Author:
Jing Yaping,Lu Xuequan,Gao Shang
Abstract
AbstractIn 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.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition
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