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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 motionextraction method, called as Two Dimensional Spatial KeystoneTransform (2DS-KST), for the motion detection and estimationfrom successive noisy Occupancy Grid Maps (OGMs). It extendsthe KST in radar imaging or motion compensation to 2Dreal spatial case, based on multiple hypotheses about possibledirections of moving obstacles. Simulation results show that 2DSKSThas a good performance on the extraction of sub-pixelmotions in very noisy environment, especially for those slowlymoving 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.2018.8455274ISBN: 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: 2019-02-01Bibliographically approved

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

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Fan, HongqiKucner, Tomasz PiotrMagnusson, MartinLilienthal, Achim
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