Curvature Regularization for Point Cloud Reconstruction and Denoising.

This paper introduces a novel approach for reconstructing and denoising 3D point clouds using curvature regularization based on differential geometry principles. By incorporating geometric information, the proposed method effectively handles noise and outliers while preserving fine-scale features and overall shape integrity. This work has practical applications in 3D scanning, reverse engineering, virtual reality, and computer vision, enabling more accurate and robust processing of raw 3D sensor data for various industrial and scientific purposes.