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Design of video quality metrics with multi-way data analysis: a data driven approach

This book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- quality metrics to be created using arbitrary features. This data- driven design approach not only requires no detailed knowledge of the human visual system, but...

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Detalles Bibliográficos
Autor principal: Keimel, Christian
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-0269-4
http://cds.cern.ch/record/2120188
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author Keimel, Christian
author_facet Keimel, Christian
author_sort Keimel, Christian
collection CERN
description This book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- quality metrics to be created using arbitrary features. This data- driven design approach not only requires no detailed knowledge of the human visual system, but also allows a proper consideration of the temporal nature of video using a three-way prediction model, corresponding to the three-way structure of video. Using two simple example metrics, the author demonstrates not only that this purely data- driven approach outperforms state-of-the-art video-quality metrics, which are often optimized for specific properties of the human visual system, but also that multi-way data analysis methods outperform the combination of two-way data analysis methods and temporal pooling. .
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2016
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spelling cern-21201882021-04-21T19:56:09Zdoi:10.1007/978-981-10-0269-4http://cds.cern.ch/record/2120188engKeimel, ChristianDesign of video quality metrics with multi-way data analysis: a data driven approachEngineeringThis book proposes a data-driven methodology using multi-way data analysis for the design of video-quality metrics. It also enables video- quality metrics to be created using arbitrary features. This data- driven design approach not only requires no detailed knowledge of the human visual system, but also allows a proper consideration of the temporal nature of video using a three-way prediction model, corresponding to the three-way structure of video. Using two simple example metrics, the author demonstrates not only that this purely data- driven approach outperforms state-of-the-art video-quality metrics, which are often optimized for specific properties of the human visual system, but also that multi-way data analysis methods outperform the combination of two-way data analysis methods and temporal pooling. .Springeroai:cds.cern.ch:21201882016
spellingShingle Engineering
Keimel, Christian
Design of video quality metrics with multi-way data analysis: a data driven approach
title Design of video quality metrics with multi-way data analysis: a data driven approach
title_full Design of video quality metrics with multi-way data analysis: a data driven approach
title_fullStr Design of video quality metrics with multi-way data analysis: a data driven approach
title_full_unstemmed Design of video quality metrics with multi-way data analysis: a data driven approach
title_short Design of video quality metrics with multi-way data analysis: a data driven approach
title_sort design of video quality metrics with multi-way data analysis: a data driven approach
topic Engineering
url https://dx.doi.org/10.1007/978-981-10-0269-4
http://cds.cern.ch/record/2120188
work_keys_str_mv AT keimelchristian designofvideoqualitymetricswithmultiwaydataanalysisadatadrivenapproach