Complete initial solutions for iterative pose estimation from planar objects

Zhou, K., Wang, X., Wang, Z., Wei, H. ORCID: https://orcid.org/0000-0002-9664-5748 and Yin, L. (2018) Complete initial solutions for iterative pose estimation from planar objects. IEEE Access, 6. pp. 22257-22266. ISSN 2169-3536 doi: 10.1109/ACCESS.2018.2827565

Abstract/Summary

Camera pose estimation from the image of a planar object has important applications in photogrammetry and computer vision. In this paper, an efficient approach to find the initial solutions for iterative camera pose estimation using coplanar points is proposed. Starting with homography, the proposed approach provides a least-squares solution for absolute orientation, which has a relatively high accuracy and can be easily refined into one optimal pose that locates local minima of the according error function by using Gauss-Newton scheme or Lu's orthogonal iteration algorithm. In response to ambiguities that exist in pose estimation from planar objects, we propose a novel method to find initial approximation of the second pose, which is different from existing methods in its concise form and clear geometric interpretation. Thorough testing on synthetic data shows that combined with currently employed iterative optimization algorithm, the two initial solutions proposed in this paper can achieve the same accuracy and robustness as the best state-of-the-art pose estimation algorithms, while with a significant decrease in computational cost. Real experiment is also employed to demonstrate its performance.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/80480
Identification Number/DOI	10.1109/ACCESS.2018.2827565
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Publisher	IEEE
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