课题基金 / 基金详情

ITR/SI: Real-Time Long-Distance Terascale Computation for Full Bandwidth Tele-Immersion

ITR/SI: Real-Time Long-Distance Terascale Computation for Full Bandwidth Tele-Immersion
ITR/SI:用于全带宽远程沉浸的实时长距离万亿级计算
批准号:
0121293
负责人:
Henry Fuchs
金额:
$265.15万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-15 至 2005-08-31
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中文摘要
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英文摘要
Tele-immersion, an ability to share presence with distant individuals, situations, and environments, may provide vast new possibilities for human experience and interaction in the near future. In order to make these dreams a reality, a host of technical difficulties must be solved: acquisition, communication, display, and interaction. This project focuses on answering two of the major questions: 1) Is tele-immersion as good as its promise or is there some inherent weakness? By using overwhelming computation power, the PI hopes to accelerate development so a real system can be tried within three years. 2) Is there a show-stopper with tele-immersion over long distances? The PI will try it for real, not just simulated distance via artificial delays. Specifically, the PI will build a 60-camera system at the University of Pennsylvania, compute depth on the 3000-processor Terascale Computing System at the Pittsburgh Supercomputing Center, and display at the University of North Carolina. The PI will have a more modest acquisition system at UNC (15 cameras) and a more modest display system at UPenn to enable local development and two-way collaboration. The testbed application will be remote medical consultation by a trauma surgeon, chosen because of its inherent demand for real-time response and its great potential benefit to societal. The PI expects to be able to provide demonstrable progress within the three year period of the project. Team members who are leading trauma surgeons will guide the design; evaluation will be by other trauma surgeons. The three years of effort will lead to a testable prototype with sufficient power and scope to be evaluated by application experts not on the research team. The results will indicate the likely success of other tele-immersion applications, as well as providing experience in building real-time applications on a remote terascale facility over fast wide-area networks.
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Collaborative Research: HCC: Medium: Deep Learning-Based Tracking of Eyes and Lens Shape from Purkinje Images for Holographic Augmented Reality Glasses
RI: Small: Uncovering Dynamics from Internet Imagery
FW-HTF: Collaborative Research: Enhancing Human Capabilities through Virtual Personal Embodied Assistants in Self-Contained Eyeglasses-Based Augmented Reality (AR) Systems
CHS: Small: Collaborative Research: 3D Audio Augmentation for Limited Field of View Augmented Reality Systems for Medical Training
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