Age estimation via face images: a survey

Facial aging adversely impacts performance of face recognition and face verification and authentication using facial features. This stochastic personalized inevitable process poses dynamic theoretical and practical challenge to the computer vision and pattern recognition community. Age estimation is...

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Bibliographic Details
Published in:EURASIP journal on image and video processing 2018-06, Vol.2018 (1), p.1-35, Article 42
Main Authors: Angulu, Raphael, Tapamo, Jules R., Adewumi, Aderemi O.
Format: Article
Language:English
Subjects:
Age
Age estimation
Anthropometry
Biometrics
Chronology
Classification
Communities
Computer vision
Engineering
Face
Face recognition
Feature
Image Processing and Computer Vision
Invariants
Object recognition
Pattern Recognition
Review
Signal,Image and Speech Processing
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Summary:Facial aging adversely impacts performance of face recognition and face verification and authentication using facial features. This stochastic personalized inevitable process poses dynamic theoretical and practical challenge to the computer vision and pattern recognition community. Age estimation is labeling a face image with exact real age or age group. How do humans recognize faces across ages? Do they learn the pattern or use age-invariant features? What are these age-invariant features that uniquely identify one across ages? These questions and others have attracted significant interest in the computer vision and pattern recognition research community. In this paper, we present a thorough analysis of recent research in aging and age estimation. We discuss popular algorithms used in age estimation, existing models, and how they compare with each other; we compare performance of various systems and how they are evaluated, age estimation challenges, and insights for future research.
ISSN:1687-5281
1687-5176
1687-5281
DOI:10.1186/s13640-018-0278-6