A Neural Network Model of Spatial Distortion Sensitivity for Video Quality Estimation

Soren Becker, Klaus Robert Muller, Thomas Wiegand, Sebastian Bosse

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate estimation of visual quality as perceived by humans is crucial for modern multimedia systems and, given the evident ease for humans, a surprisingly difficult task for computers. Complexity considerations as imperative for real-time applications render this problem even more challenging. This paper studies the application of a neural network-based spatial model of distortion sensitivity to the quality prediction of spatio-temporal videos. We propose a simple yet effective adaptation of the loss function to cope with saturation effects in human quality ratings. This adaptation drastically decreases the number of iterations necessary for training networks to replicate psychophysical human responses. Our experimental results show significantly improved prediction performance of the spatio-temporal PSNR when compensated for spatial distortion sensitivity while maintaining the advantage of low complexity.

Original languageEnglish
Title of host publication2019 IEEE 29th International Workshop on Machine Learning for Signal Processing, MLSP 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728108247
DOIs
Publication statusPublished - 2019 Oct
Externally publishedYes
Event29th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2019 - Pittsburgh, United States
Duration: 2019 Oct 132019 Oct 16

Publication series

NameIEEE International Workshop on Machine Learning for Signal Processing, MLSP
Volume2019-October
ISSN (Print)2161-0363
ISSN (Electronic)2161-0371

Conference

Conference29th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2019
CountryUnited States
CityPittsburgh
Period19/10/1319/10/16

Keywords

  • distortion sensitivity
  • neural network
  • video compression
  • video quality
  • Visual perception

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing

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  • Cite this

    Becker, S., Muller, K. R., Wiegand, T., & Bosse, S. (2019). A Neural Network Model of Spatial Distortion Sensitivity for Video Quality Estimation. In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing, MLSP 2019 [8918899] (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/MLSP.2019.8918899