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2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map
National University of Defense Technology, Changsa, P. R. China. (ATR Laboratory)ORCID iD: 0000-0002-9990-9163
National University of Defense Technology, Changsa, P. R. China. (ATR Laboratory)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-9503-0602
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0001-8658-2985
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2018 (English)In: Proceedings of 21st International Conference on Information Fusion (FUSION), 2018, p. 2400-2406Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a novel sub-pixel motion extraction method, called as Two Dimensional Spatial Keystone Transform (2DS-KST), for the motion detection and estimation from successive noisy Occupancy Grid Maps (OGMs). It extends the KST in radar imaging or motion compensation to 2D real spatial case, based on multiple hypotheses about possible directions of moving obstacles. Simulation results show that 2DS-KST has a good performance on the extraction of sub-pixel motions in very noisy environment, especially for those slowly moving obstacles.

Place, publisher, year, edition, pages
2018. p. 2400-2406
Keywords [en]
robotics, occupancy grid map, motion extraction, keystone transform, 2DS-KST, sub-pixel
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-71953DOI: 10.23919/ICIF.2018.8455274ISI: 000495071900329Scopus ID: 2-s2.0-85054090397ISBN: 978-0-9964527-6-2 (electronic)ISBN: 978-1-5386-4330-3 (print)OAI: oai:DiVA.org:oru-71953DiVA, id: diva2:1284105
Conference
21st International Conference on Information Fusion (FUSION), Cambridge, UK, July 10 - 13, 2018
Available from: 2019-01-30 Created: 2019-01-30 Last updated: 2019-12-03Bibliographically approved

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2D spatial keystone transform for sub-pixel motion extraction from noisy occupancy grid map(605 kB)638 downloads
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Kucner, Tomasz PiotrMagnusson, MartinLilienthal, Achim

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Fan, HongqiKucner, Tomasz PiotrMagnusson, MartinLilienthal, Achim
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