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1. 发明申请

WO2016207311A1 SKINNED MULTI-PERSON LINEAR MODEL 审中-公开
标题翻译：皮肤多人线性模型
公开(公告)号：WO2016207311A1
公开(公告)日：2016-12-29
申请号：PCT/EP2016/064610
申请日：2016-06-23
申请人： MAX-PLANCK-GESELLSCHAFT ZUR FÖRDERUNG DER WISSENSCHAFTEN E.V.
发明人： BLACK, Michael J. , LOPER, Matthew , MAHMOOD, Naureen , PONS-MOLL, Gerard , ROMERO, Javier
IPC分类号： G06T13/40 , G06T19/20
CPC分类号： G06T13/40 , G06T19/20 , G06T2219/2021
摘要： The invention comprises a learned model of human body shape and pose dependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines. Our Skinned Multi-Person Linear model (SMPL) is a skinned vertex based model that accurately represents a wide variety of body shapes in natural human poses. The parameters of the model are learned from data including the rest pose template, blend weights, pose-dependent blend shapes, identity- dependent blend shapes, and a regressor from vertices to joint locations. Unlike previous models, the pose-dependent blend shapes are a linear function of the elements of the pose rotation matrices. This simple formulation enables training the entire model from a relatively large number of aligned 3D meshes of different people in different poses. The invention quantitatively evaluates variants of SMPL using linear or dual- quaternion blend skinning and show that both are more accurate than a Blend SCAPE model trained on the same data. In a further embodiment, the invention realistically models dynamic soft-tissue deformations. Because it is based on blend skinning, SMPL is compatible with existing rendering engines and we make it available for research purposes.
摘要翻译：本发明包括人体形状和姿态依赖形状变化的学习模型，其比先前的模型更准确，并且与现有的图形管线兼容。我们的皮肤多人线性模型（SMPL）是一种皮肤顶点的模型，可以准确表示自然人类姿势中各种身体形状。从包括其余姿态模板，混合权重，姿势依赖混合形状，身份相关混合形状以及从顶点到联合位置的回归的数据中学习模型的参数。与以前的模型不同，姿势依赖的混合形状是姿态旋转矩阵的元素的线性函数。这种简单的配方可以从不同人物的不同人物的相对大量对齐的3D网格中训练整个模型。本发明使用线性或双四元数混合蒙皮定量评估SMPL的变体，并且显示两者比在相同数据上训练的混合SCAPE模型更准确。在另一实施例中，本发明实际上对动态软组织变形进行建模。因为它是基于混合蒙皮，SMPL与现有的渲染引擎兼容，我们使其可用于研究目的。

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