<div class="csl-bib-body">
<div class="csl-entry">Schmidt, J., Gröller, E., & Bruckner, S. (2013). VAICo: Visual Analysis for Image Comparison. <i>IEEE Transactions on Visualization and Computer Graphics</i>, <i>19</i>(12), 2090–2099. https://doi.org/10.1109/tvcg.2013.213</div>
</div>
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dc.identifier.issn
1077-2626
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/155825
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dc.description.abstract
Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains.
en
dc.language.iso
en
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dc.publisher
Institute of Electrical and Electronics Engineers (IEEE)
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dc.relation.ispartof
IEEE Transactions on Visualization and Computer Graphics
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dc.subject
Software
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dc.subject
Computer Graphics and Computer-Aided Design
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dc.subject
Computer Vision and Pattern Recognition
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dc.subject
Signal Processing
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dc.subject
Comparative visualization
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dc.subject
Image set comparison
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dc.subject
Focus+context visualization Abstract
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dc.title
VAICo: Visual Analysis for Image Comparison
en
dc.type
Artikel
de
dc.type
Article
en
dc.description.startpage
2090
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dc.description.endpage
2099
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dc.type.category
Original Research Article
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tuw.container.volume
19
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tuw.container.issue
12
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
-
tuw.publication.invited
invited
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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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dcterms.isPartOf.title
IEEE Transactions on Visualization and Computer Graphics
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tuw.publication.orgunit
E193-02 - Forschungsbereich Computer Graphics
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tuw.publisher.doi
10.1109/tvcg.2013.213
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dc.identifier.eissn
1941-0506
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dc.description.numberOfPages
10
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wb.sci
true
-
wb.sciencebranch
Mathematik, Informatik
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wb.sciencebranch.oefos
11
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wb.facultyfocus
Visual Computing and Human-Centered Technology (VC + HCT)
de
wb.facultyfocus
Visual Computing and Human-Centered Technology (VC + HCT)
en
wb.facultyfocus.faculty
E180
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item.grantfulltext
none
-
item.cerifentitytype
Publications
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item.fulltext
no Fulltext
-
item.languageiso639-1
en
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item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
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item.openairetype
research article
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crisitem.author.dept
E193 - Institut für Visual Computing and Human-Centered Technology
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crisitem.author.dept
E193-02 - Forschungsbereich Computer Graphics
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crisitem.author.dept
E193-02 - Forschungsbereich Computer Graphics
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crisitem.author.orcid
0000-0002-8569-4149
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crisitem.author.parentorg
E180 - Fakultät für Informatik
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology