Simultaneous Pose and Correspondence Determination Combining Softassign and Orthogonal Iteration

Pose estimation with unknown correspondences between 3D object points and 2D image points is known as the simultaneous pose and correspondence determination problem in the field of computer vision. It currently is still diffcutlt to solve particularly with the appearance of occlusion and cluster. In this paper, we present a new iterative algorithm for the pose estimation of an 3D object without any additional 3D-2D corresondence infromation. Our method combines SoftAssign algorithm for derterming the correspondence and OI (orthogonal iteration) algorithm for computing the pose. An assignment matrix which describes the correspondence is first introduced to the objective function of OI algorithm, and the simultaneous pose and correspondence determination problem is formulated as that of minimizing the weighted object space collinearity error. The pose and correspondence are evolved from an initial pose to an optimum value by nesting the two algorithms into one deterministic annealing process. Simulation and experimental results demonstrate that the proposed method is computationally more efficient and more accurate than the state-of-art methods.