School of Mathematical Science, Dalian University of Technology, Dalian 116024, China.
College of Information Science and Technology, Dalian Maritime University, Dalian 116024, China.
Sensors (Basel). 2021 Feb 8;21(4):1187. doi: 10.3390/s21041187.
Canonical extrinsic representations for non-rigid shapes with different poses are preferable in many computer graphics applications, such as shape correspondence and retrieval. The main reason for this is that they give a pose invariant signature for those jobs, which significantly decreases the difficulty caused by various poses. Existing methods based on multidimentional scaling (MDS) always result in significant geometric distortions. In this paper, we present a novel shape unfolding algorithm, which deforms any given 3D shape into a canonical pose that is invariant to non-rigid transformations. The proposed method can effectively preserve the local structure of a given 3D model with the regularization of local rigid transform energy based on the shape deformation technique, and largely reduce geometric distortion. Our algorithm is quite simple and only needs to solve two linear systems during alternate iteration processes. The computational efficiency of our method can be improved with parallel computation and the robustness is guaranteed with a cascade strategy. Experimental results demonstrate the enhanced efficacy of our algorithm compared with the state-of-the-art methods on 3D shape unfolding.
在许多计算机图形应用中，例如形状对应和检索，具有不同姿势的非刚性形状的规范外在表示形式是更好的。主要原因是它们为这些任务提供了一个不变的姿势签名，这显著降低了各种姿势造成的困难。基于多维尺度（MDS）的现有方法总是导致显著的几何变形。在本文中，我们提出了一种新颖的形状展开算法，该算法将任何给定的 3D 形状变形为对非刚性变换不变的规范姿势。所提出的方法可以通过基于形状变形技术的局部刚性变换能量的正则化来有效地保持给定 3D 模型的局部结构，并大大减少几何变形。我们的算法非常简单，在交替迭代过程中只需要求解两个线性系统。我们的方法的计算效率可以通过并行计算来提高，并且可以通过级联策略来保证稳健性。实验结果表明，与 3D 形状展开的最新方法相比，我们的算法具有增强的效果。
