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A face model is a mathematical representation of the distinct features of ahuman face. Traditionally, face models were built using a set of fiducialpoints 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 offitting the landmarks in a face model to the respective ground truth positionsin an input image containing a face. Despite significant research on facealignment in the past decades, no review analyses various face models used inthe literature. Catering to three types of readers - beginners, practitionersand researchers in face alignment, we provide a comprehensive analysis ofdifferent face models used for face alignment. We include the interpretationand training of the face models along with the examples of fitting the facemodel to a new face image. We found that 3D-based face models are preferred incases of extreme face pose, whereas deep learning-based methods often useheatmaps. Moreover, we discuss the possible future directions of face models inthe field of face alignment.

A survey and classification of face alignment methods based on face models