The ISPRS benchmark on urban object classification and 3d building reconstruction

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dc.identifier.uri http://dx.doi.org/10.15488/5042
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/5086
dc.contributor.author Rottensteiner, Franz
dc.contributor.author Sohn, Gunho
dc.contributor.author Jung, Jaewook
dc.contributor.author Gerke, Markus
dc.contributor.author Baillard, Caroline
dc.contributor.author Benitez, Sebastien
dc.contributor.author Breitkopf, Uwe
dc.date.accessioned 2019-06-27T07:47:38Z
dc.date.available 2019-06-27T07:47:38Z
dc.date.issued 2012
dc.identifier.citation Rottensteiner, Franz; Sohn, Gunho; Jung, Jaewook; Gerke, Markus; Baillard, Caroline et al.: The ISPRS benchmark on urban object classification and 3d building reconstruction. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences I-3 (2012), Nr. 1, S. 293-298. DOI: https://doi.org/10.5194/isprsannals-i-3-293-2012
dc.description.abstract For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of airborne image and laserscanner data, has been made available to the scientific community. Researchers were encouraged to submit results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current airborne sensor data, but also common problems of state-of-the-art methods. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartof XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia
dc.relation.ispartofseries ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences I-3 (2012), Nr. 1
dc.rights CC BY 3.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Data mining eng
dc.subject Artificial intelligence eng
dc.subject Object detection eng
dc.subject Reference data (financial markets) eng
dc.subject Computer vision eng
dc.subject Computer science eng
dc.subject Data set eng
dc.subject Remote sensing eng
dc.subject Benchmarking eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title The ISPRS benchmark on urban object classification and 3d building reconstruction eng
dc.type article
dc.type conferenceObject
dc.type Text
dc.relation.issn 2194-9050
dc.relation.doi https://doi.org/10.5194/isprsannals-i-3-293-2012
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume I-3
dc.bibliographicCitation.firstPage 293
dc.bibliographicCitation.lastPage 298
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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