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A Model‐Based Approach to Semi‐Automated Reconstruction of Buildings from Aerial Images
Author(s) -
Khoshelham Kourosh,
Li Zhilin
Publication year - 2004
Publication title -
the photogrammetric record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 51
eISSN - 1477-9730
pISSN - 0031-868X
DOI - 10.1111/j.0031-868x.2004.00290.x
Subject(s) - computer vision , aerial image , artificial intelligence , robustness (evolution) , computer science , parametric statistics , building model , image (mathematics) , computer graphics (images) , mathematics , simulation , biochemistry , chemistry , statistics , gene
Automated reconstruction of building objects from aerial images is a complex problem due to the diversity of buildings as well as noise and low contrast of images, which are the results of distant photography, atmospheric effects and poor illumination. In this paper, a semi‐automated approach to the reconstruction of parametric building models from aerial images is presented, which works with line segments extracted from the image. The model is selected interactively from a library of parametric models. A perceptual grouping technique is used to select the most significant image lines in terms of relations such as proximity and parallelism. Model lines are searched for the same relations as in the grouped image lines, and the corresponding lines undergo a matching procedure, which determines whether or not a match can be found between the given model and image lines. An experiment with aerial images of flat‐roof and gable‐roof buildings is shown and its results indicate the robustness and efficiency of the proposed approach.