A Data-driven Approach to Human-body Cloning Using a Segmented Body Database

P. Xi, Won-Sook Lee, Chang Shu
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引用次数: 23

Abstract

We present a data-driven approach to build a human body model from a single photograph by performing Principal Component Analysis (PCA) on a database of body segments. We segment a collection of human bodies to compile the required database prior to performing the analysis. Our approach then builds a single PCA for each body segment - head, left and right arms, torso and left and right legs - yielding six PCAs in total. This strategy improves on the flexibility of conventional data-driven approaches in 3D modeling and allows our approach to take variations in ethnicity, age and body posture into account. We demonstrate our approach in practice by constructing models of a Caucasian male, an Asian male and a toddler from corresponding photographs and a Caucasian adult oriented database. We also discuss rapid consistent parameterization based on Radial Basis Functions (RBF) and non-optimization based learning systems to reduce execution time.
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基于数据驱动的分段人体数据库人体克隆方法
我们提出了一种数据驱动的方法,通过对人体片段数据库进行主成分分析(PCA),从单张照片构建人体模型。在进行分析之前,我们对人体的集合进行分段,以编译所需的数据库。然后,我们的方法为每个身体部分——头部、左右手臂、躯干、左右腿——构建一个单一的PCA,总共产生6个PCA。这种策略提高了3D建模中传统数据驱动方法的灵活性,并允许我们的方法考虑种族、年龄和身体姿势的变化。我们在实践中展示了我们的方法,通过从相应的照片和以白人成人为导向的数据库中构建白种人男性、亚洲男性和幼儿的模型。我们还讨论了基于径向基函数(RBF)的快速一致参数化和基于非优化的学习系统,以减少执行时间。
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