English

Global Consistent Point Cloud Registration Based on Lie-algebraic Cohomology

Computer Vision and Pattern Recognition 2022-08-16 v1

Abstract

We present a novel, effective method for global point cloud registration problems by geometric topology. Based on many point cloud pairwise registration methods (e.g ICP), we focus on the problem of accumulated error for the composition of transformations along any loops. The major technical contribution of this paper is a linear method for the elimination of errors, using only solving a Poisson equation. We demonstrate the consistency of our method from Hodge-Helmhotz decomposition theorem and experiments on multiple RGBD datasets of real-world scenes. The experimental results also demonstrate that our global registration method runs quickly and provides accurate reconstructions.

Keywords

Cite

@article{arxiv.2208.07103,
  title  = {Global Consistent Point Cloud Registration Based on Lie-algebraic Cohomology},
  author = {Yuxue Ren and Baowei Jiang and Wei Chen and Na Lei and Xianfeng David Gu},
  journal= {arXiv preprint arXiv:2208.07103},
  year   = {2022}
}

Comments

14 pages,6 figures

R2 v1 2026-06-25T01:42:35.966Z