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Iterative Closest Conformal Maps between Planar Domains

机译:平面域之间的迭代最接近保形映射

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Conformal maps between planar domains are an important tool in geometry processing, used for shape deformation and image warping. The Riemann mapping theorem guarantees that there exists a conformal map between any two simply connected planar domains, yet computing this map efficiently remains challenging. In practice, one of the main algorithmic questions is the correspondence between the boundaries of the domains. On the one hand, there exist a number of conformal maps between any two domains, thus many potential boundary correspondences, yet on the other, given full boundary prescription a conformal map might not exist. Furthermore, an approximate boundary fitting can be enough for many applications. We therefore propose an alternating minimization algorithm for finding a boundary-approximating conformal map given only an initial global alignment of the two input domains. We utilize the Cauchy-Green complex barycentric coordinates to parameterize the space of conformal maps from the source domain, and thus compute a continuous map without requiring the discretization of the domain, and without mapping to intermediate domains. This yields a very efficient method which allows to interactively modify additional user-provided constraints, such as point-to-point and stroke-to-stroke correspondences. Furthermore, we show how to easily generalize this setup to quasi-conformal maps, thus enriching the space of mappings and reducing the area distortion. We compare our algorithm to state-of-the-art methods for mapping between planar domains, and demonstrate that we achieve less distorted maps on the same inputs. Finally, we show applications of our approach to stroke based deformation and constrained texture mapping.
机译:平面域之间的共形图是几何处理中的重要工具,可用于形状变形和图像变形。黎曼映射定理保证了在任何两个简单连接的平面域之间存在共形图,但是有效地计算该图仍然具有挑战性。在实践中,主要的算法问题之一是域边界之间的对应关系。一方面,在任何两个域之间都存在许多共形图,因此存在许多潜在的边界对应关系,但另一方面,给定完整边界处方,可能不存在共形图。此外,对于许多应用而言,近似边界拟合就足够了。因此,我们提出了一种交替最小化算法,该算法仅在两个输入域的初始全局对齐情况下找到边界近似保形图。我们利用Cauchy-Green复杂重心坐标来对源域的共形图的空间进行参数化,从而计算连续图而无需域的离散化,也无需映射到中间域。这产生了一种非常有效的方法,该方法允许交互地修改其他用户提供的约束,例如点对点和笔划与笔划的对应关系。此外,我们展示了如何轻松地将此设置概括为准保形图,从而丰富了映射空间并减少了面积失真。我们将算法与用于平面域之间映射的最新方法进行了比较,并证明了在相同的输入上我们可以获得较少的失真映射。最后,我们展示了我们的方法在基于笔划的变形和受约束的纹理映射中的应用。

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