首页> 外文会议>Scale Space and Variational Methods in Computer Vision; Lecture Notes in Computer Science; 4485 >Beauty with Variational Methods: An Optic Flow Approach to Hairstyle Simulation
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Beauty with Variational Methods: An Optic Flow Approach to Hairstyle Simulation

机译:多种方法的美:发型模拟的光流方法

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Although variational models offer many advantages in image analysis, their successful application to real-world problems is documented only for some specific areas such as medical imaging. In this paper we show how well-adapted variational ideas can solve the problem of hairstyle simulation in a fully automatic way: A customer in a hairdresser's shop selects a new hairstyle from a database, and this hairstyle is automatically registered to a digital image of the customer's face. Interestingly already a carefully modified optic flow method of Horn and Schunck turns out to be ideal for this application. These modifications include an extension to colour sequences, an incorporation of warping ideas in order to allow large deformation rates, and the inclusion of shape information that is characteristic for human faces. Employing classical numerical ideas such as finite differences and SOR iterations offers sufficient performance for real-life applications. In a number of experiments we demonstrate that our variational approach is capable of solving the hairstyle simulation problem with high quality in a fully practical setting.
机译:尽管变分模型在图像分析中提供了许多优势,但仅针对某些特定领域(例如医学成像)记录了它们在现实世界中的成功应用。在本文中,我们展示了适应性强的变式想法如何以全自动方式解决发型模拟问题:美发店中的客户从数据库中选择新发型,并且该发型会自动注册到该发型的数字图像中客户的脸。有趣的是,经过仔细修改的Horn和Schunck光学流动方法已证明是此应用程序的理想选择。这些修改包括对颜色序列的扩展,为了允许较大的变形率而合并了变形思想,以及包含了人脸特有的形状信息。采用诸如有限差分和SOR迭代之类的经典数值方法可为实际应用提供足够的性能。在许多实验中,我们证明了我们的变分方法能够在完全实际的环境中以高质量解决发型模拟问题。

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