Face sketch synthesis (FSS) plays an important role in facial entertainment, which includes face sketch morphing among two styles, multiview FSS and face sketch expression manipulation. For facial entertainment, most existing FSS methods generate sketches with over-smoothing effects, i.e., fine details are suppressed more or less. In this paper, we propose a face sketch generator based on the compositional model to handle this issue. It decomposes a face into different components instead of patches as before, and each component has several candidate templates. Multilevel B-spline approximation is utilized to delicately polish the chosen templates of all components. To fuse these components, Poisson blending is employed instead of the weighted average operator. The proposed compositional method crucially reduces the high frequency loss and improves the synthesis performance in comparison to the state-of-the-art methods. Experiments on face sketch morphing, expression manipulation, and multiview FSS, make further efforts to demonstrate the effectiveness of the proposed method.

中文翻译：

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面部娱乐中基于成分模型的草图生成器

面部素描合成（FSS）在面部娱乐中起着重要作用，其中包括两种样式之间的面部素描变形，多视图FSS和面部素描表情操纵。对于面部娱乐，大多数现有的FSS方法生成具有过度平滑效果的草图，即，或多或少地抑制了精细的细节。在本文中，我们提出了一种基于构图模型的人脸素描生成器来解决此问题。它将面部分解为不同的组件，而不是像以前那样将其分解，并且每个组件都有几个候选模板。利用多级B样条逼近来精细抛光所有组件的所选模板。为了融合这些组件，采用泊松混合代替加权平均算子。与最先进的方法相比，所提出的合成方法可显着降低高频损耗并提高合成性能。有关面部素描变形，表情操纵和多视图FSS的实验，进一步证明了该方法的有效性。