Corner-Based 3D Object Pose Estimation in Robot Vision
Conventional edge-based object pose estimation in robot vision shows low accuracy and slow convergence performance. In this paper, a corner-based object pose estimation method is proposed and studied. The classical pinhole camera model and model-based object pose estimation or tracking are employ, as well as the iterative optimization for accurate estimation. In our method, a new corner matching strategy is proposed since good corresponding is easy to be met for image corners. Then, good fitting results between the CAD model and object in the images can be obtained. Experimental results show that the new method can achieve more accurate and faster pose estimation than the conventional methods.