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dc.contributor.authorDíaz Vilariño, L.
dc.contributor.authorKhoshelham, K.
dc.date.accessioned2020-02-18T02:26:24Z-
dc.date.available2020-02-18T02:26:24Z-
dc.date.issued2017
dc.identifier.citationAnnals of the Photogrammetry, Remote Sensing and Spatial Information SciencesVolume XLII-2/W7, 2017, pp 367-372
dc.identifier.urihttp://tailieuso.tlu.edu.vn/handle/DHTL/4649-
dc.description.abstractAutomated generation of 3D indoor models from point cloud data has been a topic of intensive research in recent years. While results on various datasets have been reported in literature, a comparison of the performance of different methods has not been possible due to the lack of benchmark datasets and a common evaluation framework. The ISPRS benchmark on indoor modelling aims to address this issue by providing a public benchmark dataset and an evaluation framework for performance comparison of indoor modelling methods. In this paper, we present the benchmark dataset comprising several point clouds of indoor environments captured by different sensors. We also discuss the evaluation and comparison of indoor modelling methods based on manually created reference models and appropriate quality evaluation criteria. The benchmark dataset is available for download at: http://www2.isprs.org/commissions/comm4/wg5/benchmark-on-indoor-modelling.html.
dc.description.urihttps://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/367/2017/isprs-archives-XLII-2-W7-367-2017.pdf
dc.languageeng
dc.subject3D Model
dc.subjectGeometric reconstruction
dc.subjectIndoor navigation
dc.subjectBIM
dc.subjectPoint cloud
dc.subject3D modelling
dc.titleExploiting indoor mobile laser scanner trajectories for semantic interpretation of point clouds
dc.typeBB
dc.date.update20190828114112.0
dc.date.submitte130605s2017
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