Global Consistent Point Cloud Registration Based on Lie-algebraic Cohomology
This addresses the issue of error accumulation in point cloud registration for 3D reconstruction applications, though it appears incremental as it builds on existing pairwise methods like ICP.
The paper tackles the problem of accumulated error in global point cloud registration by proposing a linear method based on Lie-algebraic cohomology and Hodge-Helmholtz decomposition, which runs quickly and provides accurate reconstructions on RGBD datasets.
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.