Manual and gaze input cascaded (MAGIC) pointing
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Hand eye coordination patterns in target selection
ETRA '00 Proceedings of the 2000 symposium on Eye tracking research & applications
Acquisition of expanding targets
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 2004 symposium on Eye tracking research & applications
"Beating" Fitts' law: virtual enhancements for pointing facilitation
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
Eye-mouse coordination patterns on web search results pages
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Fitts' law as a research and design tool in human-computer interaction
Human-Computer Interaction
Human-Computer Interaction
Disambiguating ninja cursors with eye gaze
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Rake cursor: improving pointing performance with concurrent input channels
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Towards artificial systems: what can we learn from human perception?
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Look & touch: gaze-supported target acquisition
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Comparing eye and gesture pointing to drag items on large screens
Proceedings of the 2013 ACM international conference on Interactive tabletops and surfaces
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Selecting a graphical item by pointing with a computer mouse is a ubiquitous task in many graphical user interfaces. Several techniques have been suggested to facilitate this task, for instance, by reducing the required movement distance. Here we measure the natural coordination of eye and mouse pointer control across several search and selection tasks. We find that users automatically minimize the distance to likely targets in an intelligent, task dependent way. When target location is highly predictable, top-down knowledge can enable users to initiate pointer movements prior to target fixation. These findings question the utility of existing assistive pointing techniques and suggest that alternative approaches might be more effective.