Institutional Repository of Leibniz Universität Hannover (Leibniz Universität Hannover) · 2010 · 173 citations · 18 references
ComputingEarth SciencesGeoinformaticsComputer VisionRemote SensingSensor FusionCalibrationObject Detection FusionPattern RecognitionPhotogrammetryDempster - Shafer TheoryDempster-shafer Evidence FusionDempster-shafer FusionDempster-shafer TheoryInstrument Performance CharacterizationObject-based VerificationRoad Feature DetectionRoad Surface Detection
This paper describes a semi-automatic system for road verification from high resolution orthophotos in an urban context. The system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model and thus a unique strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a function for confidence is introduced that reflects degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. Experimental results achieved with four different test sites in Japan demonstrate the potential and confirm the reliability of the new system.
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Yuhai Wu, Vladimir Vapnik · Technometrics · 1999 · 27K citations
THE CLOUDSAT MISSION AND THE A-TRAIN
Graeme L. Stephens, D. Vane, R. J. Boain et al. · Bulletin of the American Meteorological Society · 2002 · 2.2K citations · Full text
Toneo Kawanishi, Toshihiro Sezai, Yoshiyuki Ito et al. · IEEE Transactions on Geoscience and Remote Sensing · 2003 · 584 citations
David M. J. Tax · Research Repository (Delft University of Technology) · 2001 · 528 citations · Full text