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陈岭, 季诚夏, 黄伟恺, 陈日, 陈根才. 面向移动增强现实的屏幕外对象可视化方法[J]. 计算机辅助设计与图形学学报, 2012, 24(6): 832-838.
引用本文: 陈岭, 季诚夏, 黄伟恺, 陈日, 陈根才. 面向移动增强现实的屏幕外对象可视化方法[J]. 计算机辅助设计与图形学学报, 2012, 24(6): 832-838.
Chen Ling, Ji Chengxia, Huang Weikai, Chen Ri, Chen Gencai. An Off-Screen Object Visualization Approach for Mobile Augment Reality[J]. Journal of Computer-Aided Design & Computer Graphics, 2012, 24(6): 832-838.
Citation: Chen Ling, Ji Chengxia, Huang Weikai, Chen Ri, Chen Gencai. An Off-Screen Object Visualization Approach for Mobile Augment Reality[J]. Journal of Computer-Aided Design & Computer Graphics, 2012, 24(6): 832-838.

面向移动增强现实的屏幕外对象可视化方法

An Off-Screen Object Visualization Approach for Mobile Augment Reality

  • 摘要: 现有移动增强现实屏幕外对象可视化方法往往将对象信息集中在屏幕中心进行显示,由于移动计算设备屏幕尺寸一般较小,在屏幕外对象数量多时会导致显示过于密集,进而影响可视化性能.为此提出一种屏幕外对象可视化方法,利用屏幕边缘相对较大的空间实现大量屏幕外对象的可视化.该方法基于地理信息数据及传感器姿态数据,将屏幕外对象以标注箭头形式分散于屏幕边缘来描述屏幕外对象的相对位置及相对距离,并通过可自适应距离的建筑捕捉框来可视化屏幕内对象,提高系统使用效率.实验结果表明,文中方法在进行搜寻周边建筑任务时能提供比传统屏幕外对象可视化方法更好的性能,其中搜寻时间减少11.02%,用户满意度提高14.72%.

     

    Abstract: Current mobile augmented reality off-screen visualization methods usually display the digital objects in the center of the screen.However,due to the limited screen size of a handle device,it would be intensive when there are many objects and thus have a low visualizing performance.To address this,we proposed an off-screen visualization method which utilized the edge of the screen to visualize many off-screen objects simultaneously.Based on geographical data and sensors,the method displayed arrows around the screen to indicate the directions and distances of off-screen objects,also a box whose size could be adaptive to the distance between the device and an in-screen building was designed for indicating the building,to increase the system performance.Experiments were conducted to compare the performance of the proposed method and the traditional method which displays the objects in the center of the screen.The results showed that the proposed method had a better performance in terms of locating buildings,with task completion time decreasing 11.02% and user satisfaction increasing 14.72%.

     

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