Visual attention to repeated internet images: testing the scanpath theory on the world wide web
ETRA '02 Proceedings of the 2002 symposium on Eye tracking research & applications
The determinants of web page viewing behavior: an eye-tracking study
Proceedings of the 2004 symposium on Eye tracking research & applications
Testing for statistically significant differences between groups of scan patterns
Proceedings of the 2008 symposium on Eye tracking research & applications
Group-wise similarity and classification of aggregate scanpaths
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Visual scanpath representation
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Scanpath clustering and aggregation
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Algorithm for discriminating aggregate gaze points: comparison with salient regions-of-interest
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
From gaze plots to eye fixation patterns using a clustering method based on Hausdorff distances
23rd French Speaking Conference on Human-Computer Interaction
Some applications of string algorithms in human-computer interaction
Algorithms and Applications
Saccade deviation indicators for automated eye tracking analysis
Proceedings of the 2013 Conference on Eye Tracking South Africa
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While fixation data and saccadic indices have been employed as individual measures, less frequent analysis has been attempted on the sequence or pattern data that these two indices together create. The patterns of fixations and saccades are rich and complex, and hence, they are typically studied as individual paths or parts of paths that are isolated. Analysis is usually a visual comparison, although more recently there have been studies that have compared scan patterns statistically [Josephson and Holmes 2002; Pan et al. 2002; Yarbus 1967]. In the current work we explore a method for deriving an "average" scan pattern aggregated from many users viewing the same visual stimulus (web site).