G&V: Medium: Collaborative Research: Contact-Based Human Motion Acquisition and Synthesis

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• 批准号: 1065384
• 负责人: Dilma Da Silva
• 金额: $ 31.86万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065384&HistoricalAwards=false
• 关键词: G& Medium; Collaborative; Research; Contact

To date, motion capture technologies suffer from three major limitations. First, the hardware devices are restrictive, cumbersome, and expensive. Second, most techniques only record the kinematic information of the movement, rather than underlying dynamic properties or control mechanisms. Third, the current technique fails to capture the interaction between the subject and the environment. Without the information of contacts, reconstructing motion that consists of complex contact phenomena is nearly impossible. This project develops a new motion acquisition and reconstruction technique that solves all three problems aforementioned. The new technique combines the force sensors and a single video camera to reconstruct full-body poses, joint torques, and contact forces in an unconstrained setting. In contrast to expensive lab equipment, the proposed system consists of a pair of low-cost, non-intrusive force-sensing shoes and a single consumer-level video camera that can be used to acquire motions difficult to capture in the lab. This acquisition technology enables new design of motion controllers by leveraging a large amount of real-world contact data. The research also develops new data representations and novel algorithms for intelligent and efficient motion planning and evaluates the developed motion controllers by simulating a human figure performing challenging balanced activities in a novel and unpredicted environment. The project is tightly integrated with education components in both Georgia Tech and Texas A&M. The research of this project lends itself well to solve important real-world problems for computer graphics. The results from this project would impact research in video gaming, sports training, remote health care, biped robots, and virtual characters, etc.

迄今为止，运动捕捉技术受到三个主要限制。首先，硬件设备是限制性的、笨重的和昂贵的。其次，大多数技术只记录运动的运动学信息，而不是潜在的动力学特性或控制机制。第三，当前的技术未能捕捉主体与环境之间的交互。没有接触信息，重建由复杂接触现象组成的运动几乎是不可能的。本项目开发了一种新的运动采集和重建技术，解决了上述三个问题。这项新技术结合了力传感器和单个摄像机，可以在不受约束的情况下重建全身姿势、关节扭矩和接触力。与昂贵的实验室设备相比，该系统由一双低成本、非侵入式力传感鞋和一台消费级摄像机组成，可用于获取实验室中难以捕捉的运动。该采集技术通过利用大量真实世界的接触数据来实现运动控制器的新设计。该研究还开发了新的数据表示和新的算法，用于智能和有效的运动规划，并通过模拟在新的和不可预测的环境中执行具有挑战性的平衡活动的人体来评估所开发的运动控制器。该项目与格鲁吉亚理工学院和德克萨斯农工大学的教育部分紧密结合。该项目的研究有助于解决计算机图形学的重要现实问题。该项目的成果将影响视频游戏、运动训练、远程医疗保健、双足机器人和虚拟角色等领域的研究。