建筑检测和数字表面模型提取算法的性能评估:PRRS 2008算法性能竞赛结果

S. Aksoy, B. Ozdemir, S. Eckert, F. Kayitakire, M. Pesarasi, O. Aytekin, C. Borel, J. Čech, E. Christophe, S. Duzgun, A. Erener, K. Ertugay, Elima Hussain, J. Inglada, S. Lefèvre, O. Ok, D. K. San, R. Sára, J. Shan, J. Soman, I. Ulusoy, R. Witz
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引用次数: 17

摘要

本文介绍了算法性能竞赛的初步结果,该竞赛是第五届IAPR遥感模式识别研讨会(PRRS 2008)的一部分。2008年竞赛的重点是自动建筑检测和数字表面模型(DSM)提取。建筑物检测评价采用人工地真值的QuickBird数据集,DSM提取评价采用高精度参考DSM的立体Ikonos数据集。我们收到了九份建筑探测任务的建议书,三份DSM提取任务的建议书。我们提供了数据集的概述,用于提交的方法的摘要,评估标准的细节,以及初步评估的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance evaluation of building detection and digital surface model extraction algorithms: Outcomes of the PRRS 2008 Algorithm Performance Contest
This paper presents the initial results of the algorithm performance contest that was organized as part of the 5th IAPR Workshop 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.
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