Semiautomated Building Extraction Based on CSG Model-Image Fitting

Abstract

mostly implemented in a semi-automatic manner, solving the Building extraction based on pre-established models has been model-image fitting problem based on some high-level inforrecognized as a promising idea for acquiring 3D data for build- mation given by the operator. The spatial data of a building ings from aerial images. This paper proposes a novel building object are determined, when model-image fitting is achieved. extraction method developed from the concept of fitting CSG In contrast to the traditional point-by-point mapping proce(Constructive Solid Geometry) primitives to aerial images. To dure, model-based building extraction features object-based be practicable, this method adopts a semiautomatic proce- data acquisition. Although the idea and benefits of modeldure, carrying out high-level tasks (building detection, model based building extraction have been acknowledged, the workselection, and attribution) interactively by the operator and ing principle is not well established. Therefore, the focus of performing optimal model-image fitting automatically with a this study is to establish a practical theory for model-based least-squares fitting algorithm. Buildings, represented by CSG building extraction. models, can be reconstructed part by part after fitting each Building modeling and model-image fitting are the key parameterized CSG primitive to the edge pixels of aerial issues in model-based building extraction. The issue on buildimages. Reconstructed building parts can then be combined ing modeling is how to establish a set of representative and using CSG Boolean set operators. Consequently, a building is complete building models. This paper reviews some building represented by a CSG tree in which each node links two model schemes known in the field of digital photogrammetry branches of combined parts. This paper demonstrates ten and discusses how CSG modeling is employed in the proposed examples of building extraction from aerial photos taken at a method. The issue in model-image fitting is how to develop a scale of 1:5,000 and scanned at a pixel size of 25 m. All of computer algorithm that is able to determine the pose and the tests were performed in the prototypal system implemented shape parameters of an object model such that the edge lines of in a CAD-based environment cooperated with a number of the wire frame, as projected into the images, are optimally specially designed programs. The process time for each prim- coincident with the corresponding edge pixels. It is assumed itive is about 20 seconds and the successful rate of model- that the image orientations are known and that the pose and image fitting was about 90 percent. Evaluated with some check shape parameters are approximately determined through an points, the fitting accuracy was about 0.3 m horizontally and interactive manual process. To deal with this problem, this 1m vertically. The test results are encouraging and promote paper proposes a tailored least-squares model-image fitting the theory of model-based building extraction. algorithm as the key component of the building extraction framework.