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Change Detection and Deformation Analysis based on Mobile Laser Scanning Data of Urban Areas

 
: Gehrung, Joachim; Hebel, Marcus; Arens, Michael; Stilla, Uwe

:
Fulltext urn:nbn:de:0011-n-5994002 (5.4 MByte PDF)
MD5 Fingerprint: 532f35b71fccf69f5cbba31888b6f2ee
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Created on: 12.8.2020


Paparoditis, N. ; International Society for Photogrammetry and Remote Sensing -ISPRS-:
XXIV ISPRS Congress 2020. Commission II : 31 Aug - 2 Sep, on-line, Nice, France
Istanbul: ISPRS, 2020 (ISPRS Annals V-2-2020)
pp.703–710
International Society for Photogrammetry and Remote Sensing (ISPRS Congress) <24, 2020, Online>
English
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
Mobile laser scanning; Change Detection; Occupancy Grid

Abstract
Change detection is an important tool for processing multiple epochs of mobile LiDAR data in an efficient manner, since it allows to cope with an otherwise time-consuming operation by focusing on regions of interest. State-of-the-art approaches usually either do not handle the case of incomplete observations or are computationally expensive. We present a novel method based on a combination of point clouds and voxels that is able to handle said case, thereby being computationally less expensive than comparable approaches. Furthermore, our method is able to identify special classes of changes such as partially moved, fully moved and deformed objects in addition to the appeared and disappeared objects recognized by conventional approaches. The performance of our method is evaluated using the publicly available TUM City Campus datasets, showing an overall accuracy of 88 %.

: http://publica.fraunhofer.de/documents/N-599400.html