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

  • Chang T
  • Li Y
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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.

Author-supplied keywords

  • camera
  • computer vision
  • mobile interaction
  • multi-device environment
  • task migration.

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  • Tsung-Hsiang Chang

  • Yang Li

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