Tools and Techniques for Video Performance Evaluation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Robust clustering of eye movement recordings for quantification of visual interest
Proceedings of the 2004 symposium on Eye tracking research & applications
eyePatterns: software for identifying patterns and similarities across fixation sequences
Proceedings of the 2006 symposium on Eye tracking research & applications
Where people look when watching movies: Do all viewers look at the same place?
Computers in Biology and Medicine
Continuum: designing timelines for hierarchies, relationships and scale
Proceedings of the 20th annual ACM symposium on User interface software and technology
Advanced gaze visualizations for three-dimensional virtual environments
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Visual exploration of eye movement data using the space-time-cube
GIScience'10 Proceedings of the 6th international conference on Geographic information science
eSeeTrack—Visualizing Sequential Fixation Patterns
IEEE Transactions on Visualization and Computer Graphics
Evaluation of Traditional, Orthogonal, and Radial Tree Diagrams by an Eye Tracking Study
IEEE Transactions on Visualization and Computer Graphics
Proceedings of the Symposium on Eye Tracking Research and Applications
Measuring gaze overlap on videos between multiple observers
Proceedings of the Symposium on Eye Tracking Research and Applications
EyeC: Coordinated Views for Interactive Visual Exploration of Eye-Tracking Data
IV '13 Proceedings of the 2013 17th International Conference on Information Visualisation
Space-Time Visual Analytics of Eye-Tracking Data for Dynamic Stimuli
IEEE Transactions on Visualization and Computer Graphics
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We introduce a new design for the visual analysis of eye tracking data recorded from dynamic stimuli such as video. ISeeCube includes multiple coordinated views to support different aspects of various analysis tasks. It combines methods for the spatiotemporal analysis of gaze data recorded from unlabeled videos as well as the possibility to annotate and investigate dynamic Areas of Interest (AOIs). A static overview of the complete data set is provided by a space-time cube visualization that shows gaze points with density-based color mapping and spatiotemporal clustering of the data. A timeline visualization supports the analysis of dynamic AOIs and the viewers' attention on them. AOI-based scanpaths of different viewers can be clustered by their Levenshtein distance, an attention map, or the transitions between AOIs. With the provided visual analytics techniques, the exploration of eye tracking data recorded from several viewers is supported for a wide range of analysis tasks.