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

• URL: http://arxiv.org/abs/2311.03082v1
• Date: Mon, 6 Nov 2023 13:09:04 GMT
• Title: A survey and classification of face alignment methods based on face models
• Authors: Jagmohan Meher, Hector Allende-Cid and Torbj\"orn E. M. Nordling
• Abstract summary: 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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