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

    120 Citations (Scopus)

    Abstract

    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
    Volume21
    Issue number5
    DOIs
    Publication statusPublished - 2012 May

    Bibliographical note

    Funding Information:
    Manuscript received September 21, 2011; revised January 05, 2012; accepted January 10, 2012. Date of publication February 13, 2012; date of current version April 18, 2012. This work was supported by the HC3 program of the Berlin Institute of Technology, and also supported by the World Class University Program through the National Research Foundation of Korea funded by the Ministry of Education, Science, and Technology, under Grant R31-10008. This work was supported in part by the Federal Ministry of Education and Research (BMBF) under Grant Fkz 01IB001A/B and Grant 01GQ0850. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. James E. Fowler.

    Keywords

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

    ASJC Scopus subject areas

    • Software
    • Computer Graphics and Computer-Aided Design

    Fingerprint

    Dive into the research topics of 'Toward a direct measure of video quality perception using EEG'. Together they form a unique fingerprint.

    Cite this