Lee, YunjinLee, SeungyongIvrissimtzis, IoannisSeidel, Hans-PeterAlla Sheffer and Konrad Polthier2014-01-292014-01-2920063-905673-24-X1727-8384https://doi.org/10.2312/SGP/SGP06/231-234This paper proposes a general framework for overfitting control in surface reconstruction from noisy point data. The problem we deal with is how to create a model that will capture as much detail as possible and simultaneously avoid reproducing the noise of the input points. The proposed framework is based on extra-sample validation. It is fully automatic and can work in conjunction with any surface reconstruction algorithm. We test the framework with a Radial Basis Function algorithm, Multi-level Partition of Unity implicits, and the Power Crust algorithm.Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; I.6.5 [Simulation and modeling]: Model Development