article

3D face recognition: a survey

Authors:

Sheng XiaoAuthors Info & Claims

Human-centric Computing and Information Sciences, Volume 8, Issue 1

Article No.: 157, Pages 1 - 27

https://doi.org/10.1186/s13673-018-0157-2

Published: 01 December 2018 Publication History

Abstract

3D face recognition has become a trending research direction in both industry and academia. It inherits advantages from traditional 2D face recognition, such as the natural recognition process and a wide range of applications. Moreover, 3D face recognition systems could accurately recognize human faces even under dim lights and with variant facial positions and expressions, in such conditions 2D face recognition systems would have immense difficulty to operate. This paper summarizes the history and the most recent progresses in 3D face recognition research domain. The frontier research results are introduced in three categories: pose-invariant recognition, expression-invariant recognition, and occlusion-invariant recognition. To promote future research, this paper collects information about publicly available 3D face databases. This paper also lists important open problems.

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1. Computing methodologies
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cover image Human-centric Computing and Information Sciences

Human-centric Computing and Information Sciences Volume 8, Issue 1

December 2018

787 pages

ISSN:2192-1962

EISSN:2192-1962

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Copyright © Copyright © 2018 The Author(s).

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Published: 01 December 2018

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https://dl.acm.org/doi/10.5555/3692070.3694657
Fan LHe FSi TFan RYe CLi B(2024)MBA: Backdoor Attacks Against 3D Mesh ClassifierIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.334664419(2127-2142)Online publication date: 1-Jan-2024
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Yuan QGu WWang YYao S(2023)Research and Progress on 3D Face RecognitionProceedings of the 2023 4th International Conference on Computer Science and Management Technology10.1145/3644523.3644558(185-188)Online publication date: 13-Oct-2023
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P.R. SR. B(2023)A two-phase approach for expression invariant 3D face recognition using fine-tuned VGG-16 and 3D-SIFT descriptorsMultimedia Tools and Applications10.1007/s11042-023-14407-z82:15(23873-23890)Online publication date: 21-Feb-2023
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