MRI: Development of Large-Scale Dense Scene Capture and Tracking Instrument

MRI:大规模密集场景捕捉和跟踪仪器的开发

基本信息

  • 批准号:
    1337722
  • 负责人:
  • 金额:
    $ 50万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-09-01 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

Proposal #: 13-37899PI(s): Hahn, James K. Lee, Taeyoung; Philbeck, John W.; Rickmond, Brian G.; Townsend, Gabe SibleyInstitution: George Washington University Title: MRI/Dev.: Large-Scale Dense Scene Capture and Tracking InstrumentProject Proposed:This project, developing a large-scale, dense 3D measurement instrument for capturing dynamic environments, integrates devices such as range-and-color sensing devices like depth cameras (RGB-D sensors) by designing and developing key technical methodologies to fuse the data received from remote networked sensors. The instrument will collectively cover a large space at a sampling resolution of at least 1cm with submillimeter resolution in localized regions. These data are then fused into a single underlying representation. The work involves developing a system that possesses both large-scale and real-time dense capture capabilities. Specifically, - Experimentally validating perception, planning and control algorithms of agile mobile robots (particularly those that operate with deformable objects) requires ground truth representation of those environments.- Validating computational tools for tether dynamics and control for flexible multibody systems requires the capture of their environment in a large environment.- Study of human motion for biomechanics, physical therapy, and exercise science applications requires accurate capture of dynamically changing deformable human shapes in a large environment.- Image-guided surgical procedures require capture of localized dense patient anatomical surface registered in a larger surgical environment.- Human visual perception and navigation require a dense model of the surrounding environments that include object in motion, thus advancing the state of eye movement analysis by enabling fast, automated and objective coding of object analysis by enabling fast, automated, and objective coding of objects people see as they move through the environment.- The study of foot deformations enabled by dense shape capture during running and walking on real sediments will shed light on the evolution of gait and human anatomy, and the biomechanics of barefoot walking and running. Thus, facilitating new research, the developed system enables rapid capture and construction of large dynamic high-resolution virtual environments that duplicate specific real-world environments, including deformable objects, with unprecedented density of detail.
提案编号:13- 37899 PI:Hahn,James K. 放大图片作者:John W. Rickmond,Brian G.;汤森,加布西布利机构:乔治华盛顿大学职称: MRI/器械:大规模密集场景捕获和跟踪仪器项目建议:该项目开发用于捕获动态环境的大规模密集3D测量仪器,通过设计和开发关键技术方法来融合从远程网络传感器接收的数据,集成深度相机(RGB-D传感器)等距离和颜色传感设备。该仪器将以至少1厘米的采样分辨率覆盖大空间,在局部区域具有亚毫米分辨率。然后,这些数据被融合成一个单一的底层表示。这项工作涉及开发一个具有大规模和实时密集捕获能力的系统。具体来说,-实验验证敏捷移动的机器人(特别是那些与可变形物体一起操作的机器人)的感知,规划和控制算法需要这些环境的地面真实表示。验证用于柔性多体系统的系绳动力学和控制的计算工具需要在大环境中捕获其环境。生物力学、物理治疗和运动科学应用中的人体运动研究需要准确捕捉大环境中动态变化的可变形人体形状。图像引导的外科手术程序需要捕获在更大的外科手术环境中配准的局部密集患者解剖表面。人类视觉感知和导航需要周围环境的密集模型,包括运动中的物体,从而通过实现快速,自动化和客观的物体编码来实现物体分析,从而推进眼动分析的状态。在真实的沉积物上跑步和行走过程中,通过密集的形状捕获来研究足部变形,将有助于阐明步态和人体解剖学的演变,以及赤脚行走和跑步的生物力学。因此,促进新的研究,开发的系统能够快速捕获和构建大型动态高分辨率虚拟环境,复制特定的现实世界环境,包括可变形物体,具有前所未有的细节密度。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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James Hahn其他文献

Hiding in Plain Strokes : Handwriting and Applications to Steganography
隐藏在平淡的笔画中:手写体及其在隐写术中的应用
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Hahn
  • 通讯作者:
    James Hahn
Hiding in plain sight: handwriting and applications to steganography
  • DOI:
  • 发表时间:
    2019-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    James Hahn
  • 通讯作者:
    James Hahn

James Hahn的其他文献

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{{ truncateString('James Hahn', 18)}}的其他基金

Collaborative Research: KEYING SUITE -- A Library of Key Establishment Schemes for Sensor Networks
合作研究:KEYING SUITE——传感器网络密钥建立方案库
  • 批准号:
    0627322
  • 财政年份:
    2007
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant

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