We introduce a robust optimization method for flip-free distortion energies used, for example, in parametrization, deformation, and volume correspondence. This method can minimize a variety of distortion energies, such as the symmetric Dirichlet energy and our new symmetric gradient energy. We identify and exploit the special structure of distortion energies to employ an operator splitting technique, leading us to propose a novel Alternating Direction Method of Multipliers (ADMM) algorithm to deal with the non-convex, non-smooth nature of distortion energies. The scheme results in an efficient method where the global step involves a single matrix multiplication and the local steps are closed-form per-triangle/per-tetrahedron expressions that are highly parallelizable. The resulting general-purpose optimization algorithm exhibits robustness to flipped triangles and tetrahedra in initial data as well as during the optimization. We establish the convergence of our proposed algorithm under certain conditions and demonstrate applications to parametrization, deformation, and volume correspondence.
翻译:我们引入了一种强大的优化法,用于无翻转扭曲能量,例如在对称、变形和体积通信中使用。这种方法可以最大限度地减少各种扭曲能量,例如对称的狄里赫特能量和我们新的对称梯度能量。我们确定并利用扭曲能量的特殊结构,以使用操作员分裂技术,导致我们提出一种新的乘数转换方向法(ADMM)算法,以处理扭曲能量的非对称、非移动性质。这个办法的结果是一种有效的方法,即全球步骤涉及单一矩阵乘法,而局部步骤是可高度平行的封闭式的每个三角形/每色谱表达式。由此产生的一般用途优化算法显示在初始数据中以及在优化期间,翻转三角形和四希德拉的稳健性。我们在某些条件下将我们提议的算法趋同起来,并展示了对称、变形和量通信的应用。