Length-independent refinement of video quality metrics based on multiway data analysis

Clemens Horch, Christian Keimel, Julian Habigt, Klaus Diepold

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In previous publications it has been shown that no-reference video quality metrics based on a data analysis approach rather than on modeling the human visual system lead to very promising results and outperform many well-known full-reference metrics. Furthermore, the results improve when taking the temporal structure of the video sequence into account by using multiway analysis methods. This contribution shows a way of refining these multiway quality metrics in order to make them more suitable for real-life applications and maintaining the performance at the same time. Additionally, our results confirm the validity of H.264/AVC bitstream no-reference quality metrics using multiway PLSR by evaluating this concept on an additional dataset.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
PublisherIEEE Computer Society
Pages44-48
Number of pages5
ISBN (Print)9781479923410
DOIs
StatePublished - 2013
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: 15 Sep 201318 Sep 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period15/09/1318/09/13

Keywords

  • Video quality metric
  • multiway PLSR
  • multiway data analysis
  • no-reference metric
  • trilinear PLS

Fingerprint

Dive into the research topics of 'Length-independent refinement of video quality metrics based on multiway data analysis'. Together they form a unique fingerprint.

Cite this