Toward a direct measure of video quality perception using EEG

Simon Scholler, Sebastian Bosse, Matthias Sebastian Treder, Benjamin Blankertz, Gabriel Curio, Klaus Robert Müller, Thomas Wiegand

Research output: Contribution to journalArticlepeer-review

113 Citations (Scopus)


An approach to the direct measurement of perception of video quality change using electroencephalography (EEG) is presented. Subjects viewed 8-s video clips while their brain activity was registered using EEG. The video signal was either uncompressed at full length or changed from uncompressed to a lower quality level at a random time point. The distortions were introduced by a hybrid video codec. Subjects had to indicate whether they had perceived a quality change. In response to a quality change, a positive voltage change in EEG (the so-called P3 component) was observed at latency of about 400-600 ms for all subjects. The voltage change positively correlated with the magnitude of the video quality change, substantiating the P3 component as a graded neural index of the perception of video quality change within the presented paradigm. By applying machine learning techniques, we could classify on a single-trial basis whether a subject perceived a quality change. Interestingly, some video clips wherein changes were missed (i.e., not reported) by the subject were classified as quality changes, suggesting that the brain detected a change, although the subject did not press a button. In conclusion, abrupt changes of video quality give rise to specific components in the EEG that can be detected on a single-trial basis. Potentially, a neurotechnological approach to video assessment could lead to a more objective quantification of quality change detection, overcoming the limitations of subjective approaches (such as subjective bias and the requirement of an overt response). Furthermore, it allows for real-time applications wherein the brain response to a video clip is monitored while it is being viewed.

Original languageEnglish
Article number6151827
Pages (from-to)2619-2629
Number of pages11
JournalIEEE Transactions on Image Processing
Issue number5
Publication statusPublished - 2012 May


  • Electroencephalography (EEG)
  • perception
  • video coding
  • video quality

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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