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Surface Deformation Models for Nonrigid 3D Shape Recovery

机译:用于非刚性3D形状恢复的表面变形模型

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摘要

Three-dimensional detection and shape recovery of a nonrigid surface from video sequences require deformation models to effectively take advantage of potentially noisy image data. Here, we introduce an approach to creating such models for deformable 3D surfaces. We exploit the fact that the shape of an inextensible triangulated mesh can be parameterized in terms of a small subset of the angles between its facets. We use this set of angles to create a representative set of potential shapes, which we feed to a simple dimensionality reduction technique to produce low-dimensional 3D deformation models. We show that these models can be used to accurately model a wide range of deforming 3D surfaces from video sequences acquired under realistic conditions.
机译:从视频序列对非刚性表面进行三维检测和形状恢复需要变形模型,以有效利用可能带有噪声的图像数据。在这里,我们介绍一种为可变形3D曲面创建此类模型的方法。我们利用这样一个事实,即不可扩展的三角网格的形状可以根据其小平面之间的一小部分角度进行参数化。我们使用这组角度来创建代表性的潜在形状集,然后将其馈入一种简单的降维技术以生成低维3D变形模型。我们展示了这些模型可用于从现实条件下获取的视频序列中准确建模各种变形的3D表面。

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