A face model is a mathematical representation of the distinct features of a human face. Traditionally, face models were built using a set of fiducial points or landmarks, each point ideally located on a facial feature, i.e., corner of the eye, tip of the nose, etc. Face alignment is the process of fitting the landmarks in a face model to the respective ground truth positions in an input image containing a face. Despite significant research on face alignment in the past decades, no review analyses various face models used in the literature. Catering to three types of readers - beginners, practitioners and researchers in face alignment, we provide a comprehensive analysis of different face models used for face alignment. We include the interpretation and training of the face models along with the examples of fitting the face model to a new face image. We found that 3D-based face models are preferred in cases of extreme face pose, whereas deep learning-based methods often use heatmaps. Moreover, we discuss the possible future directions of face models in the field of face alignment.

面部模型是人脸独特特征的数学表示。本文为入门者、从业者和研究人员提供了对用于面部对齐的不同面部模型的全面分析，包括模型的解释和训练，以及将模型拟合到新面部图像的示例。研究发现，在面部极端姿势的情况下，3D模型更受青睐，而基于深度学习的方法通常使用热图。此外，还讨论了面部模型在面部对齐领域的可能未来发展方向。

基于人脸模型的人脸对齐方法调查和分类