Acquisition and Modeling of Non-Rigid Shape and Deformation

非刚性形状和变形的采集和建模

• 批准号: 0541227
• 负责人: Jovan Popovic
• 金额: --
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-15 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0541227&HistoricalAwards=false
• 关键词: Acquisition; Modeling; Non; Rigid; Shape

Acquisition and Modeling of Non-Rigid Shape and DeformationThe acquisition of three-dimensional digital replicas of real-word objects enables digital archiving, virtual restoration, simulation, medicine, education, reverse engineering, and many other applications. The recent success of the efforts to digitize sculptures by Michelangelo, the Florentine Pieta, and artifacts in Cairo's Egyptian Museum demonstrate that the technical challenges involved in scanning static, rigid objects have been largely solved. However, the same scanning technology is far less effective for numerous applications requiring digitization of non-rigid, deforming objects, including humans, animals, and the environment. For example, the state-of-the-art scanners today require human patients to remain motionless in a single pose for several seconds even though infants, small children, and people with disabilities may find it difficult to remain still for the required time periods. More fundamentally, the key drawback of present-day scanning technology is that a single, static scan of a deformable object is a poor representation of its shape because human and animal shapes can easily change at any time instant.This research tackles the algorithmic challenges in acquiring moving three-dimensional shapes. Using high-speed depth cameras to acquire real-time range images allows the object to change freely throughout the scanning process and in the process reveal its entire shape, including the usually occluded regions. The acquired range images are then automatically processed to compute temporal correspondence between data points in nearby frames; to reverse the motion of these data points; and to reconstruct the moving three-dimensional shape in its entirety by aggregating partial information from each time frame. These algorithms simplify acquisition of non-rigid shapes and enable new applications such as studies of locomotion development in humans and animals and content creation for education and training.

非刚性形状和变形的获取和建模获取真实世界对象的三维数字复制品使数字存档、虚拟修复、模拟、医学、教育、逆向工程和许多其他应用成为可能。最近，米开朗基罗的雕塑、佛罗伦萨的皮埃塔和开罗埃及博物馆的文物数字化的努力取得了成功，这表明扫描静态、刚性物体所涉及的技术挑战在很大程度上已经得到解决。然而，同样的扫描技术对于许多需要数字化的非刚性、变形对象，包括人类、动物和环境的应用来说，效率要低得多。例如，今天最先进的扫描仪要求人类患者在单一姿势下保持不动几秒钟，即使婴儿、幼儿和残疾人可能发现很难在所需的时间段内保持静止。更根本的是，目前扫描技术的主要缺陷是对可变形物体的单一静态扫描不能很好地表示其形状，因为人和动物的形状很容易在任何时刻改变。这项研究解决了获取运动三维形状的算法挑战。使用高速深度相机获取实时距离图像，允许对象在整个扫描过程中自由变化，并在此过程中显示其整个形状，包括通常被遮挡的区域。然后自动处理所获取的距离图像，以计算相邻帧中的数据点之间的时间对应；反转这些数据点的运动；以及通过聚集来自每个时间帧的部分信息来重建运动的三维形状的整体。这些算法简化了非刚性形状的获取，并使新的应用成为可能，例如研究人类和动物的运动发育，以及为教育和培训创建内容。