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Design of Video Quality Metrics with Multi-Way Data Analysis - Christian Keimel - Bog

- A data driven approach

Bag om Design of Video Quality Metrics with Multi-Way Data Analysis

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789811091193
  • Indbinding:
  • Paperback
  • Sideantal:
  • 240
  • Udgivet:
  • 31. Marts 2018
  • Udgave:
  • 12016
  • Størrelse:
  • 155x235x0 mm.
  • Vægt:
  • 454 g.
  • 2-3 uger.
  • 13. Juni 2024
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Beskrivelse af Design of Video Quality Metrics with Multi-Way Data Analysis

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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