Abstract
Abstract. Geometrically and topologically correct 3D building models are required to satisfy with new demands such as 3D cadastre, map updating, and decision making. More attention on building reconstruction has been paid using Airborne Laser Scanning (ALS) point cloud data. The planimetric accuracy of roof outlines, including step-edges is questionable in building models derived from only point clouds. This paper presents a new approach for the detection of accurate building boundaries by merging point clouds acquired by ALS and aerial photographs. It comprises two major parts: reconstruction of initial roof models from point clouds only, and refinement of their boundaries. A shortest closed circle (graph) analysis method is employed to generate building models in the first step. Having the advantages of high reliability, this method provides reconstruction without prior knowledge of primitive building types even when complex height jumps and various types of building roof are available. The accurate position of boundaries of the initial models is determined by the integration of the edges extracted from aerial photographs. In this process, scene constraints defined based on the initial roof models are introduced as the initial roof models are representing explicit unambiguous geometries about the scene. Experiments were conducted using the ISPRS benchmark test data. Based on test results, we show that the proposed approach can reconstruct 3D building models with higher geometrical (planimetry and vertical) and topological accuracy.
Highlights
With the development of sensor technology, Airborne Laser Scanning (ALS) demonstrates the high potential for the acquisition of accurate three dimensional dense point clouds in a rapid manner
The goal of this paper is to present a new method for enhancing, mainly, the planimetric accuracy of roof models reconstructed from point clouds
The performance of the method is analysed in the context of the ISPRS WG III/4 “Test Project on Urban Classification and 3D Building Reconstruction”, which allows us to use external reference data
Summary
With the development of sensor technology, Airborne Laser Scanning (ALS) demonstrates the high potential for the acquisition of accurate three dimensional dense point clouds in a rapid manner. In order to enhance the accuracy of building models, refinement processes have been applied in some reconstruction schemes. Due to the difficulty of enhancing accuracy of models by point clouds itself, most practices which deal with refinement have used external data sources. In this regard, image data is shown as the most prominent source because it has complementary properties than ALS point clouds. Image data is shown as the most prominent source because it has complementary properties than ALS point clouds Integration of these two data sources enhances the quality of building models in many ways, for instance LoD, segmentation, planimetric and as well as topological accuracy. Once data is properly integrated, image information can be used to increase the accuracy of roof point segmentation. Khoshelham (2005) use a single image for refining segmentation of point clouds. Rottensteiner (2010) illustrate that the segmentation can further be enhanced by integrating multiple images and it solves contrast issues of individual images
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