PostDoc: Parallel Search Algorithms for Automating the Animation of Human Motion

博士后：用于自动化人体运动动画的并行搜索算法

• 批准号: 9704694
• 负责人: Jessica Hodgins
• 金额: $ 4.62万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2001-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9704694&HistoricalAwards=false
• 关键词: PostDoc; Parallel; Search; Algorithms; Automating

9704694 Hodgins, Jessica K. Georgia Institute of Technology CISE Postdoctoral Research Associates in Experimental CS: Parallel Search Algorithms for Automating the Animation of Human Motion (This award supports CES associate Nancy Pollard.) Realistic simulation of human motion remains an elusive goal. Although recent systems have demonstrated dynamic tasks such as running, cycling, diving, and vaulting, one specific flaw in most current systems is that they cannot automatically adapt to changes in the simulated scenario. The goal of this work is to develop efficient parallel algorithms for adapting biomechanical simulations of human motion to changes in task conditions and to changes in the size and proportions of a moving character. This research will develop scaling laws and search procedures to automate adaptation of simulations to a range of situations. The search techniques will be computationally intensive due to the complexity of modeling and simulating human motion. As one means of addressing this complexity, parallel search algorithms will be implemented and tested on different hardware configurations to gain insight into the effectiveness of various architectures for creating realistic simulations. This research should contribute necessary data for the development of low-cost parallel architectures that will make sophisticated human simulation capabilities widely available to animators and researchers in fields ranging from biomechanics and ergonomics to education and entertainment.

9704694 Hodgins，杰西卡·K·佐治亚理工学院CEISE博士后研究员，实验CS：用于自动化人类运动动画的并行搜索算法(该奖项支持CES研究员南希·波拉德)。逼真地模拟人体运动仍然是一个难以实现的目标。尽管最近的系统已经演示了动态任务，如跑步、骑自行车、跳水和跳跃，但大多数当前系统的一个具体缺陷是它们不能自动适应模拟场景中的变化。这项工作的目标是开发高效的并行算法，使人体运动的生物力学模拟适应任务条件的变化，以及运动角色的大小和比例的变化。这项研究将制定比例定律和搜索程序，以自动调整模拟以适应一系列情况。由于建模和模拟人体运动的复杂性，搜索技术将是计算密集型的。作为解决这种复杂性的一种手段，并行搜索算法将在不同的硬件配置上实施和测试，以深入了解各种架构在创建逼真模拟方面的有效性。这项研究应该为开发低成本的并行体系结构提供必要的数据，使复杂的人类模拟能力广泛适用于从生物力学和人体工程学到教育和娱乐等领域的动画师和研究人员。