Browsing by Author "Eckert, S."
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Item Open Access Performance evaluation of building detection and digital surface model extraction algorithms: Outcomes of the PRRS 2008 algorithm performance contest(IEEE, 2008-12) Aksoy, Selim; Özdemir, Bahadır; Eckert, S.; Kayitakire, F.; Pesarasi, M.; Aytekin, O.; Borel, C. C.; Cech, J.; Christophe, E.; Düzgün, S.; Erener, A.; Ertugay, K.; Hussain, E.; Inglada, J.; Lefévrë, S.; Ok, Ö.; San, D. K.; Šára, R.; Shan, J.; Soman, J.; Ulusoy, I.; Witz, R.This paper presents the initial results of the Algorithm Performance Contest that was organized as part of the 5th IAPRWorkshop on Pattern Recognition in Remote Sensing (PRRS 2008). The focus of the 2008 contest was automatic building detection and digital surface model (DSM) extraction. A QuickBird data set with manual ground truth was used for building detection evaluation, and a stereo Ikonos data set with a highly accurate reference DSM was used for DSM extraction evaluation. Nine submissions were received for the building detection task, and three submissions were received for the DSM extraction task. We provide an overview of the data sets, the summaries of the methods used for the submissions, the details of the evaluation criteria, and the results of the initial evaluation. © 2008 IEEE.Item Open Access Performance measures for object detection evaluation(Elsevier BV, 2010) Özdemir, B.; Aksoy, S.; Eckert, S.; Pesaresi, M.; Ehrlich, D.We propose a new procedure for quantitative evaluation of object detection algorithms. The procedure consists of a matching stage for finding correspondences between reference and output objects, an accuracy score that is sensitive to object shapes as well as boundary and fragmentation errors, and a ranking step for final ordering of the algorithms using multiple performance indicators. The procedure is illustrated on a building detection task where the resulting rankings are consistent with the visual inspection of the detection maps. © 2009 Elsevier B.V. All rights reserved.