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Fast extraction of dominant planes in MLS-data of urban areas

: Gordon, Marvin

Fulltext urn:nbn:de:0011-n-4263647 (4.9 MByte PDF)
MD5 Fingerprint: 15e6842b10b3f64704cae760ccf7bc6d
Created on: 21.12.2016

Michaelsen, E. ; International Association for Pattern Recognition -IAPR-; Institute of Electrical and Electronics Engineers -IEEE-:
9th IAPR Workshop on Pattern Recognition in Remote Sensing, PRRS 2016 : 4 December 2016, Cancun
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-5041-3
ISBN: 978-1-5090-5042-0
5 pp.
Workshop on Pattern Recognition in Remote Sensing (PRRS) <9, 2016, Cancun>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
RANSAC; plane estimation; MLS; LIDAR

Many current LIDAR systems generate huge amounts of 3D points, therefore efficient and fast data processing is essential. In urban areas surfaces are often planar and plane patches are an efficient representation for localization purposes. Our approach thus stores the points in a voxel grid and afterwards extracts the dominant plane using RANSAC-based plane fitting. Classical RANSAC-based plane extraction can result in improper planes, especially in the case of steps like curbsides. Different solutions have been presented, but they are computational demanding. We tackle this problem by extending the loss function of the standard RANSAC. This solves the problem in most cases and has nearly no impact on the runtime. We show the improvement using data of an urban environment, which were recorded by an MLS-system.