As Symmetric As Possible: Shape Completion with Non-Rigid Registration Leveraging Generalized Cylinder Decomposition

Shuji Oishi, M. Yokozuka, A. Banno
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Abstract

To infer a 3D entire shape from its partial observation, a non-rigid registration algorithm that employs embedded deformations is proposed. We construct a deformation graph on a reference model to discretize the space, and compute a complex deformation as a collection of affine transformations to align the reference model toward the given geometric data. To avoid distortion artifacts during the non-rigid registration, we introduce constraint “As symmetric as possible (ASAP)” on the graph via a generalized cylinder decomposition. ASAP allows model deformation maintaining its underlying local symmetry, which leads to plausible shape completion in the area with no observation. We performed experiments with synthesized data, and demonstrated that the proposed method successfully restored missing surfaces compared with conventional completion techniques.
尽可能对称:利用广义圆柱分解的非刚性配准的形状补全
为了从局部观测推断出三维整体形状,提出了一种利用嵌入变形的非刚性配准算法。我们在参考模型上构造一个变形图来离散空间,并计算一个复杂的变形作为仿射变换的集合,以使参考模型与给定的几何数据对齐。为了避免非刚性配准过程中的畸变,我们通过广义柱面分解在图上引入“尽可能对称(ASAP)”约束。ASAP允许模型变形保持其潜在的局部对称性,从而在没有观测的情况下实现貌似合理的形状完成。利用合成数据进行了实验,结果表明,与传统完井技术相比,该方法成功地恢复了缺失的表面。
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