Supporting interaction in augmented reality in the presence of uncertain spatial knowledge

Abstract

A significant problem encountered when building Augmented Reality (AR) systems is that all spatial knowledge about the world has uncertainty associated with it. This uncertainty manifests itself as registration errors between the graphics and the physical world, and ambiguity in user interaction. In this paper, we show how estimates of the registration error can be leveraged to support predictable selection in the presence of uncertain 3D knowledge. These ideas are demonstrated in osgAR, an extension to OpenSceneGraph with explicit support for uncertainty in the 3D transformations. The osgAR runtime propagates this uncertainty throughout the scene graph to compute robust estimates of the probable location of all entities in the system from the user's viewpoint, in real-time. We discuss the implementation of selection in osgAR, and the issues that must be addressed when creating interaction techniques in such a system.