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A Probabilistic Feature Fusion for Building Detection in Satellite Images
2015
Proceedings of the 10th International Conference on Computer Vision Theory and Applications
Building segmentation from 2D images can be a very challenging task due to the variety of objects that appear in an urban environment. Many algorithms that attempt to automatically extract buildings from satellite images face serious problems and limitations. In this paper, we address some of these problems by applying a novel approach that is based on the fusion of Histogram of Oriented Gradients (HOG), Normalized Difference Vegetation Index (NDVI) and Features from Accelerated Segment Test
doi:10.5220/0005260502050212
dblp:conf/visapp/KonstantinidisS15
fatcat:qclixfvnfvehpivgl4ywuyn2di