Nonrigid iterative closest points for registration of 3D biomedical surfaces

Luming LIANG, Mingqiang WEI*, Andrzej SZYMCZAK, Anthony PETRELLA, Haoran XIE, Jing QIN, Jun WANG, Fu Lee WANG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

31 Citations (Scopus)


Advanced 3D optical and laser scanners bring new challenges to computer graphics. We present a novel nonrigid surface registration algorithm based on Iterative Closest Point (ICP) method with multiple correspondences. Our method, called the Nonrigid Iterative Closest Points (NICPs), can be applied to surfaces of arbitrary topology. It does not impose any restrictions on the deformation, e.g. rigidity or articulation. Finally, it does not require parametrization of input meshes. Our method is based on an objective function that combines distance and regularization terms. Unlike the standard ICP, the distance term is determined based on multiple two-way correspondences rather than single one-way correspondences between surfaces. A Laplacian-based regularization term is proposed to take full advantage of multiple two-way correspondences. This term regularizes the surface movement by enforcing vertices to move coherently with their 1-ring neighbors. The proposed method achieves good performances when no global pose differences or significant amount of bending exists in the models, for example, families of similar shapes, like human femur and vertebrae models.

Original languageEnglish
Pages (from-to)141-154
Number of pages14
JournalOptics and Lasers in Engineering
Early online date10 Aug 2017
Publication statusPublished - Jan 2018
Externally publishedYes


  • Bone
  • Multiple two-way correspondences
  • Nonrigid iterative closest points (NICPs)
  • Surface registration


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