2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map

Hongqi Fan; Dawei Lu; Tomasz P. Kucner; Martin Magnusson; Achim J. Lilienthal

doi:10.23919/ICIF.2018.8455274

2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map

Hongqi Fan, Dawei Lu, Tomasz P. Kucner, Martin Magnusson, Achim J. Lilienthal

Not published at Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

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.

Original language	English
Title of host publication	Proceedings of 21st International Conference on Information Fusion, FUSION 2018
Publisher	IEEE
Number of pages	7
ISBN (Electronic)	978-0-9964527-6-2
DOIs	https://doi.org/10.23919/ICIF.2018.8455274
Publication status	Published - Sept 2018
MoE publication type	A4 Conference publication
Event	International Conference on Information Fusion - Cambridge, United Kingdom Duration: 10 Jul 2018 → 13 Jul 2018 Conference number: 21

Conference

Conference	International Conference on Information Fusion
Abbreviated title	FUSION
Country/Territory	United Kingdom
City	Cambridge
Period	10/07/2018 → 13/07/2018

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@inproceedings{c145d68bb90b48dcab08d88b63a29210,

title = "2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map",

abstract = "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.",

author = "Hongqi Fan and Dawei Lu and Kucner, {Tomasz P.} and Martin Magnusson and Lilienthal, {Achim J.}",

year = "2018",

month = sep,

doi = "10.23919/ICIF.2018.8455274",

language = "English",

booktitle = "Proceedings of 21st International Conference on Information Fusion, FUSION 2018",

publisher = "IEEE",

address = "United States",

note = "International Conference on Information Fusion, FUSION ; Conference date: 10-07-2018 Through 13-07-2018",

}

Fan, H, Lu, D, Kucner, TP, Magnusson, M & Lilienthal, AJ 2018, 2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map. in Proceedings of 21st International Conference on Information Fusion, FUSION 2018. IEEE, International Conference on Information Fusion, Cambridge, United Kingdom, 10/07/2018. https://doi.org/10.23919/ICIF.2018.8455274

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T1 - 2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map

AU - Fan, Hongqi

AU - Lu, Dawei

AU - Kucner, Tomasz P.

AU - Magnusson, Martin

AU - Lilienthal, Achim J.

N1 - Conference code: 21

PY - 2018/9

Y1 - 2018/9

N2 - 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.

AB - 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.

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U2 - 10.23919/ICIF.2018.8455274

DO - 10.23919/ICIF.2018.8455274

M3 - Conference contribution

BT - Proceedings of 21st International Conference on Information Fusion, FUSION 2018

PB - IEEE

T2 - International Conference on Information Fusion

Y2 - 10 July 2018 through 13 July 2018

ER -

2D Spatial Keystone Transform for Sub-Pixel Motion Extraction from Noisy Occupancy Grid Map

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