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Evaluation of video artifact perception using event-related potentials

Published: 27 August 2011 Publication History

Abstract

When new computer graphics algorithms for image and video editing, rendering or compression are developed, the quality of the results has to be evaluated and compared. Since the produced media are usually to be presented to an audience it is important to predict image and video quality as it would be perceived by a human observer. This can be done by applying some image quality metric or by expensive and time consuming user studies. Typically, statistical image quality metrics do not correlate to quality perceived by a human observer. More sophisticated HVS-inspired algorithms often do not generalize to arbitrary images. A drawback of user studies is that perceived image or video quality is filtered by a decision process, which, in turn, may be influenced by the performed task and chosen quality scale. To get an objective view on (subjectively) perceived image quality, electroencephalography can be used. In this paper we show that artifacts appearing in videos elicit a measurable brain response which can be analyzed using the event-related potentials technique. Since electroencephalography itself requires an elaborate procedure, we aim to find a minimal setup to reduce time and participants needed to conduct a reliable study of image and video quality. As a first step we demonstrate that the reaction to a video with or without an artifact can be identified by an off-the-shelf support vector machine, which is trained on a set of previously recorded responses, with a reliability of up to 80% from a single recorded electroencephalogram.

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cover image ACM Conferences
APGV '11: Proceedings of the ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization
August 2011
128 pages
ISBN:9781450308892
DOI:10.1145/2077451
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 27 August 2011

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Author Tags

  1. artifact detection
  2. electroen-cephalography (EEG)
  3. event-related potentials (ERP)
  4. perception
  5. support vector machines (SVM)
  6. video

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  • (2024)Brain-Inspired Image Perceptual Quality Assessment Based on EEG: A QoE PerspectiveIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.340868446:12(8424-8441)Online publication date: Dec-2024
  • (2024)Brain-Inspired Visual Attention Modeling Based on EEG for Intelligent RoboticsIEEE Journal of Selected Topics in Signal Processing10.1109/JSTSP.2024.340810018:3(431-443)Online publication date: Apr-2024
  • (2022)Human Perception Measurement by Electroencephalography for Facial Image CompressionIEEE Signal Processing Letters10.1109/LSP.2022.321115729(2148-2152)Online publication date: 2022
  • (2020)An EEG-Based Study on Perception of Video Distortion Under Various Content Motion ConditionsIEEE Transactions on Multimedia10.1109/TMM.2019.293442522:4(949-960)Online publication date: 24-Mar-2020
  • (2018)Analysis of neural correlates of saccadic eye movementsProceedings of the 15th ACM Symposium on Applied Perception10.1145/3225153.3225164(1-9)Online publication date: 10-Aug-2018
  • (2018)Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral DecompositionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2017.269480728:8(1694-1706)Online publication date: Aug-2018
  • (2018)On the Stimulation Frequency in SSVEP-based Image Quality Assessment2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)10.1109/QoMEX.2018.8463381(1-6)Online publication date: May-2018
  • (2018)Study of image quality using event‐related potentials and eye tracking measurementJournal of the Society for Information Display10.1002/jsid.65326:6(339-351)Online publication date: 26-Apr-2018
  • (2017)Comparative Analysis of Three Different Modalities for Perception of Artifacts in VideosACM Transactions on Applied Perception (TAP)10.1145/312928914:4(1-12)Online publication date: 14-Sep-2017
  • (2017)Objective quality assessment of stereoscopic images with vertical disparity using EEGJournal of Neural Engineering10.1088/1741-2552/aa6d8b14:4(046009)Online publication date: 25-May-2017
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