Featureless 6 DOF pose refinement from stereo images

We present a pose estimation method from an initial unreliable guess using calibrated stereo images. The approach does not rely on a priori known salient features on the surface. The stereo images are brought in congruence without computing a disparity map like in standard stereo algorithms. Instead, the pose parameters of the object are varied to match the stereo images on the known surface shape. Our approach takes into account the aliasing effects introduced due to irregular sub-sampling and is not limited to simple geometric surfaces.