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OakleyIan

Oakley, Ian
Interactions Lab.
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dc.citation.conferencePlace CN -
dc.citation.conferencePlace Toronto, ON -
dc.citation.endPage 178 -
dc.citation.startPage 169 -
dc.citation.title 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014 -
dc.contributor.author Oakley, Ian -
dc.contributor.author Lee, Doyoung -
dc.date.accessioned 2023-12-20T00:07:27Z -
dc.date.available 2023-12-20T00:07:27Z -
dc.date.created 2014-05-27 -
dc.date.issued 2014-04-26 -
dc.description.abstract The touch screen interaction paradigm, currently dominant in mobile devices, begins to fail when very small systems are considered. Specifically, "fat fingers", a term referring to the fact that users' extremities physically obstruct their view of screen content and feedback, become particularly problematic. This paper presents a novel solution for this issue based on sensing touches to the perpendicular edges of a device featuring a front-mounted screen. The use of such offset contact points ensures that both a user's fingers and the device screen remain clearly in view throughout a targeting operation. The configuration also supports a range of novel interaction scenarios based on the touch, grip and grasp patterns it affords. To explore the viability of this concept, this paper describes EdgeTouch, a small (6 cm) hardware prototype instantiating this multi-touch functionality. User studies characterizing targeting performance, typical user grasps and exploring input affordances are presented. The results show that targets of 7.5-22.5 degrees in angular size are acquired in 1.25-1.75 seconds and with accuracy rates of 3%-18%, promising results considering the small form factor of the device. Furthermore, grasps made with between two and five fingers are robustly identifiable. Finally, we characterize the types of input users envisage performing with EdgeTouch, and report occurrence rates for key interactions such as taps, holds, strokes and multi-touch and compound input. The paper concludes with a discussion of the interaction scenarios enabled by offset sensing. -
dc.identifier.bibliographicCitation 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014, pp.169 - 178 -
dc.identifier.doi 10.1145/2556288.2557138 -
dc.identifier.scopusid 2-s2.0-84900435985 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/46645 -
dc.identifier.url http://dl.acm.org/citation.cfm?doid=2556288.2557138 -
dc.language 영어 -
dc.publisher 32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014 -
dc.title Interaction on the edge: Offset sensing for small devices -
dc.type Conference Paper -
dc.date.conferenceDate 2014-04-26 -

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