Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-08-01
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| Series: | ISPRS Open Journal of Photogrammetry and Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667393222000084 |
| _version_ | 1797995744051855360 |
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| author | Joachim Gehrung Marcus Hebel Michael Arens Uwe Stilla |
| author_facet | Joachim Gehrung Marcus Hebel Michael Arens Uwe Stilla |
| author_sort | Joachim Gehrung |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T10:06:31Z |
| format | Article |
| id | doaj.art-a6201ce6d2a34cae94c99d35823f7fd2 |
| institution | Directory Open Access Journal |
| issn | 2667-3932 |
| language | English |
| last_indexed | 2024-04-11T10:06:31Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ISPRS Open Journal of Photogrammetry and Remote Sensing |
| spelling | doaj.art-a6201ce6d2a34cae94c99d35823f7fd22022-12-22T04:30:14ZengElsevierISPRS Open Journal of Photogrammetry and Remote Sensing2667-39322022-08-015100019Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approachJoachim Gehrung0Marcus Hebel1Michael Arens2Uwe Stilla3Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275, Ettlingen, Germany; Photogrammetry and Remote Sensing, TUM School of Engineering and Design, Technical University of Munich, 80333, Muenchen, Germany; Corresponding author. Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275, Ettlingen, Germany.Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275, Ettlingen, GermanyFraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275, Ettlingen, GermanyPhotogrammetry and Remote Sensing, TUM School of Engineering and Design, Technical University of Munich, 80333, Muenchen, GermanyAutomated 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.http://www.sciencedirect.com/science/article/pii/S2667393222000084Change detectionSpatial information representationEvidence gridsFuzzy logic |
| spellingShingle | Joachim Gehrung Marcus Hebel Michael Arens Uwe Stilla Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach ISPRS Open Journal of Photogrammetry and Remote Sensing Change detection Spatial information representation Evidence grids Fuzzy logic |
| title | Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach |
| title_full | Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach |
| title_fullStr | Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach |
| title_full_unstemmed | Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach |
| title_short | Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach |
| title_sort | change detection in street environments based on mobile laser scanning a fuzzy spatial reasoning approach |
| topic | Change detection Spatial information representation Evidence grids Fuzzy logic |
| url | http://www.sciencedirect.com/science/article/pii/S2667393222000084 |
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