<div class="csl-bib-body">
<div class="csl-entry">Strohmayer, J., & Kampel, M. (2022). A Compact Tri-Modal Camera Unit for RGBDT Vision. In <i>2022 the 5th International Conference on Machine Vision and Applications (ICMVA)</i> (pp. 34–42). https://doi.org/10.1145/3523111.3523116</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/150216
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dc.description.abstract
The combination of RGBD and thermal cameras in multi-modal person-centric vision applications has great potential. As a complementary modality, thermal cameras can compensate for weaknesses such as the inability to operate in absolute darkness of conventional RGB cameras or the range limitations associated with consumer depth cameras, resulting in a more robust computer vision system. In addition, the high contrast between persons and their surroundings in thermal images can ease fundamental detection and segmentation tasks. Unfortunately, the market supply of low-cost consumer RGBDT vision systems is non-existent at the moment, which slows down progress in the field of person-centric vision. We address this problem by proposing a Compact Tri-modal CAmera uniT (CTCAT) for RGBDT vision, which can be manufactured from off-the-shelf components and 3D printed parts. CTCAT features a 1280 × 720 RGB camera, a 640 × 480 structured light depth camera with an operating range of 0.6 - 8m, and a 160 × 120 uncooled radiometric thermal camera. RGB, depth, and thermal images can be captured simultaneously at frame rates up to 9 fps. In this work, we describe the components, fabrication, and calibration of CTCAT. In addition, a new multi-modal calibration target suitable for the geometric calibration of RGB, depth, and thermal cameras is presented, which offers advantages over the state of the art in terms of contrast and practicality. Moreover, radiometric calibration of CTCAT is performed to evaluate the applicability to person-centric vision applications requiring radiometry.
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dc.language.iso
en
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dc.subject
computer vision
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dc.subject
depth
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dc.subject
multi-modal camera
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dc.subject
person-centric vision
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dc.subject
RGB
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dc.subject
RGBDT
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dc.subject
sensor fusion
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dc.subject
thermal
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dc.title
A Compact Tri-Modal Camera Unit for RGBDT Vision
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dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
9781450395670
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dc.description.startpage
34
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dc.description.endpage
42
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
2022 the 5th International Conference on Machine Vision and Applications (ICMVA)
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tuw.peerreviewed
true
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tuw.researchTopic.id
I5
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tuw.researchTopic.name
Visual Computing and Human-Centered Technology
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E193-01 - Forschungsbereich Computer Vision
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tuw.publisher.doi
10.1145/3523111.3523116
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dc.description.numberOfPages
9
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tuw.author.orcid
0000-0002-5217-2854
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tuw.event.name
2022 the 5th International Conference on Machine Vision and Applications (ICMVA) (ICMVA 2022)
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tuw.event.startdate
18-02-2022
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tuw.event.enddate
20-02-2022
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tuw.event.online
Online
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tuw.event.type
Event for scientific audience
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tuw.event.country
AT
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tuw.event.presenter
Strohmayer, Julian
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tuw.presentation.online
Online
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
90
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wb.sciencebranch.value
10
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item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.languageiso639-1
en
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item.openairetype
conference paper
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item.grantfulltext
restricted
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crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
-
crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
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crisitem.author.orcid
0000-0003-1560-4221
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crisitem.author.orcid
0000-0002-5217-2854
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crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
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crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology