3D face recognition: A comprehensive survey in 2022
Yaping Jing, Xuequan Lu, Shang Gao
Abstract
In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as 3D geometric information provides more discriminative features. This comprehensive survey reviews 3D face recognition techniques developed in the past decade, both conventional methods and deep learning methods. These methods are evaluated with detailed descriptions of selected representative works. Their advantages and disadvantages are summarized in terms of accuracy, complexity, and robustness to facial variations (expression, pose, occlusion, etc.). A review of 3D face databases is also provided, and a discussion of future research challenges and directions of the topic.
Topics & Concepts
Facial recognition systemComputer scienceRobustness (evolution)Discriminative modelArtificial intelligenceComputer graphicsFace (sociological concept)Three-dimensional face recognitionFacial expressionMachine learningPattern recognition (psychology)Face detectionChemistryGeneSocial scienceSociologyBiochemistryFace recognition and analysisFace and Expression RecognitionBiometric Identification and Security