Variational Surface Reconstruction Using Natural Neighbors

Surface reconstruction from points is a fundamental problem in computer graphics. While numerous methods have been proposed, it remains challenging to reconstruct from sparse and non-uniform point distributions, particularly when normals are absent. We present a robust and scalable method for reconstructing an implicit surface from points without normals. By exploring the locality of natural neighborhoods, we propose local reformulations of a previous global method, known for its ability to surface sparse points but high computational cost, thereby significantly improving its scalability while retaining its robustness. Experiments show that our method achieves comparable speed to existing reconstruction methods on large inputs while producing fewer artifacts in under-sampled regions.