Acquisition of Off-Screen Object by Predictive Jumping
Acquisition of Off-Screen Object by Predictive Jumping
复制标题
通过预测跳跃获取屏幕外物体
DOI：
10.1007/978-3-540-70585-7_34
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
F. Kishino
中科院分区：
文献类型：
--
作者：
Kazuki Takashima;S. Subramanian;Takayuki Tsukitani;Y. Kitamura;F. Kishino
我们提出了预测跳跃（PJ），一种快速有效的算法，使用户导航到屏幕外的目标。该算法的灵感来自Delphian Desktop [1]和离屏可视化技术-Halo [2]。在视口边缘显示的光晕帮助用户估计屏幕外的目标距离，并鼓励他们向目标进行单个流畅的鼠标移动。在用户运动的中途，系统预测用户的预期目标，并将光标快速移动到预测的屏幕外位置。在一项试点研究中，我们研究了用户选择屏幕外目标的能力与预测模型的基础上，用户的指向运动学与光环屏幕外指向。我们建立了PJ的峰值速度与目标距离之间的线性关系。然后，我们进行了一项对照实验，以评估PJ与其他基于Halo的技术，Hop [8]和Pan with Halo。研究结果显示了PJ的有效性。
We propose predictive jumping (PJ), a fast and efficient algorithm that enables user navigation to off-screen targets. The algorithm is inspired by Delphian Desktop [1] and the off-screen visualization technique---Halo [2]. The Halos represented at the edge of the viewport help users estimate off-screen target distance and encourage them to make a single fluid mouse movement toward the target. Halfway through the user's motion, the system predicts the user's intended target and quickly moves the cursor towards that predicted off-screen location. In a pilot study we examine the user's ability to select off-screen targets with predictive models based on user's pointing kinematics for off-screen pointing with Halo. We establish a linear relationship between peak velocity and target distance for PJ. We then conducted a controlled experiment to evaluate PJ against other Halo-based techniques, Hop [8] and Pan with Halo. The results of the study highlight the effectiveness of PJ.