University of California San Francisco
3D modeling of building architecture from point-cloud scans is a rapidly advancing field. These models are used in augmented reality, navigation, and energy simulation applications. State-of-the-art scanning produces accurate point-clouds of building interiors containing hundreds of millions of points. Current surface reconstruction techniques either do not preserve sharp features common in a man-made structures, do not guarantee watertightness, or are not constructed in a scalable manner. This paper presents an approach that generates watertight triangulated surfaces from input point-clouds, preserving the sharp features common in buildings.