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See me, see you: a lightweight method for discriminating user touches on tabletop displays

Published: 05 May 2012 Publication History

Abstract

Tabletop systems provide a versatile space for collaboration, yet, in many cases, are limited by the inability to differentiate the interactions of simultaneous users. We present See Me, See You, a lightweight approach for discriminating user touches on a vision-based tabletop. We contribute a valuable characterization of finger orientation distributions of tabletop users. We exploit this biometric trait with a machine learning approach to allow the system to predict the correct position of users as they touch the surface. We achieve accuracies as high as 98% in simple situations and above 92% in more challenging conditions, such as two-handed tasks. We show high acceptance from users, who can self-correct prediction errors without significant costs. See Me, See You is a viable solution for providing simple yet effective support for multi-user application features on tabletops.

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    cover image ACM Conferences
    CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    May 2012
    3276 pages
    ISBN:9781450310154
    DOI:10.1145/2207676
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 05 May 2012

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    Author Tags

    1. multi-user application
    2. position aware system
    3. tabletop interaction
    4. touch discrimination

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