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Deep shot: a framework for migrating tasks across devices using mobile phone cameras

Published:07 May 2011Publication History

ABSTRACT

A user task often spans multiple heterogeneous devices, e.g., working on a PC in the office and continuing the work on a laptop or a mobile phone while commuting on a shuttle. However, there is a lack of support for users to easily migrate their tasks across devices. To address this problem, we created Deep Shot, a framework for capturing the user's work state that is needed for a task (e.g., the specific part of a webpage being viewed) and resuming it on a different device. In particular, Deep Shot supports two novel and intuitive interaction techniques, deep shooting and deep posting, for pulling and pushing work states, respectively, using a mobile phone camera. In addition, Deep Shot provides a concise API for developers to leverage its services and make their application states migratable. We demonstrated that Deep Shot can be used to support a range of everyday tasks migrating across devices. An evaluation consisting of a series of experiments showed that our framework and techniques are feasible.

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    • Published in

      cover image ACM Conferences
      CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      May 2011
      3530 pages
      ISBN:9781450302289
      DOI:10.1145/1978942

      Copyright © 2011 ACM

      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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      New York, NY, United States

      Publication History

      • Published: 7 May 2011

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      CHI '11 Paper Acceptance Rate410of1,532submissions,27%Overall Acceptance Rate6,199of26,314submissions,24%

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