Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ETRA '02 Proceedings of the 2002 symposium on Eye tracking research & applications
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IV '04 Proceedings of the Information Visualisation, Eighth International Conference
IEEE Computer Graphics and Applications
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
eyePatterns: software for identifying patterns and similarities across fixation sequences
Proceedings of the 2006 symposium on Eye tracking research & applications
iComp: a tool for scanpath visualization and comparison
ACM SIGGRAPH 2006 Research posters
Introduction to Information Retrieval
Introduction to Information Retrieval
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
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IEEE Transactions on Visualization and Computer Graphics
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Expert Systems with Applications: An International Journal
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INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
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Proceedings of the 3rd BELIV'10 Workshop: BEyond time and errors: novel evaLuation methods for Information Visualization
Parallel scan-path visualization
Proceedings of the Symposium on Eye Tracking Research and Applications
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Proceedings of the Symposium on Eye Tracking Research and Applications
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Proceedings of the 2013 Conference on Eye Tracking South Africa
Space-Time Visual Analytics of Eye-Tracking Data for Dynamic Stimuli
IEEE Transactions on Visualization and Computer Graphics
AOI rivers for visualizing dynamic eye gaze frequencies
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Several algorithms, approaches, and implementations have been developed to support comparison of scan paths and finding of interesting scan path structures. In this work we contribute a visual approach to support scan path comparison. A key feature of this approach is the combination of a clustering algorithm using Levenshtein distance with the parallel scan path visualization technique. The combination of computational methods with an interactive visualization allows us to use both the power of pattern finding algorithms and the human ability to visually recognize patterns. To use the concept in practice we implemented the approach in a prototype and show its application in two scan path analysis scenarios from automobile usability testing and visualization research.