<div class="csl-bib-body">
<div class="csl-entry">Ceneda, D., Arleo, A., Gschwandtner, T., & Miksch, S. (2022, June 14). <i>Show Me Your Face: Towards an Automated Method to Provide Timely Guidance in Visual Analytics</i> [Conference Presentation]. EuroVis 2022, Rom, Italy. https://doi.org/10.1109/TVCG.2021.3094870</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/136164
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dc.description.abstract
Providing guidance during a Visual Analytics session can support analysts in pursuing their goals more efficiently. However, the effectiveness of guidance depends on many factors: Determining the right timing to provide it is one of them. Although in complex analysis scenarios choosing the right timing could make the difference between a dependable and a superfluous guidance, an analysis of the literature suggests that this problem did not receive enough attention. In this paper, we describe a methodology to determine moments in which guidance is needed. Our assumption is that the need of guidance would influence the user state-of-mind, as in distress situations during the analytical process, and we hypothesize that such moments could be identified by analyzing the user's facial expressions. We propose a framework composed by a facial recognition software and a machine learning model trained to detect when to provide guidance according to changes of the user facial expressions. We trained the model by interviewing eight analysts during their work and ranked multiple facial features based on their relative importance in determining the need of guidance. Finally, we show that by applying only minor modifications to its architecture, our prototype was able to detect a need of guidance on the fly and made our methodology well suited also for real-time analysis sessions. The results of our evaluations show that our methodology is indeed effective in determining when a need of guidance is present, which constitutes a prerequisite to providing timely and effective guidance in VA.
en
dc.description.sponsorship
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
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dc.language.iso
en
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dc.subject
Machine Learning
en
dc.subject
Software
en
dc.subject
Facial Expression
en
dc.subject
Computer Graphics
en
dc.subject
Algorithms
en
dc.title
Show Me Your Face: Towards an Automated Method to Provide Timely Guidance in Visual Analytics
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.relation.grantno
ICT19-47
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dc.relation.grantno
880883
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dc.relation.grantno
P 31419-N31
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dc.type.category
Conference Presentation
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tuw.publication.invited
invited
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tuw.project.title
Guidance-Enriched Visual Analytics for Temporal Data
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tuw.project.title
Domain-adaptive Remote sensing Image Analysis with Human-in-the-loop
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tuw.project.title
Wissensunterstützte Visual Analytics
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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.linking
https://conferences.eg.org/eurovis2022/program/
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tuw.publication.orgunit
E193-07 - Forschungsbereich Visual Analytics
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tuw.publisher.doi
10.1109/TVCG.2021.3094870
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tuw.author.orcid
0000-0003-1198-567X
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tuw.author.orcid
0000-0003-2008-3651
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tuw.author.orcid
0000-0003-4427-5703
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tuw.event.name
EuroVis 2022
en
tuw.event.startdate
13-06-2022
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tuw.event.enddate
17-06-2022
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Rom
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tuw.event.country
IT
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tuw.event.institution
La Sapienza University
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tuw.event.presenter
Ceneda, Davide
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tuw.event.track
Multi Track
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wb.sciencebranch
Informatik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.value
100
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item.languageiso639-1
en
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item.openairecristype
http://purl.org/coar/resource_type/c_18cp
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item.fulltext
no Fulltext
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item.openairetype
conference paper not in proceedings
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item.grantfulltext
none
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item.cerifentitytype
Publications
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crisitem.project.funder
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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crisitem.project.funder
FFG - Österr. Forschungsförderungs- gesellschaft mbH
-
crisitem.project.funder
FWF - Österr. Wissenschaftsfonds
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crisitem.project.grantno
ICT19-47
-
crisitem.project.grantno
880883
-
crisitem.project.grantno
P 31419-N31
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crisitem.author.dept
E193-07 - Forschungsbereich Visual Analytics
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crisitem.author.dept
E193-07 - Forschungsbereich Visual Analytics
-
crisitem.author.dept
E193-07 - Forschungsbereich Visual Analytics
-
crisitem.author.dept
E193-07 - Forschungsbereich Visual Analytics
-
crisitem.author.orcid
0000-0003-1198-567X
-
crisitem.author.orcid
0000-0003-2008-3651
-
crisitem.author.orcid
0000-0003-4427-5703
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
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
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology