New Methods for Maintaining Good Stereoscopic Viewing During Interaction with Large-Scale Head-Tracked Displays

在与大型头部跟踪显示器交互期间保持良好立体观看的新方法

基本信息

  • 批准号:
    0332923
  • 负责人:
  • 金额:
    $ 7.07万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2003
  • 资助国家:
    美国
  • 起止时间:
    2003-03-10 至 2004-07-31
  • 项目状态:
    已结题

项目摘要

Virtual reality (VR) aims to perceptually place the user in an artificial world through computer-generated sight and sound. VR thus offers a new human-computer interaction paradigm which can improve the user's understanding of and interaction with 3D information spaces in diverse applications domains such as design, data visualization, training, education, and medicine. Stereoscopic VR systems generate imagery by presenting a separate perspective image to each eye. As a result, the user perceives a single, true 3D image that appears to exist in front of and behind the physical display surface. While stereoscopic display is an important and common feature in VR systems, further research is needed because stereoscopic viewing raises concerns beyond those raised in monoscopic VR systems as the user travels through and manipulates the virtual environment. This is especially true for extended virtual environments where the scene contains rendered geometric detail at scales covering several orders of magnitude. In such environments, users need to zoom in and out to move between detailed and global views. This project will investigate techniques for maintaining good stereoscopic viewing conditions under such conditions. The PIs will focus on stereoscopic Head-Tracked Display systems such as the virtual workbench (as distinguished from head-mounted displays in which the display surface is mounted on the user's head). The expected impact of this project will be better understanding and implementations of head-tracked displays based on a thorough geometric and analytic analysis of false eye separation and head-tracking distortions; new and improved techniques for automatic view optics adjustments and automatic view position adjustments to maintain good stereoscopic viewing conditions; and a systematic study of the compatibility between the above methods and the relevant geometric attributes of VR applications.
虚拟现实(VR)旨在通过计算机生成的视觉和声音感知地将用户置于人工世界中。因此,虚拟现实提供了一种新的人机交互范式,可以提高用户在设计、数据可视化、培训、教育和医学等不同应用领域对3D信息空间的理解和交互。立体虚拟现实系统通过向每只眼睛呈现单独的视角图像来生成图像。因此,用户感知到一个单一的,真实的3D图像,似乎存在于物理显示表面的前后。虽然立体显示是虚拟现实系统中一个重要且常见的功能,但由于用户在虚拟环境中穿行和操纵时,立体观看引起的担忧超出了单镜虚拟现实系统所引起的担忧,因此还需要进一步的研究。这对于扩展的虚拟环境来说尤其如此,因为场景包含了几个数量级的几何细节。在这样的环境中,用户需要放大和缩小以在详细视图和全局视图之间移动。该项目将研究在这种条件下保持良好立体观看条件的技术。pi将专注于立体头显跟踪显示系统,如虚拟工作台(与头戴式显示器不同,头戴式显示器的显示表面安装在用户的头上)。该项目的预期影响将是基于对假眼分离和头部跟踪失真的彻底几何和分析分析,更好地理解和实现头部跟踪显示器;新的和改进的自动视场光学调整和自动视场位置调整技术,以保持良好的立体观看条件;以及系统研究上述方法与VR应用相关几何属性之间的兼容性。

项目成果

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Larry Hodges其他文献

Larry Hodges的其他文献

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{{ truncateString('Larry Hodges', 18)}}的其他基金

REU Site: Undergraduate Research in Human-Centered Computing
REU 网站:以人为中心的计算本科生研究
  • 批准号:
    0850695
  • 财政年份:
    2009
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Standard Grant
New Methods for Maintaining Good Stereoscopic Viewing During Interaction with Large-Scale Head-Tracked Displays
在与大型头部跟踪显示器交互期间保持良好立体观看的新方法
  • 批准号:
    9977325
  • 财政年份:
    1999
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Continuing Grant
REU: Software Development Experimental Quantification, and Application Development for Virtual Reality and Real-Time Visualization Systems
REU:软件开发实验量化以及虚拟现实和实时可视化系统的应用程序开发
  • 批准号:
    9424075
  • 财政年份:
    1995
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Continuing Grant
Algorithms for Efficient Generation of Ray-traced Animation Frames
高效生成光线追踪动画帧的算法
  • 批准号:
    9223803
  • 财政年份:
    1993
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Standard Grant
REU SITE Continuing Award: Graphics Representation and Display of Complex Data Sets
REU SITE 连续奖:复杂数据集的图形表示和显示
  • 批准号:
    9200635
  • 财政年份:
    1992
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Continuing Grant
Benefits of Three Dimensional Data in Characterizing Images
三维数据在表征图像方面的优势
  • 批准号:
    8920774
  • 财政年份:
    1989
  • 资助金额:
    $ 7.07万
  • 项目类别:
    Continuing Grant

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Computational Methods for Analyzing Toponome Data
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