Surface Parameterization

Surface parameterization focuses on representing 3D surfaces using 2D parameters, enabling efficient manipulation and analysis of complex geometries. Current research emphasizes developing neural network architectures, such as PointNets and implicit surface representations, to achieve robust and efficient parameterization, particularly for unstructured point cloud data and irregular geometries. These advancements are crucial for diverse applications, including computer graphics, optical design, and even industrial processes like quality control in the wood industry, by facilitating tasks like texture mapping, surface optimization, and accurate 3D reconstruction from limited data.