Tilting operations for small screen interfaces
Proceedings of the 9th annual ACM symposium on User interface software and technology
BlueTable: connecting wireless mobile devices on interactive surfaces using vision-based handshaking
GI '07 Proceedings of Graphics Interface 2007
It's Mine, Don't Touch!: interactions at a large multi-touch display in a city centre
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Tilt techniques: investigating the dexterity of wrist-based input
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Poker surface: combining a multi-touch table and mobile phones in interactive card games
Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services
Worlds of information: designing for engagement at a public multi-touch display
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PhoneTouch: a technique for direct phone interaction on surfaces
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
Your phone or mine?: fusing body, touch and device sensing for multi-user device-display interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A cross-device interaction style for mobiles and surfaces
Proceedings of the Designing Interactive Systems Conference
Personal clipboards for individual copy-and-paste on shared multi-user surfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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While very large collaborative surfaces are already being widely employed to facilitate concurrent interactions with multiple users, they involve no personalization in the touch interactions. Augmenting them to identify the touch interactions with multiple smart-phones can enable interesting co-located communal applications with context-based personalized interactions and information exchange amongst users' portable devices and the shared wall display. This paper proposes a novel matching technique, called tilt correlation, which employs the built-in tilt sensor to identify smart-phones that make concurrent two-point contacts on a common multi-touch wall display. Experimental investigations suggest that the resultant error rate is relatively low; in addition, we also propose a quantitative measure, called the Bourne Identity Index to allow application designers to determine the reliability of each device identification.