DC Field | Value | Language |
---|---|---|
dc.contributor.author | ahn, sunggeun | ko |
dc.contributor.author | Lee, Geehyuk | ko |
dc.date.accessioned | 2020-01-20T05:20:59Z | - |
dc.date.available | 2020-01-20T05:20:59Z | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.created | 2020-01-20 | - |
dc.date.issued | 2019-10-17 | - |
dc.identifier.citation | UIST '19: The 32nd Annual ACM Symposium on User Interface Software and Technology, pp.857 - 869 | - |
dc.identifier.uri | http://hdl.handle.net/10203/271583 | - |
dc.description.abstract | Text entry is expected to be a common task for smart glass users, which is generally performed using a touchpad on the temple or by a promising approach using eye tracking. However, each approach has its own limitations. For more efficient text entry, we present the concept of gaze-assisted typing (GAT), which uses both a touchpad and eye tracking. We initially examined GAT with a minimal eye input load, and demonstrated that the GAT technology was 51% faster than a two-step touch input typing method (i.e.,M-SwipeBoard: 5.85 words per minute (wpm) and GAT: 8.87 wpm). We also compared GAT methods with varying numbers of touch gestures. The results showed that a GAT requiring five different touch gestures was the most preferred, although all GAT techniques were equally efficient. Finally, we compared GAT with touch-only typing (SwipeZone) and eye-only typing (adjustable dwell) using an eye-trackable head-worn display. The results demonstrate that the most preferred technique, GAT, was 25.4% faster than the eye-only typing and 29.4% faster than the touch-only typing (GAT: 11.04 wpm, eye-only typing: 8.81 wpm, and touch-only typing: 8.53 wpm). | - |
dc.language | English | - |
dc.publisher | ACM | - |
dc.title | Gaze-Assisted Typing for Smart Glasses | - |
dc.type | Conference | - |
dc.identifier.wosid | 000518189200068 | - |
dc.identifier.scopusid | 2-s2.0-85074850406 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 857 | - |
dc.citation.endingpage | 869 | - |
dc.citation.publicationname | UIST '19: The 32nd Annual ACM Symposium on User Interface Software and Technology | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | New Orleans, Louisiana | - |
dc.identifier.doi | 10.1145/3332165.3347883 | - |
dc.contributor.localauthor | Lee, Geehyuk | - |
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