3D face modeling from single image based on discrete shape space,Computer Animation and Virtual Worlds

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3D face modeling from single image based on discrete shape space
Computer Animation and Virtual Worlds ( IF 0.9 ) Pub Date : 2020-07-01 , DOI: 10.1002/cav.1943
Dan Zhang ₁ , Chenlei Lv ₁ , Na Liu ₁ , Zhongke Wu ₁ , Xingce Wang ₁

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In this article, we propose a novel 3D face modeling method which constructs a new 3D face model from a low‐dimensional feature space consisted of a large set of blend shapes based on the discrete shape space theory. The details of original face features are completely retained during the modeling process and a large number of new natural faces are constructed by several face samples. The optimization process of our method is independently decoupled for different facial attributes (identity, expression, and head pose), which improves the application flexibility and reduces the probability of it falling into a local optimal situation. The new facial data with new attributes are constructed based on the geodesic path search in discrete shape space with sufficient freedom and accuracy. In experiments and applications based on public databases (Helen, LFW, and CUFS), the modeling results show our method can provide high‐quality 3D face model, with enough freedom for face expression editing and natural facial expression animation from a small facial sample set.

中文翻译：

基于离散形状空间的单幅人脸3D建模

在本文中，我们提出了一种新颖的 3D 人脸建模方法，该方法基于离散形状空间理论，从由大量混合形状组成的低维特征空间构建新的 3D 人脸模型。在建模过程中完全保留了原始人脸特征的细节，并通过多个人脸样本构建了大量新的自然人脸。我们方法的优化过程针对不同的面部属性（身份、表情和头部姿势）独立解耦，提高了应用的灵活性，降低了陷入局部最优情况的概率。具有新属性的新人脸数据是基于离散形状空间中的测地线路径搜索构建的，具有足够的自由度和准确性。在基于公共数据库的实验和应用中（Helen,

更新日期：2020-07-01

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