Open AccessAge Estimation and its Progression from Face Images
Author(s) -
Neha Sharma,
Reecha Sharma,
Neeru Jindal
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4414.098319
Subject(s) - estimation , face (sociological concept) , computer science , process (computing) , field (mathematics) , artificial intelligence , feature (linguistics) , feature extraction , computer vision , image (mathematics) , machine learning , pattern recognition (psychology) , mathematics , engineering , sociology , social science , linguistics , philosophy , systems engineering , pure mathematics , operating system
Face model improves the performance of evaluating the accurate age estimation with facial images and has enormous real-world applications. Human aging is a process of growing gradually old and mature. However, it is slow, depends upon person to person and most important it is irreversible. This paper mainly focuses on the various face model techniques, their performance metrics, databases, age estimation challenges to provide the researcher a great knowledge with recent journals in this field. Age estimation process progress with two modules: first part is feature extraction from the image and second module is age estimation. The accuracy or the desired output from age estimation model largely depends upon the features extraction, which if selected appropriately helps to achieve better results for research work.