New Techniques for Automated Architectural Reconstruction from Photographs
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Improved Rooftop Detection in Aerial Images with Machine Learning
Machine Learning
Generalized use of homographies for piecewise planar reconstruction
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
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A method for detection and description of rectangular buildings from two or more registered aerial intensity images is proposed. The output is a 3D description of the buildings, with an associated confidence measure for each building. Hierarchical perceptual grouping and matching across views is employed to increase the robustness of the system. Verification of selected building hypotheses is done using shadow and wall evidence of the buildings. The system is largely feature-based. Grouping and matching are performed in a hierarchical manner, utilizing primitives of increasing complexity, starting with line segments and junctions, and proceeding to higher level features. Binocular and trinocular epipolar constraints are used to reduce the search space for matching features.