Please wait a minute...
工程设计学报  2019, Vol. 26 Issue (4): 416-422    DOI: 10.3785/j.issn.1006-754X.2019.04.007
工业设计     
基于Fitts定律的虚拟现实小目标选择模型
尤乾, 吕健, 李阳, 金昱潼, 赵子健
贵州大学 现代制造技术教育部重点实验室, 贵州 贵阳 550025
Small target selection model in virtual reality based on Fitts' law
YOU Qian, Lü Jian, LI Yang, JIN Yu-tong, ZHAO Zi-jian
Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University,Guiyang 550025, China
 全文: PDF(1309 KB)   HTML
摘要: 为了准确地选择虚拟现实人机交互过程中的小目标,避免因手和控制器抖动导致选择精度较低等情况,提出了一种基于Fitts定律的虚拟情境中有效测算小目标交互时间的方法。首先,类比图形用户界面中的移动距离和目标宽度,明确了虚拟情境中Fitts定律的适用性。其次,设计实验并对虚拟情境下的Fitts公式进行回归分析,得到相关系数R2=0.896 3,说明预测时间与真实时间有偏差。接着,利用MATLAB cftool拟合工具箱对不同目标尺寸进行回归分析,结合方差分析发现拟合直线的截距与目标尺寸之间显著相关,结合虚拟情境的Fitts公式建立了虚拟现实小目标选择模型。然后,对新模型进行多元回归分析,确定相关系数R2=0.976 7,说明新模型能够有效预测捕获小目标的时间;分析了运动方向对交互时间的影响,结果表明新模型在不同运动方向下都具有良好的适用性,能够有效指导虚拟情境交互任务中良好目标尺寸的计算。最后,以某VR(virtual reality,虚拟现实)隧道救援体验系统为例进行实验评估。实验结果表明,利用该模型能够在获取虚拟现实小目标时有效减少用户的交互时间,提供更好的用户体验。研究结果能为相关设计开发人员确定虚拟情境下的界面布局提供有效指导,并一定程度上优化用户的交互体验。
Abstract: In order to accurately select small target in the process of human-computer interaction in virtual reality and avoid the poor user selection accuracy due to the hand and controller jitter, a method was proposed based on Fitts' law to effectively measure the interaction time of small target in virtual situation. Firstly, the applicability of Fitts' law in virtual environment was clarified by analogy of moving distance and target width in graphical user interface. Secondly, the experiment was designed and the regression analysis of Fitts's formula in virtual situation was carried out. The correlation coefficient R2=0.896 3 indicated that the prediction time deviated from the real time. Then, MATLAB cftool was used to perform linear regression for different target sizes. Combined with the analysis of variance, the intercept of the fitted line was significantly correlated with the target size, and then combined with the Fitts's formula in virtual situation, the small target selection model was established in virtual reality. The new model was subjected to multiple regression analysis to determine the correlation coefficient R2=0.976 7, which indicated that the new model could effectively predict the time of capturing small target. Then the influence of the motion direction on the interaction time was analyzed. The new model had good applicability to different motion directions and it could effectively guide to calculate the good selection size in the virtual context interaction task. Finally, a virtual reality tunnel rescue experience system was taken as an example for experimental evaluation. The results indicated that using this model could effectively reduce the user interaction time and provide a better user experience when acquiring small target in virtual reality. The research results can provide effective guidance for the design developer to determine the interface layout in virtual situation and optimize the user interaction experience to some extent.
收稿日期: 2019-01-14 出版日期: 2019-08-28
CLC:  TP 391  
基金资助: 国家自然科学基金资助项目(51865004);贵州省科技厅基金资助项目([2017]1046,[2017]2016,[2018]1049)
通讯作者: 吕健(1983—),男,河北承德人,副教授,硕士生导师,博士,从事工业设计与交互设计研究,E-mail:jlv@gzu.edu.cn     E-mail: jlv@gzu.edu.cn
作者简介: 尤乾(1994—),男,安徽阜阳人,硕士生,从事信息与交互设计研究,E-mail:youqian411@qq.com, https://orcid.org/0000-0002-2042-173X
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

尤乾, 吕健, 李阳, 金昱潼, 赵子健. 基于Fitts定律的虚拟现实小目标选择模型[J]. 工程设计学报, 2019, 26(4): 416-422.

YOU Qian, Lü Jian, LI Yang, JIN Yu-tong, ZHAO Zi-jian. Small target selection model in virtual reality based on Fitts' law. Chinese Journal of Engineering Design, 2019, 26(4): 416-422.

链接本文:

https://www.zjujournals.com/gcsjxb/CN/10.3785/j.issn.1006-754X.2019.04.007        https://www.zjujournals.com/gcsjxb/CN/Y2019/V26/I4/416

[1] 来全宝, 陶庆, 胡玉舸, 孟庆丰. 基于人工鱼群算法-极限学习机的多手势精准识别[J]. 工程设计学报, 2021, 28(6): 671-678.
[2] 倪子健, 李文强, 唐忠. 基于网络表示学习的本体语义挖掘与功能语义检索方法[J]. 工程设计学报, 2021, 28(5): 539-547.
[3] 王洪申, 刘敏, 强会英. 基于极半径曲面矩和HMM的三维模型分类与检索算法[J]. 工程设计学报, 2021, 28(4): 407-414.
[4] 王春香, 纪康辉, 王耀, 刘流. 快速成型技术中分段算法的研究综述[J]. 工程设计学报, 2021, 28(4): 399-406.
[5] 徐勇明, 汤一帆, 张盛, 史建勋, 郁云忠, 张征. 电力线缆自动化矫直的仿真和实验研究[J]. 工程设计学报, 2021, 28(3): 329-334.
[6] 颜宝明, 潘伟杰, 吕健, 王毅, 赵泽宇. 面向VR放置任务的自然手势交互时间的预测[J]. 工程设计学报, 2021, 28(3): 296-304.
[7] 王春香, 郝林文, 王耀, 周国勇, 纪康辉, 刘流. 基于GA-BP神经网络的散乱点云孔洞自动修补[J]. 工程设计学报, 2021, 28(2): 155-162.
[8] 张世淼, 邵宏宇, 陈辰, 陈永亮. 云制造环境下板材余料资源的服务匹配方法[J]. 工程设计学报, 2021, 28(2): 121-131.
[9] 陈洋, 任成祖, 邓晓帆, 陈光, 靳新民. 基于双盘直槽研磨的圆柱滚子自转运动研究[J]. 工程设计学报, 2021, 28(2): 179-189.
[10] 姚寿文, 胡子然, 柳博文, 丁佳, 常富祥, 栗丽辉. 基于实时装配状态感知和直观性交互的虚拟现实辅助维修训练[J]. 工程设计学报, 2021, 28(1): 14-24.
[11] 邓晓帆, 任成祖, 陈洋, 陈光, 蔡智杰, 贺英伦. 基于摩擦磨损实验的双盘直槽研磨方法的研具选材研究[J]. 工程设计学报, 2020, 27(6): 720-728.
[12] 汪威, 张开颜, 刘亚川, 黄玉春. 三维点云的两步校准法及其应用研究[J]. 工程设计学报, 2020, 27(5): 560-567.
[13] 李梦. 基于机器视觉的车道线在线识别系统设计[J]. 工程设计学报, 2020, 27(4): 498-507.
[14] 李典伦, 黄华, 邓文强. 数控机床液体静压导轨结构的优化设计[J]. 工程设计学报, 2020, 27(4): 448-455.
[15] 张帆, 褚少微, 吉娜烨. 可变摩擦力触感移动终端的汉语盲文编码设计[J]. 工程设计学报, 2020, 27(2): 154-161.