CAREER: Acquiring Computer Graphics Models of Human Shape and Motion

加州大学圣克鲁斯分校的詹姆斯·戴维斯研究人员正在开发一种算法，无需在人体上放置“基准”(即标记)，即可测量出精确到1 mm和1度的人体形状和运动。与以往进行精确人体运动跟踪的努力相比，这项研究的主要进展是用高精度的3D形状测量设备取代了传统的摄像头，并利用精心构建的人体模型。改进的可靠和准确的人体运动测量技术最终将在人体工程学、智能空间、时尚、监控、手术、安全、健康、用户界面和艺术方面实现新的应用。该项目使用两个具体的应用领域来评估科学目标：通过直接测量运动来提高对运动损伤原因和补救措施的认识，并将舞蹈表演作为教育资源。这项研究将人体形状和运动跟踪从优化问题转变为人体形状先验和实时、3D形状测量的问题。这需要精确的3D形状传感器，可以处理移动的对象，并且可以支持多个同时的视点。现有的结构光三角测量和飞行时间传感器不支持这些要求；然而，它们确实具有互补的特性和不足。研究人员研究了两种新的设计，它们结合了这些模式，以实现更高的准确性。该方法需要一个由非常详细和准确的人体表面形状作为姿势和身份函数的模型组成的先验模型。这个模型最初是通过对不同体型、不同姿势的各种人进行全身激光扫描而构建的。当高精度的实时3D数据测量系统完全开发完成时，将捕获更大的训练数据集。数据测量和先前模型的改进将提供一个条件更好的优化空间，具有更少的局部极小值，从而允许更稳健和准确的估计。

AbstractAcquiring Computer Graphics Models of Human Shape and MotionJames Davis, UC Santa CruzThis research is developing algorithms to measure human body shape and motion to 1mm and 1deg accuracy without placing "fiducials" (i.e., markers) on the person's body. The major advances in this research over previous efforts to do accurate human motion tracking are replacing traditional cameras with high accuracy 3D shape measurement devices and utilizing a carefully constructed body model. Improved technology for the reliable and accurate measurement of human movement will ultimately enable new applications in ergonomics, smart spaces, fashion, surveillance, surgery, security, health, user interfaces, and art. The project uses two specific application areas for evaluation of the scientific goals: improving knowledge about the causes and remedies of athletic injuries through direct measurement of motion and archiving dance performances as an educational resource.This research transforms human shape and motion tracking from a problem of optimization to a problem of human shape priors and real-time, 3D shape measurement. This requires 3D shape sensors which are accurate, work with moving subjects, and can support multiple simultaneous viewpoints. Existing structured light triangulation and time-of-flight sensors do not support these requirements; however, they do have complementary qualities and deficiencies. The investigators study two novel designs that combine these modalities to achieve the improved accuracy. The method requires a prior model consisting of a very detailed and accurate model of human surface shape as a function of pose and identity. This model is constructed initially from full body laser scans of a variety of people with different body types in a variety of different poses. When the highly accurate real-time 3D data measurement system has been fully developed, a much larger training data set will be captured. Improvements in data measurement and prior models will provide a better conditioned optimization space with fewer local minima, allowing for more robust and accurate estimation.