论文标题
MINA：用于非刚性形状对齐的凸混合组编程
MINA: Convex Mixed-Integer Programming for Non-Rigid Shape Alignment
论文作者
论文摘要
我们提出了用于非刚性形状匹配的凸混合构成编程公式。为此，我们提出了一个基于有效的低维离散模型的新型形状变形模型，因此在（大多数）实际情况下，找到全球最佳解决方案是可以处理的。我们的方法结合了几种有利的属性：它与初始化无关，与类似的二次分配问题配方相比，求解全球最优性要高得多，并且就可以处理的匹配问题的变异而言，它具有很高的灵活性。在实验上，我们证明我们的方法的表现优于现有的稀疏形状匹配方法，它可用于初始化致密形状匹配的方法，并且在几个示例上展示了其灵活性。
We present a convex mixed-integer programming formulation for non-rigid shape matching. To this end, we propose a novel shape deformation model based on an efficient low-dimensional discrete model, so that finding a globally optimal solution is tractable in (most) practical cases. Our approach combines several favourable properties: it is independent of the initialisation, it is much more efficient to solve to global optimality compared to analogous quadratic assignment problem formulations, and it is highly flexible in terms of the variants of matching problems it can handle. Experimentally we demonstrate that our approach outperforms existing methods for sparse shape matching, that it can be used for initialising dense shape matching methods, and we showcase its flexibility on several examples.
