A user-friendly interactive framework for unsteady fluid flow segmentation and visualization

Detalhes bibliográficos
Autor(a) principal: Motta, Danilo
Data de Publicação: 2018
Outros Autores: Casaca, Wallace [UNESP], Pagliosa, Paulo, Paiva, Afonso
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s12650-018-0474-6
http://hdl.handle.net/11449/170652
Resumo: Abstract: While vector fields are essential to simulate a large amount of natural phenomena, the difficulty to identify patterns and predict behaviors makes the visual segmentation in simulations an attractive and powerful tool. In this paper, we present a novel user-steered segmentation framework to cope with steady as well as unsteady vector fields on fluid flow simulations. Given a discrete vector field, our approach extracts multi-valued features from the field by exploiting its streamline structures so that these features are mapped to a visual space through a multidimensional projection technique. From an easy-to-handle interface, the user can interact with the projected data so as to partition and explore the most relevant vector features in a guidance frame of the simulation. Besides navigating and visually mining structures of interest, the interactivity with the projected data also allows the user to progressively enhance the segmentation result according to his insights. Finally, to successfully deal with unsteady simulations, the segments previously annotated by the user are used as a training set for a Support Vector Machine approach that classifies the remaining frames in the flow. We attest the effectiveness and versatility of our methodology throughout a set of classical physical-inspired applications on fluid flow simulations as depicted in the experiment results section. Graphical Abstract: [Figure not available: see fulltext.].
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spelling A user-friendly interactive framework for unsteady fluid flow segmentation and visualizationFlow segmentationInteractive toolsMachine learningTime-varying visualizationVector fieldAbstract: While vector fields are essential to simulate a large amount of natural phenomena, the difficulty to identify patterns and predict behaviors makes the visual segmentation in simulations an attractive and powerful tool. In this paper, we present a novel user-steered segmentation framework to cope with steady as well as unsteady vector fields on fluid flow simulations. Given a discrete vector field, our approach extracts multi-valued features from the field by exploiting its streamline structures so that these features are mapped to a visual space through a multidimensional projection technique. From an easy-to-handle interface, the user can interact with the projected data so as to partition and explore the most relevant vector features in a guidance frame of the simulation. Besides navigating and visually mining structures of interest, the interactivity with the projected data also allows the user to progressively enhance the segmentation result according to his insights. Finally, to successfully deal with unsteady simulations, the segments previously annotated by the user are used as a training set for a Support Vector Machine approach that classifies the remaining frames in the flow. We attest the effectiveness and versatility of our methodology throughout a set of classical physical-inspired applications on fluid flow simulations as depicted in the experiment results section. Graphical Abstract: [Figure not available: see fulltext.].Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade de São Paulo (USP) ICMCUniversidade Estadual Paulista (UNESP)Universidade Federal de Mato Grosso do Sul (UFMS) FACOMUniversidade Estadual Paulista (UNESP)FAPESP: 2013/07375-0FAPESP: 2014/16857-0CAPES: 88881.133553/2016-01Universidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Universidade Federal de Mato Grosso do Sul (UFMS)Motta, DaniloCasaca, Wallace [UNESP]Pagliosa, PauloPaiva, Afonso2018-12-11T16:51:51Z2018-12-11T16:51:51Z2018-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article625-636application/pdfhttp://dx.doi.org/10.1007/s12650-018-0474-6Journal of Visualization, v. 21, n. 4, p. 625-636, 2018.1875-89751343-8875http://hdl.handle.net/11449/17065210.1007/s12650-018-0474-62-s2.0-850418222492-s2.0-85041822249.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Visualization0,267info:eu-repo/semantics/openAccess2023-11-04T06:09:37Zoai:repositorio.unesp.br:11449/170652Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-11-04T06:09:37Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
title A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
spellingShingle A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
Motta, Danilo
Flow segmentation
Interactive tools
Machine learning
Time-varying visualization
Vector field
title_short A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
title_full A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
title_fullStr A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
title_full_unstemmed A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
title_sort A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
author Motta, Danilo
author_facet Motta, Danilo
Casaca, Wallace [UNESP]
Pagliosa, Paulo
Paiva, Afonso
author_role author
author2 Casaca, Wallace [UNESP]
Pagliosa, Paulo
Paiva, Afonso
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
Universidade Federal de Mato Grosso do Sul (UFMS)
dc.contributor.author.fl_str_mv Motta, Danilo
Casaca, Wallace [UNESP]
Pagliosa, Paulo
Paiva, Afonso
dc.subject.por.fl_str_mv Flow segmentation
Interactive tools
Machine learning
Time-varying visualization
Vector field
topic Flow segmentation
Interactive tools
Machine learning
Time-varying visualization
Vector field
description Abstract: While vector fields are essential to simulate a large amount of natural phenomena, the difficulty to identify patterns and predict behaviors makes the visual segmentation in simulations an attractive and powerful tool. In this paper, we present a novel user-steered segmentation framework to cope with steady as well as unsteady vector fields on fluid flow simulations. Given a discrete vector field, our approach extracts multi-valued features from the field by exploiting its streamline structures so that these features are mapped to a visual space through a multidimensional projection technique. From an easy-to-handle interface, the user can interact with the projected data so as to partition and explore the most relevant vector features in a guidance frame of the simulation. Besides navigating and visually mining structures of interest, the interactivity with the projected data also allows the user to progressively enhance the segmentation result according to his insights. Finally, to successfully deal with unsteady simulations, the segments previously annotated by the user are used as a training set for a Support Vector Machine approach that classifies the remaining frames in the flow. We attest the effectiveness and versatility of our methodology throughout a set of classical physical-inspired applications on fluid flow simulations as depicted in the experiment results section. Graphical Abstract: [Figure not available: see fulltext.].
publishDate 2018
dc.date.none.fl_str_mv 2018-12-11T16:51:51Z
2018-12-11T16:51:51Z
2018-08-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s12650-018-0474-6
Journal of Visualization, v. 21, n. 4, p. 625-636, 2018.
1875-8975
1343-8875
http://hdl.handle.net/11449/170652
10.1007/s12650-018-0474-6
2-s2.0-85041822249
2-s2.0-85041822249.pdf
url http://dx.doi.org/10.1007/s12650-018-0474-6
http://hdl.handle.net/11449/170652
identifier_str_mv Journal of Visualization, v. 21, n. 4, p. 625-636, 2018.
1875-8975
1343-8875
10.1007/s12650-018-0474-6
2-s2.0-85041822249
2-s2.0-85041822249.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Visualization
0,267
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 625-636
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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