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Design of Video Quality Metrics with Multi-Way Data Analysis [electronic resource] : A data driven approach / by Christian Keimel.

By: Keimel, Christian [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: T-Labs Series in Telecommunication Services: Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XV, 240 p. 52 illus., 2 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811002694.Subject(s): Signal processing | User interfaces (Computer systems) | Human-computer interaction | Telecommunication | Signal, Speech and Image Processing | User Interfaces and Human Computer Interaction | Communications Engineering, NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
Introduction -- Video Quality -- Video Quality Metrics -- Data Analysis Approach -- Two-way Data Analysis -- Multi-way Data Analysis -- Model Building Considerations -- Designing Video Quality Metrics -- Performance Comparison -- Conclusion.
In: Springer Nature eBookSummary: 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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Introduction -- Video Quality -- Video Quality Metrics -- Data Analysis Approach -- Two-way Data Analysis -- Multi-way Data Analysis -- Model Building Considerations -- Designing Video Quality Metrics -- Performance Comparison -- Conclusion.

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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