Toward a Direct Measure of Video Quality Perception Using EEG
- Authors
- Scholler, Simon; Bosse, Sebastian; Treder, Matthias Sebastian; Blankertz, Benjamin; Curio, Gabriel; Mueller, Klaus-Robert; Wiegand, Thomas
- Issue Date
- 5월-2012
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Electroencephalography (EEG); perception; video coding; video quality
- Citation
- IEEE TRANSACTIONS ON IMAGE PROCESSING, v.21, no.5, pp.2619 - 2629
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON IMAGE PROCESSING
- Volume
- 21
- Number
- 5
- Start Page
- 2619
- End Page
- 2629
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/108605
- DOI
- 10.1109/TIP.2012.2187672
- ISSN
- 1057-7149
- 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.
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Collections - Graduate School > Department of Brain and Cognitive Engineering > 1. Journal Articles
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