Efficient Iterative Pose Estimation Using an Invariant to Rotations

Abstract

This paper deals with pose estimation using an iterative scheme. We show that using adequate visual information, pose estimation can be performed iteratively with only three independent unknowns, which are the translation parameters. Specifically, an invariant to rotational motion is used to estimate the camera position. In addition, an adequate transformation is applied to the proposed invariant to decrease the nonlinearities between the variations in image space and 3-D space. Once the camera position is estimated, we show that the rotation can be estimated efficiently using two different direct methods. The proposed approach is compared against two other methods from the literature. The results show that using our method, pose tracking in image sequences and the convergence rate for randomly generated poses are improved.