Surface Sampling

Surface sampling focuses on efficiently acquiring data from the surfaces of objects or regions of interest, aiming to optimize data collection for tasks like 3D reconstruction, level set estimation, and image synthesis. Current research emphasizes intelligent sampling strategies, leveraging techniques like active learning, near-surface sampling guided by depth information or point clouds, and hybrid voxel-surface approaches to reduce computational cost and improve accuracy. These advancements are improving the efficiency and quality of 3D modeling, image rendering, and other applications requiring accurate surface representations, particularly in challenging scenarios like those involving complex geometries or limited data.