CHS: Small: Highly Realistic Virtual Human Hands using Anatomically Based Modeling

人类手的骨骼由27块骨头组成，包括8块短腕骨。由于难以获取内部手部解剖结构的“稳定”（没有手部运动）数据以及难以获取用于识别所捕获的解剖图像中的骨骼的分割算法，人手建模的当前技术水平仅支持人手的近似版本。计算机断层扫描（CT）扫描用有害的辐射照射手部，并且没有对比度来显示除骨骼以外的任何解剖结构。磁共振成像（MRI）扫描仪可以提供内部解剖结构，但采集是困难的，因为手必须保持静止在MRI扫描仪内，因为质量扫描会话很长（约10分钟）。该项目的目标是大大提高人手的建模，仿真和动画。这些模型在许多领域都很有用。在计算机图形、虚拟现实、电信和电影中，它们可以实现更好、更可信的虚拟手，增强沉浸式体验。精确的手模型可用于设计必须用手操作的工具、设备和日常物品。在医疗保健方面，他们改进了与手接触的医疗设备的设计。在服装行业，它们使人们能够设计出更好的手套。 这些计算机模型还可以改进用于医疗假肢的机器人手的设计，使带有人造骨骼和肌肉的人造手能够像真实的生物手一样运动和变形。该项目将开发一种稳定的方法来获取手部内部解剖结构（骨骼，肌肉，脂肪）在多个手部姿势使用MRI扫描仪，通过制造人体工程学的刚性模具，在扫描期间将手保持在固定和已知的姿势。真实的骨骼不会简单地围绕另一个骨骼末端的某个旋转中心旋转，而是相对于其父骨骼进行复杂的刚体运动。利用获得的骨骼刚体运动，研究小组将开发新的方法来模拟这种复杂的刚体运动，使用新的数据驱动和基于模型的技术。然后应用基于有限元方法（FEM）的模拟来将所获得的姿态变化的肌肉和脂肪/皮肤形状联合收割机组合。这些进步使得能够对手部的详细表面外观进行逼真的建模，该建模与地面实况表面扫描相匹配并且概括为任意手部姿势。然后，研究小组将建立一个计算机模型，用于研究当人类手部关节连接时，手部的骨骼和肌肉如何移动。考虑到在几个姿势中手部的三维表面扫描，研究小组还将使用计算机模拟来“填充”扫描姿势中的遮挡（发生在闭合的手，拳头姿势等）。这个程序将创建一个内部的手解剖和外部的手appearance.This奖项的计算机模型反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

The skeleton of the human hand consists of 27 bones, including 8 short carpel bones. Current state-of-the-art in human hand modeling only supports an approximate version of human hand because of the difficulty in acquiring a "stable" (without hand movements) data of the internal hand anatomy, as well in segmentation algorithms for identifying bones in the captured anatomical images. Computed Tomography (CT) scans irradiate the hand with harmful radiation and do not have the contrast to show any anatomy other than bones. Magnetic Resonance Imaging (MRI) scanners can provide internal anatomy, but the acquisition is difficult because the hand must be kept still inside the MRI scanner and because a quality scanning session is long (about 10 minutes). The goal of this project is to greatly improve the modeling, simulation and animation of human hands. Such models are useful in many fields. In computer graphics, virtual reality, telecommunication and film, they enable better, more believable virtual hands, enhancing the immersive experience. Accurate hand models can be used to design tools, equipment and everyday objects that must be manipulated by hands. In healthcare, they improve the design of medical devices that come in contact with hands. In the apparel industry, they enable one to design better gloves. These computer models can also improve the design of robotic hands for medical prosthetics, enabling the artificial hands with artificial bones and muscles to move and deform like their real biological counterparts.The project will develop a stable method to acquire hand internal anatomy (bones, muscles, fat) in multiple hand poses using MRI scanners, by manufacturing ergonomic rigid molds that hold the hand in a fixed and known pose during the scan. Real bones do not simply rotate around some center of rotation at the end of another bone, but instead undergo complex rigid body motion relative to their parent bones. Using the acquired bone rigid body motion, the research team will develop new methods to model this complex rigid motion, using novel data-driven and model-based techniques. Finite Element Methods (FEM) based simulations are then applied to combine acquired pose-varying muscle and fat/skin shapes. These advances enable realistic modeling of detailed surface appearance of hands that matches ground truth surface scans and that generalizes to arbitrary hand poses. The research team will then build a computer model for how the bones and muscles of the human hand move when the hand is articulated. Given the three-dimensional surface scans of the hand in a few poses, the research team also will use computer simulation to "fill-in" occlusions in scanned poses (occurring in a closed hand, fist pose and similar). This procedure will create a computer model of both the internal hand anatomy and the external hand appearance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.