Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information

This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism of FMTHL and SGTs to deal with erroneous, missing, and noisy data and compl...

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Autores:
Tipo de recurso:
Book
Fecha de publicación:
2017
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
ger
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/17597
Acceso en línea:
https://directory.doabooks.org/handle/20.500.12854/41905
http://hdl.handle.net/20.500.12010/17597
Palabra clave:
Situation recognition
Kognitives Sichtsystem
Situationsanalyse
Sistemas de visualización tridimensionales
Imágenes digitales
Imágenes tridimensionales
Rights
License
Abierto (Texto Completo)
id UTADEO2_5bb3a2b4ab52b1357795431295a1c1fa
oai_identifier_str oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/17597
network_acronym_str UTADEO2
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dc.title.spa.fl_str_mv Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
title Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
spellingShingle Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
Situation recognition
Kognitives Sichtsystem
Situationsanalyse
Sistemas de visualización tridimensionales
Imágenes digitales
Imágenes tridimensionales
title_short Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
title_full Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
title_fullStr Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
title_full_unstemmed Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
title_sort Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information
dc.subject.spa.fl_str_mv Situation recognition
Kognitives Sichtsystem
Situationsanalyse
topic Situation recognition
Kognitives Sichtsystem
Situationsanalyse
Sistemas de visualización tridimensionales
Imágenes digitales
Imágenes tridimensionales
dc.subject.lemb.spa.fl_str_mv Sistemas de visualización tridimensionales
Imágenes digitales
Imágenes tridimensionales
description This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism of FMTHL and SGTs to deal with erroneous, missing, and noisy data and complexity, demonstrates the robustness of situational recognition in natural scenarios, and expands generic applicability beyond discourse boundaries.
publishDate 2017
dc.date.created.none.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2021-02-22T20:12:07Z
dc.date.available.none.fl_str_mv 2021-02-22T20:12:07Z
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2f33
format http://purl.org/coar/resource_type/c_2f33
dc.identifier.isbn.none.fl_str_mv 9783731506447
dc.identifier.other.none.fl_str_mv https://directory.doabooks.org/handle/20.500.12854/41905
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/17597
dc.identifier.doi.none.fl_str_mv 10.5445/KSP/1000066975
identifier_str_mv 9783731506447
10.5445/KSP/1000066975
url https://directory.doabooks.org/handle/20.500.12854/41905
http://hdl.handle.net/20.500.12010/17597
dc.language.iso.spa.fl_str_mv ger
language ger
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.creativecommons.none.fl_str_mv https://creativecommons.org/licenses/by-sa/4.0/
rights_invalid_str_mv Abierto (Texto Completo)
https://creativecommons.org/licenses/by-sa/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.spa.fl_str_mv XVII, 241 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv KIT Scientific Publishing
institution Universidad de Bogotá Jorge Tadeo Lozano
bitstream.url.fl_str_mv https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17597/1/978-3-7315-0644-7.pdf
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https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17597/2/license.txt
bitstream.checksum.fl_str_mv 0ddc49e0e8662c28c9146639109b6d8b
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repository.name.fl_str_mv Repositorio Institucional - Universidad Jorge Tadeo Lozano
repository.mail.fl_str_mv expeditio@utadeo.edu.co
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spelling 2021-02-22T20:12:07Z2021-02-22T20:12:07Z20179783731506447https://directory.doabooks.org/handle/20.500.12854/41905http://hdl.handle.net/20.500.12010/1759710.5445/KSP/1000066975This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism of FMTHL and SGTs to deal with erroneous, missing, and noisy data and complexity, demonstrates the robustness of situational recognition in natural scenarios, and expands generic applicability beyond discourse boundaries.XVII, 241 páginasapplication/pdfgerKIT Scientific PublishingSituation recognitionKognitives SichtsystemSituationsanalyseSistemas de visualización tridimensionalesImágenes digitalesImágenes tridimensionalesBegriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter InformationAbierto (Texto Completo)https://creativecommons.org/licenses/by-sa/4.0/http://purl.org/coar/access_right/c_abf2http://purl.org/coar/resource_type/c_2f33Münch, DavidORIGINAL978-3-7315-0644-7.pdf978-3-7315-0644-7.pdfVer documentoapplication/pdf12485023https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17597/1/978-3-7315-0644-7.pdf0ddc49e0e8662c28c9146639109b6d8bMD51open accessTHUMBNAIL978-3-7315-0644-7.pdf.jpg978-3-7315-0644-7.pdf.jpgIM Thumbnailimage/jpeg15147https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17597/3/978-3-7315-0644-7.pdf.jpg9e46f73c75fc3fa90015afe09618927fMD53open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/17597/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open access20.500.12010/17597oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/175972021-02-22 15:13:24.242open accessRepositorio Institucional - Universidad Jorge Tadeo Lozanoexpeditio@utadeo.edu.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