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2022
Journal Article
Titel

Change detection in street environments based on mobile laser scanning

Titel Supplements
A fuzzy spatial reasoning approach
Abstract
Automated change detection based on urban mobile laser scanning data is the foundation for a whole range of applications such as building model updates, map generation for autonomous driving and natural disaster assessment. The challenge with mobile LiDAR data is that various sources of error, such as localization errors, lead to uncertainties and contradictions in the derived information. This paper presents an approach to automatic change detection using a new category of generic evidence grids that addresses the above problems. Said technique, referred to as fuzzy spatial reasoning, solves common problems of state-of-the-art evidence grids and also provides a method of inference utilizing fuzzy Boolean reasoning. Based on this, logical operations are used to determine changes and combine them with semantic information. A quantitative evaluation based on a hand-annotated version of the TUM-MLS data set shows that the proposed method is able to identify confirmed and changed elements of the environment with F1-scores of 0.93 and 0.89.
Author(s)
Gehrung, Joachim
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Hebel, Marcus
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Arens, Michael
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Stilla, Uwe
Zeitschrift
ISPRS open journal of photogrammetry and remote sensing
DOI
10.1016/j.ophoto.2022.100019
File(s)
Gehrung_Hebel_Arens_Stilla_ISPRS-Open-Journal-2022.pdf (17.71 MB)
Language
English
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Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Tags
  • Open Access

  • Spatial information r...

  • Fuzzy logic

  • Evidence grids

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