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

到目前为止，运动捕捉技术受到三大限制。首先，硬件设备受限、繁琐且昂贵。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属性或控制机制。第三，目前的技术未能捕捉到主体与环境之间的相互作用。没有接触的信息，重建由复杂接触现象组成的运动几乎是不可能的。该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。这项新技术将力传感器和单个摄像机相结合，在不受约束的环境中重建全身姿势、关节扭矩和接触力。与昂贵的实验室设备不同，拟议的系统由一双低成本、非侵入性的力传感鞋和一个消费级摄像机组成，可以用来捕捉在实验室很难捕捉到的动作。这项采集技术通过利用大量真实世界的联系数据，实现了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，用于智能和高效的运动规划，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形象来评估所开发的运动控制器。该项目与佐治亚理工学院和德克萨斯A&A；M大学的教育部门紧密结合。该项目的研究很好地帮助自己解决了计算机图形学的重要现实问题。该项目的结果将影响视频游戏、运动训练、远程医疗、两足机器人和虚拟角色等领域的研究。

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.