A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

By P. Dorninger, Norbert Pfeifer. Italian National Conference on Sensors, 2008

360 citations recorded by the source corpus.

Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects.

Subfields: Ecology, Environmental Engineering, Geology

View Paper: https://www.semanticscholar.org/paper/d85f83f2139ea4abc69330d8c5486981c0690463

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Citations in the corpus

The ISPRS benchmark on urban object classification and 3D building reconstruction (2012, methodology): “Finally, the borders of the regions are delineated, which results in polygonal building outlines (Dorninger & Pfeifer, 2008).”
Shape-based recognition of 3D point clouds in urban environments (2009, background): “, buildings [2, 9] and trees [28, 30]), for extracting geometric primitives (e.”
An update on automatic 3D building reconstruction (2010, neutral): “Dorninger and Pfeifer (2008) first simplify the boundaries using an angular criterion and then regularize them to enforce orthogonal or parallelism.”
Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning (2011, background): “Range sensors are nowadays employed for large area topographic mapping, DSM/DTM generation (Figure 1), heritage documentation (Figure 2), modeling fluvial environments and geological structures [39], studies on biomass and vegetation information [40-42], archaeological applications [43], landslide a”