Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A simple and robust line detection algorithm based on small eigenvalue analysis
Pattern Recognition Letters
EURASIP Journal on Applied Signal Processing
A novel approach for polygonal rooftop detection in satellite/aerial imageries
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic Building Detection in Aerial Images Using a Hierarchical Feature Based Image Segmentation
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Building Detection in a Single Remotely Sensed Image with a Point Process of Rectangles
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
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This paper describes an improved version of our system for robust detection of buildings with a gable roof in varying rural areas from very-high-resolution aerial images. The algorithm follows a custom-made design, extracting key features close to modeling, such as roof ridges and gutters, in order to allow a large freedom in roof appearances. It starts by detecting straight line-segments as roof-ridge hypotheses, and for each of them, the likely roof-gutter positions are estimated. Supervised classification is employed to select the optimal gutter pair and to reject unlikely detections. Afterwards, overlapping detections are merged. Experiments on a large dataset containing 220 images, covering different rural regions with significant variation in both building appearance and surroundings, show that the system is able to detect over 87% of the present buildings, thereby handling common distortions, such as occlusions by trees.