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An EEG-Based Study on Perception of Video Distortion under Various Content Motion Conditions

  • Xiwen Liu
  • , Xiaoming Tao*
  • , Mai Xu
  • , Yafeng Zhan
  • , Jianhua Lu
  • *Corresponding author for this work
  • Tsinghua University

Research output: Contribution to journalArticlepeer-review

Abstract

Human perception sensitivity to video distortion is vital for visual quality assessment (VQA). Different from the perception mechanism of image distortion that has been thoroughly studied, the perception of video distortion is inevitably influenced by motion of dynamic content due to the characteristics of the human visual system (HVS). In this paper, electroencephalography (EEG) is used as a novel psychophysiological method to study the human perception sensitivity to quantification-aroused video distortion under various content motion conditions. For this purpose, we conduct experiments to record the EEG signals of the subjects when they are watching distorted videos. According to the feature analysis of EEG data, the P300 component aroused by human perception of video quality change is selected as the indicator of human perception of distortion. By the means of classification based on linear discriminant analysis (LDA), it is found that the separability of the P300 component, which is measured by the area under curve (AUC) of the receiver operating characteristic (ROC), is positively correlated with the perceptibility of distortion. The correlation provides a valid psychophysiological method, which is exempt from being influenced by subjective bias due to human high-level cognitive activities, for evaluating distortion perceptibility. In addition, the regression analysis results demonstrate a sigmoid-typed quantitative relation between the perceptibility of distortion and separability of the P300 component. Based on such relation, the perceptibility thresholds of distortion corresponding to various content motion speeds are calibrated by EEG signals and it is found that the content motion speed has a significant impact on distortion perceptibility.

Original languageEnglish
Article number8793159
Pages (from-to)949-960
Number of pages12
JournalIEEE Transactions on Multimedia
Volume22
Issue number4
DOIs
StatePublished - Apr 2020

Keywords

  • AUC
  • Distortion
  • EEG
  • LDA classifier
  • P300
  • perceptibility threshold

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