Abstract
3D morphable models are widely used to describe the variation of human body shapes. However, these models typically focus on the surface of the human body, since the acquisition of the volumetric interior would require prohibitive medical imaging. In this paper we present a novel approach for creating a volumetric body template and for fitting this template to the surface scan of a person in a just a few seconds. The body model is composed of three surface layers for bones, muscles, and skin, which enclose the volumetric muscle and fat tissue in between them. Our approach includes a data-driven method for estimating the amount of muscle mass and fat mass from a surface scan, which provides more accurate fits to the variety of human body shapes compared to previous approaches. We also show how to efficiently embed fine-scale anatomical details, such as high resolution skeleton and muscle models, into the layered fit of a person. Our model can be used for physical simulation, statistical analysis, and anatomical visualization in computer animation and medical applications, which we demonstrate on several examples.
Highlights
IntroductionThey can be found in movies, computer games, and commercials
Virtual humans are present in our everyday lives
We compared the linear model to a support vector regression (using scikit-learn (Pedregosa et al, 2011) with default parameters and radial basis functions (RBFs) kernels), but in contrast to Hasler et al (2009) we found that for the BeyondBMI dataset this approach performs considerably worse: MAEFM 2.98 kg (± 2.85) and MAEMM 1.24 kg (± 1.02) with an average R2 score of 0.64 for the female dataset, and MAEFM 2.63 kg (± 2.60) and MAEMM 2.48 kg (± 1.82) with an average R2 score of 0.58 for the male dataset
Summary
They can be found in movies, computer games, and commercials They are employed in a rapidly growing number of applications in virtual reality (VR) and augmented reality (AR), even ranging to computational medicine. For the purpose of creating convincing animations of and interactions with those models, large amounts of 3D captured data have been collected to build sophisticated surface-based models (Anguelov et al, 2005; Loper et al, 2015; Bogo et al, 2017) Those models compensate for the fact that humans are not empty hulls or homogeneous solids by capturing and analyzing more and more data of that surface hull. While surface-based models might be sufficient for many applications, for others (e.g., surgery simulation) a volumetric model is an essential prerequisite
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