Extended gravitational pose estimation

The model-to-image registration problem is a problem of determining the position and orientation (the pose) of a three-dimensional object with respect to a camera coordinate system. When there is no additional information available to constrain the pose of the object and to constrain the correspondence of object features to image features, the problem is also known as simultaneous pose and correspondence problem, or correspondenceless pose estimation problem. In this paper, we present a new algorithm, called extended gravitational pose estimation (EGPE), for determining the pose and correspondence simultaneously. The algorithm is based on gravitational pose estimation (GPE) algorithm. In our algorithm, the original GPE has been revised to deal with the problem with false image points. For problems with both occluded object points and false image points, we firstly applied single-link agglomerative clustering algorithm to pick out occluded object points when a local minimum has been found, then the revised GPE is applied again on the clustering result to update rotation and translation of the object model. EGPE has been verified on both synthetic images and real images. Empirical results show that EGPE is faster, more stable and reliable than most current algorithms, and can be used in real applications.