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dc.contributor.author
Maffra, Fabiola
dc.contributor.author
Pinto Teixeira, Lucas
dc.contributor.author
Chen, Zetao
dc.contributor.author
Chli, Margarita
dc.date.accessioned
2019-11-05T09:09:16Z
dc.date.available
2019-01-31T09:12:57Z
dc.date.available
2019-01-31T09:35:54Z
dc.date.available
2019-03-14T07:01:28Z
dc.date.available
2019-10-17T09:59:41Z
dc.date.available
2019-11-05T09:09:16Z
dc.date.issued
2019-04
dc.identifier.issn
2377-3766
dc.identifier.other
10.1109/lra.2019.2895826
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/321767
dc.identifier.doi
10.3929/ethz-b-000321767
dc.description.abstract
Place recognition is an essential capability for robotic autonomy. While ground robots observe the world from generally similar viewpoints over repeated visits, other robots, such as small aircraft, experience far more different viewpoints, requiring place recognition for images captured from very wide baselines. While traditional feature-based methods fail dramatically under extreme viewpoint changes, deep learning approaches demand heavy runtime processing. Driven by the need for cheaper alternatives able to run on computationally restricted platforms, such as small aircraft, this work proposes a novel real-time pipeline employing depth-completion on sparse feature maps that are anyway computed during robot localization and mapping, to enable place recognition at extreme viewpoint changes. The proposed approach demonstrates unprecedented precision-recall rates on challenging benchmarking and own synthetic and real datasets with up to 45◦ difference in viewpoints. In particular, our synthetic datasets are, to the best of our knowledge, the first to isolate the challenge of viewpoint changes for place recognition, addressing a crucial gap in the literature. All of the new datasets are publicly available to aid benchmarking.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Aerial Systems: Perception and Autonomy
en_US
dc.subject
Visual-Based Navigation
en_US
dc.subject
SLAM
en_US
dc.subject
Localization
en_US
dc.subject
Place Recognition
en_US
dc.title
Real-time Wide-baseline Place Recognition using Depth Completion
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-01-29
ethz.journal.title
IEEE Robotics and Automation Letters
ethz.journal.volume
4
en_US
ethz.journal.issue
2
en_US
ethz.pages.start
1525
en_US
ethz.pages.end
1532
en_US
ethz.size
8 p.
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.grant
Collaborative vision-based perception for teams of (aerial) robots
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09559 - Chli, Margarita (ehemalig) / Chli, Margarita (former)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09559 - Chli, Margarita (ehemalig) / Chli, Margarita (former)
en_US
ethz.grant.agreementno
157585
ethz.grant.agreementno
157585
ethz.grant.agreementno
157585
ethz.grant.fundername
SNF
ethz.grant.fundername
SNF
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
SNF-Förderungsprofessuren Stufe 2
ethz.date.deposited
2019-01-31T09:13:04Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-03-14T07:01:48Z
ethz.rosetta.lastUpdated
2022-03-29T00:13:08Z
ethz.rosetta.exportRequired
true
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true
ethz.COinS
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