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arXiv · 2311.03082

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

Jagmohan Meher·Hector Allende-Cid·Torbjörn E. M. Nordling
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Abstract

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.

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Jagmohan Meher, Hector Allende-Cid, Torbjörn E. M. Nordling. 2023-11-06. A survey and classification of face alignment methods based on face models. https://arxiv.org/abs/2311.03082

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