Eye tracking in advanced interface design
Virtual environments and advanced interface design
Eye gaze interaction with expanding targets
CHI '04 Extended Abstracts on Human Factors in Computing Systems
EyePrint: support of document browsing with eye gaze trace
Proceedings of the 6th international conference on Multimodal interfaces
Improving hands-free menu selection using eyegaze glances and fixations
Proceedings of the 2008 symposium on Eye tracking research & applications
Eye typing using word and letter prediction and a fixation algorithm
Proceedings of the 2008 symposium on Eye tracking research & applications
Improving eye cursor's stability for eye pointing tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluation of gaze-added target selection methods suitable for general GUIs
International Journal of Computer Applications in Technology
Personalized online document, image and video recommendation via commodity eye-tracking
Proceedings of the 2008 ACM conference on Recommender systems
Low-cost gaze interaction: ready to deliver the promises
CHI '09 Extended Abstracts on Human Factors in Computing Systems
GazeSpace: eye gaze controlled content spaces
BCS-HCI '07 Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI...but not as we know it - Volume 2
An eye-gaze input system using information on eye movement history
UAHCI'07 Proceedings of the 4th international conference on Universal access in human-computer interaction: ambient interaction
Look & touch: gaze-supported target acquisition
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
| Hi-index | 0.00 |
Gaze data processing is an important and necessary step in gaze-based applications. This study focuses on the comparison of several gaze-to-object mapping algorithms using various dwell times for selection and presenting targets of several types and sizes. Seven algorithms found in literature were compared against two newly designed algorithms. The study revealed that a fractional mapping algorithm (known) has produced the highest rate of correct selections and fastest selection times, but also the highest rate of incorrect selections. The dynamic competing algorithm (designed) has shown the next best result, but also high rate of incorrect selections. A small impact on the type of target to the calculated statistics has been observed. A strictly centered gazing has helped to increase the rate of correct selections for all algorithms and types of targets. The directions for further mapping algorithms improvement and future investigation have been explained.