1. Lynn Y. Arnaut and Joel S. Greenstein. 1987. An Evaluation of Display/Control Gain . In Proceedings of the Human Factors Society Annual Meeting, Vol. 31 . SAGE Publications, Los Angeles, CA, USA, 437–441. https://doi.org/10.1177/154 1931 28703100412 10.1177/154193128703100412 Lynn Y. Arnaut and Joel S. Greenstein. 1987. An Evaluation of Display/Control Gain. In Proceedings of the Human Factors Society Annual Meeting, Vol. 31. SAGE Publications, Los Angeles, CA, USA, 437–441. https://doi.org/10.1177/154193128703100412
2. Lynn Y. Arnaut and Joel S. Greenstein . 1990. Is Display/ Control Gain a Useful Metric for Optimizing an Interface? Human Factors 32, 6 ( 1990 ), 651–663. https://doi.org/10.1177/001872089003200604 10.1177/001872089003200604 Lynn Y. Arnaut and Joel S. Greenstein. 1990. Is Display/Control Gain a Useful Metric for Optimizing an Interface?Human Factors 32, 6 (1990), 651–663. https://doi.org/10.1177/001872089003200604
3. Advantages of eye-gaze over head-gaze-based selection in virtual and augmented reality under varying field of views
4. Riccardo Bovo , Daniele Giunchi , Ludwig Sidenmark , Hans Gellersen , Enrico Costanza , and Thomas Heinis . 2022 . Real-Time Head-Based Deep-Learning Model for Gaze Probability Regions in Collaborative VR. In 2022 Symposium on Eye Tracking Research and Applications ( Seattle, WA, USA) (ETRA ’22). Association for Computing Machinery, New York, NY, USA, Article 6, 8 pages. https://doi.org/10.1145/3517031.3529642 10.1145/3517031.3529642 Riccardo Bovo, Daniele Giunchi, Ludwig Sidenmark, Hans Gellersen, Enrico Costanza, and Thomas Heinis. 2022. Real-Time Head-Based Deep-Learning Model for Gaze Probability Regions in Collaborative VR. In 2022 Symposium on Eye Tracking Research and Applications (Seattle, WA, USA) (ETRA ’22). Association for Computing Machinery, New York, NY, USA, Article 6, 8 pages. https://doi.org/10.1145/3517031.3529642
5. XGBoost