Artificial Intelligence - Special volume on computer vision
Automatic object extraction from aerial imagery—a survey focusing on buildings
Computer Vision and Image Understanding
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Recognition and reconstruction of buildings from multiple aerial images
Computer Vision and Image Understanding
Improved Rooftop Detection in Aerial Images with Machine Learning
Machine Learning
An Efficient Solution to the Five-Point Relative Pose Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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This paper presents a new procedure for rooftop detection and 3D building modeling from aerial images. After an over-segmentation of the aerial image, the rooftop regions are coarsely detected by employing multi-scale SIFT-like features and visual object recognition. In order to refine the detected result and remove the non-rooftop regions, we further resort to explore the 3D information of the rooftop by 3D reconstruction. Wherein, we employ a hierarchical strategy to obtain the corner correspondence between images based on an asymmetry correlation corner matching. We determine whether a candidate region is a rooftop or not according to its height information relative to the ground plane. Finally, the 3D building model with texture mapping based on one of the images is given. Experimental results are shown on real aerial scenes.