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2017.IX.
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2017.VII.
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2017.VI.
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2017.IV.
III. Prize in the Hlavay competition for a member of the MY-X team!

2017.III.
NTP-NFTÖ financial support for a member of the MY-X team!

2017.II.
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Last modified: 2015.VII.19.14:08 - MIAÚ-RSS
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Object recognition and change detection of buildings based on airborne LiDAR

Leading article: 2019. August (MIAU No. 252.)
(Previous article: MIAU No. 251.)

Keywords: LiDAR, building recognition, change detection

Abstract: Nowadays, using modern LiDAR (Light Detection And Ranging) devices, it is possible to cost-efficiently scan larger areas with high resolution even at regular intervals, which provides an alternative data source for automated analyses about the surface and its changes. The results can be directly applied in various fields, e.g. in case of land use inspections, urban planning, civil engineering, monitoring of environmental disasters (extent of flood and waterlogging, earthquake damages), afforestation and maintaining GIS databases. However, the data volume acquired from the laser scans requires efficient processing or even the support of distributed computations. In this study, I present a contour-based method for building recognition. It provides favorable computer resource (memory and storage space) requirement compared to other studies, with reasonable execution time due to the utilization of local features. When comparing epochs of multitemporal datasets to detect changes in the buildings of the scene, a novel approach based on possible contour pairings has been worked out with a limited capability to reconstruct lack or loss of information from the previous steps. To demonstrate and validate the results, the public Dutch altimetry archive (AHN), a multitemporal point cloud covering the entire Netherlands and the governmental TOP10NL building records were used. More (DOC) *** More (PDF)


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