Pose estimation for objects with planar surfaces using eigenimage and range data analysis

In this paper we present a novel method for estimating the object pose for 3D objects with well-defined planar surfaces. Specifically, we investigate the feasibility of estimating the object pose using an approach that combines the standard eigenspace analysis technique with range data analysis. In this sense, eigenspace analysis was employed to constrain one object rotation and reject surfaces that are not compatible with a model object. The remaining two object rotations are estimated by computing the normal to the surface from the range data. The proposed pose estimation scheme has been successfully applied to scenes defined by polyhedral objects and experimental results are reported.