Efficient Iterative Pose Estimation using an Invariant to Rotations

Omar Tahri (1) , Helder Araujo (2) , Youcef Mezouar (3) , François Chaumette (4)

1 ISR-UC - Institute of Systems and Robotics
2 ISR - Institute for System and Robotics [Lisbonne]
3 IFMA - Institut Français de Mécanique Avancée
4 Lagadic - Visual servoing in robotics, computer vision, and augmented reality

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.

Domaines: Robotique [cs.RO]

Omar Tahri, Helder Araujo, Youcef Mezouar, François Chaumette. Efficient Iterative Pose Estimation using an Invariant to Rotations. IEEE Transactions on Cybernetics, 2014, 22 (4), pp.199-207. ⟨10.1109/TCYB.2013.2251331⟩. ⟨hal-00840264⟩