Smoothed Graphic User Interaction on Smartphones with Motion Prediction

Ying Dar Lin, Edward T.H. Chu, Evan Chang, Yuan Cheng Lai

Research output: Contribution to journalArticlepeer-review

Abstract

The smoothness of human-smartphone interaction directly influences users experience and affects their purchase decisions. A commonly used method to improve user interaction of smartphones is to optimize the CPU scheduler. However, optimizing the CPU scheduler requires a modification of operating system. In addition, the improvement of the smoothness of human-smartphone interaction may be limited because the display subsystem is not optimized. Therefore, in this paper, we design a motion prediction queuing system, named MPQS, to improve the smoothness of human-smartphone interaction. For this, we use the information of vector, speed, movement, provided by the queuing mechanism of Android, to predict the movement of user-smartphone interaction. Based on the prediction, we then utilize available execution time between frames to perform image processing. We conducted a set of experiments on beagleboard-xM to evaluate the performance of MPQS. Our experiment results show that the proposed method can reduce the number of jank by up to 21.75%.

Original languageEnglish
Article number7894225
Pages (from-to)1429-1441
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume50
Issue number4
DOIs
StatePublished - Apr 2020

Keywords

  • Frame interval
  • graphic user interaction
  • motion prediction
  • smartphones
  • smoothness

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