Location of Repository

Artificial Neural Networks and Gene Expression Programing based age estimation using facial features

By Baddrud Z. Laskar, Ashutosh and Swanirbhar Majumder

Abstract

This work is about estimating human age automatically through analysis of facial images. It has got a lot of real-world applications. Due to prompt advances in the fields of machine vision, facial image processing, and computer graphics, automatic age estimation via faces in computer is one of the dominant topics these days. This is due to widespread real-world applications, in areas of biometrics, security, surveillance, control, forensic art, entertainment, online customer management and support, along with cosmetology. As it is difficult to estimate the exact age, this system is to estimate a certain range of ages. Four sets of classifications have been used to differentiate a person’s data into one of the different age groups. The uniqueness about this study is the usage of two technologies i.e., Artificial Neural Networks (ANN) and Gene Expression Programing (GEP) to estimate the age and then compare the results. New methodologies like Gene Expression Programing (GEP) have been explored here and significant results were found. The dataset has been developed to provide more efficient results by superior preprocessing methods. This proposed approach has been developed, tested and trained using both the methods. A public data set was used to test the system, FG-NET. The quality of the proposed system for age estimation using facial features is shown by broad experiments on the available database of FG-NET

Topics: Neural networks, Neurons, Gene Expression Programing, Chromosomes, Age estimation, Electronic computers. Computer science, QA75.5-76.95
Publisher: Elsevier
Year: 2015
DOI identifier: 10.1016/j.jksuci.2014.06.017
OAI identifier: oai:doaj.org/article:4627ec6dfef64a09b3e3223f87939a46
Journal:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://doaj.org/toc/1319-1578 (external link)
  • http://www.sciencedirect.com/s... (external link)
  • https://doaj.org/article/4627e... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.