RUI: Multiple Information Sources for 3D Articulated Pose Tracking

机器人和计算机视觉项目摘要提案编号：0328741标题：RUI：三维关节姿态跟踪的多信息源PI：Howe，NicholasSmith College该项目将致力于研究和开发一个系统，从单个摄像机视频输入中跟踪三维人体运动。 长期以来，在严格控制的环境之外，感知人类活动的有限能力一直阻碍着计算机技术的应用。 通过简单的视频输入，计算机可以学习到周围环境中发生的事件，从而扩大计算机的学习范围，这有可能极大地增加计算机在现实世界中的应用数量。该项目将产生研究见解和新的课程倡议。 当前用于跟踪人体运动的系统要么以某种方式限制域（仅跟踪某些类型的运动，或者在少于三维的维度中），要么缺乏可靠性，随着时间的推移失去对它们的主体的跟踪。 因此，该项目的研究重点旨在通过整合新的反馈来源，包括从轮廓中检索已知姿势，以及基于图形的分割和身体部位识别技术，建立一个具有改进的长期可靠性的通用系统。 该机制将体现一个灵活的贝叶斯框架，允许在制定时纳入更多的跟踪指导组成部分。 一旦建成，跟踪系统将为课程部署提供机会，特别是在锻炼和体育研究中，它可以增加用于人类运动和生物力学研究的工具。 这项工作将增加在各自领域利用运动分析的机会。

Robotics and Computer Vision ProgramABSTRACTProposal #: 0328741Title: RUI: Multiple Information Sources for 3D Articulated Pose TrackingPI: Howe, NicholasSmith CollegeThis project will pursue the research and development of a system to track human motions in three dimensions from single camera video input. A limited ability to sense the activities of humans in their native environment has long inhibited the application of computer technology outside strictly controlled environments. Expanding the range of what computers can learn through simple video input concerning events in their surroundings has the potential to vastly increase the number of applications to real-world situations.The project will yield both research insights and new curricular initiatives. Current systems for tracking human motion either limit the domain in some manner (tracking only certain types of motion, or in fewer than three dimensions) or else lack reliability, losing track of their subjects over time. The research focus of this project therefore aims to build a general system with improved long-term reliability by incorporating novel sources of feedback, including retrieval of known poses from silhouettes, and graph-based techniques for segmentation and body-part identification. The mechanism will embody a flexible Bayesian framework, admitting the inclusion of additional tracking guidance components as they are developed. Once built, the tracking system will offer opportunities for curricular deployment, particularly in exercise and sport studies, where it may augment the tools available for the study of human motion and biomechanics. The work will enhance opportunities in areas utilizing motion analysis in their fields.