  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.

Computer Vision and Pattern Recognition