Xu Zijian, Chen Hong, Zhu Song-Chun, Luo Jiebo
Moody's Corporation, Wall Street Analytics, San Francisco, CA 94111, USA.
IEEE Trans Pattern Anal Mach Intell. 2008 Jun;30(6):955-69. doi: 10.1109/TPAMI.2008.50.
We present a hierarchical-compositional face model as a three-layer And-Or graph to account for the structural variabilities over multiple resolutions. In the And-Or graph, an And-node represents a decomposition of certain graphical structure expanding to a set of Or-nodes with associated relations; an Or-node functions as a switch variable pointing to alternative And-nodes. Faces are represented hierarchically: layer one treats each face as a whole; layer two refines the local facial parts jointly as a set of individual templates; layer three divides face into 15 zones and models facial features like eyecorners or wrinkles. Transitions between layers are realized by measuring the minimum-description-length given the face image complexity. Diverse face representations are formed by drawing from hierarchical dictionaries of faces, parts and skin features. A sketch captures the most informative part of a face in a concise and potentially robust representation. However, generating good facial sketches is challenging because of the rich facial details and large structural variations, especially in the high-resolution images. The representing power of our generative model is demonstrated by reconstructing high-resolution face images and generating cartoon sketches. Our model is useful for applications such as face recognition, non-photo-realistic rendering, super-resolution, and low-bit rate face coding.
我们提出一种分层组合的人脸模型,它是一个三层的与或图,用于解释多分辨率下的结构变异性。在与或图中,与节点表示某种图形结构的分解,扩展为一组具有关联关系的或节点;或节点用作指向替代与节点的开关变量。人脸以分层方式表示:第一层将每张脸视为一个整体;第二层将局部面部部分联合细化为一组单独的模板;第三层将脸分为15个区域,并对眼角或皱纹等面部特征进行建模。层与层之间的转换通过在给定人脸图像复杂度的情况下测量最小描述长度来实现。通过从人脸、部件和皮肤特征的分层字典中提取信息,形成了多样的人脸表示。草图以简洁且可能稳健的表示方式捕捉人脸最具信息性的部分。然而,由于丰富的面部细节和较大的结构变化,尤其是在高分辨率图像中,生成高质量的面部草图具有挑战性。通过重建高分辨率人脸图像和生成卡通草图,展示了我们生成模型的表示能力。我们的模型可用于人脸识别、非真实感渲染、超分辨率和低比特率人脸编码等应用。