitations of these visualizations are addressed by our addition of view modes allowing the user to obtain additional detail by zooming in, or an overview of the environment via an overhead exocentric view.

We have developed a system built on our mobile AR platform that provides users with see-through vision, allowing visualization of occluded objects textured with real-time video information. We present a user study that evaluates the userpsilas ability to view this information and understand the appearance of an outdoor area occluded by a building while using a mobile AR computer. This understanding was compared against a second group of users who watched video footage of the same outdoor area on a regular computer monitor. The comparison found an increased accuracy in locating specific points from the scene for the outdoor AR participants. The outdoor participants also displayed more accurate results, and showed better speed improvement than the indoor group when viewing more than one video simultaneously.

This paper describes techniques to allow both the visualization of hidden objects, and removal of real objects, for a mobile augmented reality user. A gesture based technique is also described which allows the user to select when to view occluded objects. By using the real-time modeling techniques of the Tinmith system, the user is able to create the required geometry to allow image based rendering techniques to be used to render corrected images on the user's display. The images of the hidden objects are captured by a mobile robot platform that is controlled by the mobile user.

This paper describes a new hybrid tracking system that integrates standard outdoor augmented reality trackers with a low cost indoor tracker based on the use of fiducial markers. We use multiple cameras, separate orientation sensing, and scene graph integration to improve on similar previous systems. This hybrid tracker allows applications to operate within large indoor and outdoor environments with minimal scaling costs. Tracking is performed using GPS style world coordinates both indoors and outdoors, and has been integrated into our existing mobile 3D modelling applications.