CAREER: Motion Capture from Movies: Video-Based Tracking and Modeling of Human Motion

职业：电影动作捕捉：基于视频的人体动作跟踪和建模

• 批准号: 0133779
• 负责人: James Rehg
• 金额: $ 37万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2007-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0133779&HistoricalAwards=false
• 关键词: CAREER; Motion; Capture; Movies; Video

The project addresses the issues of tracking and modeling of human motion. Robust tracking algorithms will be developed that do not require manual initialization and are capable of tracking over many frames without failure. These trackers will then be applied to archival video footage, to produce a rich corpus of historically-significant motion data. A combination of manual labeling, state invariant detection, and temporal co-occurrence analysis will be utilized to parse motions into sequences of movements. The generated library of learned motions can then be applied to a diverse set of applications, including robot control and computer animation. The education part of the project calls for development of a curriculum for figure tracking and motion modeling that is self-contained and accessible to students and researchers in the areas of computer vision, robotics, computer graphics, and biomechanics. An outreach program will be initiated that will target the machine learning and computer animation communities.

该项目解决了人体运动的跟踪和建模问题。将开发强大的跟踪算法，不需要手动初始化，并能够跟踪许多帧没有失败。这些跟踪器将被应用于档案视频片段，以产生丰富的历史重要的运动数据语料库。将利用手动标记、状态不变检测和时间共现分析的组合来将运动解析成运动序列。然后，生成的学习运动库可以应用于各种应用，包括机器人控制和计算机动画。该项目的教育部分要求开发图形跟踪和运动建模课程，该课程是独立的，可供计算机视觉，机器人技术，计算机图形学和生物力学领域的学生和研究人员使用。将启动一项针对机器学习和计算机动画社区的推广计划。