Evaluation of EEG-Based Predictions of Image QoE in Augmented Reality Scenarios

Brian Bauman, Patrick Seeling

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Augmented Reality (AR) devices and phone adaptations are commonly head-worn to overlay context-dependent information into the field of view of the device operators. One particular scenario is the overlay of still images, for which we evaluate the interplay of user ratings as Quality of Experience (QoE) with (i) the non-referential BRISQUE objective image quality metric as QoS and (ii) human subject dry electrode EEG signals gathered with a commercial device. We find strong correlations for subject-specific EEG portfolios, resulting in an approach to the predictability of the QoE. Our overall results can be employed in practical scenarios by mobile content and network service providers to optimize the user experience in augmented reality scenarios with a passive human in-the-loop in the future.

Original languageEnglish
Title of host publication2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538663585
StatePublished - Jul 2 2018
Event88th IEEE Vehicular Technology Conference, VTC-Fall 2018 - Chicago, United States
Duration: Aug 27 2018Aug 30 2018

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252


Conference88th IEEE Vehicular Technology Conference, VTC-Fall 2018
Country/TerritoryUnited States


  • Augmented reality
  • Electroencephalography
  • Image quality
  • Quality of experience
  • Quality of service


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