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Evaluation of Signal Processing Methods for Attention Assessment in Visual Content Interaction

  • Georgia ElafoudiEmail author
  • Vladimir Stankovic
  • Lina Stankovic
  • Deepti Pappusetti
  • Hari Kalva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)

Abstract

Eye movements and changes in pupil dilation are known to provide information about viewer’s attention and interaction with visual content. This paper evaluates different statistical and signal processing methods for autonomously analysing pupil dilation signals and extracting information about viewer’s attention when perceiving visual information. In particular, using a commercial video-based eye tracker to estimate pupil dilation and gaze fixation, we demonstrate that wavelet-based signal processing provides an effective tool for pupil dilation analysis and discuss the effect that different image content has on pupil dilation and viewer’s attention.

Keywords

Power Spectral Density Discrete Wavelet Transform Content Image Pupil Size Mental Workload 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Georgia Elafoudi
    • 1
    Email author
  • Vladimir Stankovic
    • 1
  • Lina Stankovic
    • 1
  • Deepti Pappusetti
    • 2
  • Hari Kalva
    • 2
  1. 1.Department of Electronic and Electrical EngineeringUniversity of StrathclydeGlasgowUK
  2. 2.Department of Computer and Electrical Engineering and Computer ScienceFlorida Atlantic UniversityBoca RatonUSA

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