Lattice Menu: A Low-Error Gaze-Based Marking Menu Utilizing Target-Assisted Gaze Gestures on a Lattice of Visual Anchors

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 79
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKim, Taejunko
dc.contributor.authorHam, Auejinko
dc.contributor.authorAhn, Sunggeunko
dc.contributor.authorLee, Geehyukko
dc.date.accessioned2022-09-30T02:00:57Z-
dc.date.available2022-09-30T02:00:57Z-
dc.date.created2022-09-27-
dc.date.created2022-09-27-
dc.date.created2022-09-27-
dc.date.issued2022-05-
dc.identifier.citation2022 CHI Conference on Human Factors in Computing Systems, CHI 2022-
dc.identifier.urihttp://hdl.handle.net/10203/298786-
dc.description.abstractWe 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.languageEnglish-
dc.publisherAssociation for Computing Machinery-
dc.titleLattice Menu: A Low-Error Gaze-Based Marking Menu Utilizing Target-Assisted Gaze Gestures on a Lattice of Visual Anchors-
dc.typeConference-
dc.identifier.wosid000890212502046-
dc.identifier.scopusid2-s2.0-85130546079-
dc.type.rimsCONF-
dc.citation.publicationname2022 CHI Conference on Human Factors in Computing Systems, CHI 2022-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationVirtual-
dc.identifier.doi10.1145/3491102.3501977-
dc.contributor.localauthorLee, Geehyuk-
dc.contributor.nonIdAuthorHam, Auejin-
Appears in Collection
CS-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0