Björn Lunt

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We propose a data driven approach to detect zebra crossings in aerial imagery. The system automatically learns an appearance model from available geospatial data for an examined region. HOG as well as LBPH features, in combination with a SVM, yield state of the art detection results on different datasets. We also use this classifier across datasets obtained(More)
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