[POSTER] Rubix: Dynamic spatial augmented reality by extraction of plane regions with a RGB-D camera

Dynamic spatial augmented reality requires accurate real-time 3D pose information of the physical objects that are to be projected onto. Previous depth-based methods for tracking objects required strong features to enable recognition; making it difficult to estimate an accurate 6DOF pose for physical objects with a small set of recognizable features (such as a non-textured cube). We propose a more accurate method with fewer limitations for the pose estimation of a tangible object that has known planar faces and using depth data from an RGB-D camera only. In this paper, the physical object's shape is limited to cubes of different sizes. We apply this new tracking method to achieve dynamic projections onto these cubes. In our method, 3D points from an RGB-D camera are divided into a cluster of planar regions, and the point cloud inside each face of the object is fitted to an already-known geometric model of a cube. With the 6DOF pose of the physical object, SAR generated imagery is then projected correctly onto the physical object. The 6DOF tracking is designed to support tangible interactions with the physical object. We implemented example interactive applications with one or multiple cubes to show the capability of our method.