Accurate shape-based 6-DoF pose estimation of single-colored objects

The problem of accurate 6-DoF pose estimation of 3D objects based on their shape has so far been solved only for specific object geometries. Edge-based recognition and tracking methods rely on the extraction of straight line segments or other primitives. Straight-forward extensions of 2D approaches are potentially more general, but assume a limited range of possible view angles. The general problem is that a 3D object can potentially produce completely different 2D projections depending on the view angle. One way to tackle this problem is to use canonical views. However, accurate shape-based 6-DoF pose estimation requires more information than matching of canonical views can provide. In this paper, we present a novel approach to 6-DoF pose estimation of single-colored objects based on their shape. Our approach combines stereo triangulation with matching against a high-resolution view set of the object, each view having associated orientation information. The errors that arise from separating the position and orientation computation in first place are corrected by a subsequent correction procedure based on online 3D model projection. The proposed approach can estimate the pose of a single object within 20 ms using conventional hardware.