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Big visual data analysis: scene classification and geometric labeling

This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural...

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Detalles Bibliográficos
Autores principales: Chen, Chen, Ren, Yuzhuo, Kuo, C -C Jay
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-0631-9
http://cds.cern.ch/record/2137839
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author Chen, Chen
Ren, Yuzhuo
Kuo, C -C Jay
author_facet Chen, Chen
Ren, Yuzhuo
Kuo, C -C Jay
author_sort Chen, Chen
collection CERN
description This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.
id cern-2137839
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
publisher Springer
record_format invenio
spelling cern-21378392021-04-21T19:46:08Zdoi:10.1007/978-981-10-0631-9http://cds.cern.ch/record/2137839engChen, ChenRen, YuzhuoKuo, C -C JayBig visual data analysis: scene classification and geometric labelingEngineeringThis book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.Springeroai:cds.cern.ch:21378392016
spellingShingle Engineering
Chen, Chen
Ren, Yuzhuo
Kuo, C -C Jay
Big visual data analysis: scene classification and geometric labeling
title Big visual data analysis: scene classification and geometric labeling
title_full Big visual data analysis: scene classification and geometric labeling
title_fullStr Big visual data analysis: scene classification and geometric labeling
title_full_unstemmed Big visual data analysis: scene classification and geometric labeling
title_short Big visual data analysis: scene classification and geometric labeling
title_sort big visual data analysis: scene classification and geometric labeling
topic Engineering
url https://dx.doi.org/10.1007/978-981-10-0631-9
http://cds.cern.ch/record/2137839
work_keys_str_mv AT chenchen bigvisualdataanalysissceneclassificationandgeometriclabeling
AT renyuzhuo bigvisualdataanalysissceneclassificationandgeometriclabeling
AT kuoccjay bigvisualdataanalysissceneclassificationandgeometriclabeling