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

提案#：13-37899PI(S)：Hahn，James K.Lee，TaeYoung；Philbeck，John W.；Rickmond，Brian G.；Townsend，Gabe Sibley研究所：乔治华盛顿大学标题：磁共振成像/开发：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，从而集成诸如深度相机(RGB-D传感器)等距离和颜色传感设备。该仪器将在局部区域以至少1厘米的采样分辨率和亚毫米分辨率共同覆盖大空间。然后，这些数据被融合到单一的底层表示中。这项工作涉及开发一种同时具有大规模和实时密集捕获能力的系统。具体地说，-通过实验验证灵活移动机器人(特别是那些使用可变形物体操作的移动机器人)的感知、规划和控制算法需要这些环境的地面真实描述。-验证用于系绳动力学和控制的计算工具需要在大环境中捕获它们的环境。-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在大环境中准确捕获动态变化的可变形人体形状。-图像引导的外科手术需要捕获在更大的外科环境中登记的局部致密的患者解剖表面。-人类的视觉感知和导航需要周围环境的密集模型，包括运动中的对象，因此，通过允许对人们在环境中移动时看到的对象进行快速、自动和客观的编码，从而通过实现对象分析的快速、自动和客观的编码来推进眼部运动分析的状态。-通过在真实沉积物上跑步和行走期间通过密集的形状捕获实现的脚变形的研究将有助于揭示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，为了促进新的研究，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，这些环境以前所未有的细节密度复制特定的真实世界环境，包括可变形对象。

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.