3D non-rigid point cloud based surface registration based on mean shift

In this article, we present a new 3D non-rigid surface registration algorithm for unstructured point clouds. The algorithm has very low data requirements and can easily be adapted to use additional information other than vertex positions such as texture information or prior knowledge about local deformations. It is robust to noise, outliers and to some extent to missing data. The mathematical theory is based on probability density estimation. Furthermore, we use the mean shift formula for fast computation. The algorithm is able to use different regularisation models for the deformation. Quantitative and qualitative experiments are conducted on artificial surfaces and on real 3D face data.