DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Taejun | ko |
dc.contributor.author | Ham, Auejin | ko |
dc.contributor.author | Ahn, Sunggeun | ko |
dc.contributor.author | Lee, Geehyuk | ko |
dc.date.accessioned | 2022-09-30T02:00:57Z | - |
dc.date.available | 2022-09-30T02:00:57Z | - |
dc.date.created | 2022-09-27 | - |
dc.date.created | 2022-09-27 | - |
dc.date.created | 2022-09-27 | - |
dc.date.issued | 2022-05 | - |
dc.identifier.citation | 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 | - |
dc.identifier.uri | http://hdl.handle.net/10203/298786 | - |
dc.description.abstract | We present Lattice Menu, a gaze-based marking menu utilizing a lattice of visual anchors that helps perform accurate gaze pointing for menu item selection. Users who know the location of the desired item can leverage target-assisted gaze gestures for multilevel item selection by looking at visual anchors over the gaze trajectories. Our evaluation showed that Lattice Menu exhibits a considerably low error rate (∼1%) and a quick menu selection time (1.3-1.6 s) for expert usage across various menu structures (4 × 4 × 4 and 6 × 6 × 6) and sizes (8, 10 and 12°). In comparison with a traditional gaze-based marking menu that does not utilize visual targets, Lattice Menu showed remarkably (∼5 times) fewer menu selection errors for expert usage. In a post-interview, all 12 subjects preferred Lattice Menu, and most subjects (8 out of 12) commented that the provisioning of visual targets facilitated more stable menu selections with reduced eye fatigue. | - |
dc.language | English | - |
dc.publisher | Association for Computing Machinery | - |
dc.title | Lattice Menu: A Low-Error Gaze-Based Marking Menu Utilizing Target-Assisted Gaze Gestures on a Lattice of Visual Anchors | - |
dc.type | Conference | - |
dc.identifier.wosid | 000890212502046 | - |
dc.identifier.scopusid | 2-s2.0-85130546079 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Virtual | - |
dc.identifier.doi | 10.1145/3491102.3501977 | - |
dc.contributor.localauthor | Lee, Geehyuk | - |
dc.contributor.nonIdAuthor | Ham, Auejin | - |
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