Evaluation of an Eye Tracking Selection Technique with Progressive Refinement
dc.contributor.advisor | Kopper, Regis | |
dc.contributor.author | Wang, Yunhan | |
dc.date.accessioned | 2018-05-31T21:18:44Z | |
dc.date.available | 2019-05-15T08:17:12Z | |
dc.date.issued | 2018 | |
dc.department | Mechanical Engineering and Materials Science | |
dc.description.abstract | We designed a novel eye tracking selection technique with progressive refinement - eye-controlled sphere-casting refined by quad-menu (EyeSQUAD) selection technique. Through a user study, we evaluated the performance of this technique with comparison of two previous selection techniques - ray-casting and SQUAD under different target size and distractor density scenarios. Results show that the EyeSQUAD technique can achieve similar selection speed as ray-casting and SQUAD and is more accurate than ray-casting although less precise than SQUAD. Finally, we summarized several insights for designing interaction techniques with eye tracking. | |
dc.identifier.uri | ||
dc.subject | Computer science | |
dc.subject | Mechanical engineering | |
dc.subject | eye tracking | |
dc.subject | interaction technique | |
dc.subject | Selection | |
dc.subject | Virtual reality | |
dc.title | Evaluation of an Eye Tracking Selection Technique with Progressive Refinement | |
dc.type | Master's thesis | |
duke.embargo.months | 11 |