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%.

中文翻译：

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具有运动预测功能的智能手机上的平滑图形用户交互

人机交互的流畅度直接影响用户体验，影响他们的购买决策。提高智能手机用户交互的常用方法是优化 CPU 调度程序。但是，优化 CPU 调度程序需要修改操作系统。此外，由于显示子系统没有优化，人机交互流畅度的提升可能会受到限制。因此，在本文中，我们设计了一个名为 MPQS 的运动预测排队系统，以提高人机交互的平滑度。为此，我们利用Android的排队机制提供的向量、速度、移动信息来预测用户与智能手机交互的移动。根据预测，然后我们利用帧之间的可用执行时间来执行图像处理。我们在 beagleboard-xM 上进行了一组实验来评估 MPQS 的性能。我们的实验结果表明，所提出的方法可以减少高达 21.75% 的卡顿次数。