Fisherface is one of the popular algorithms used in face recognition, and is widely believed to be superior to other techniques, such as eigenface because of the effort to maximize the separation between classes in the training process.
Published in Chapter:
Surveillance of Age and Gender With ML: A Knowledge Based Statistical Analysis for Next Gen Software Products
Rohit Rastogi (ABES Engineering College, India), Mayank Gupta (Eli Lilly and Company, India),
Kaushlendra Gupta (ABES Engineering College, India), and Saumya Kulpriya (HCL Technologies, Noida, India)
Copyright: © 2024
|Pages: 23
DOI: 10.4018/979-8-3693-1082-3.ch012
Abstract
Gender and age classification is a major role for many purposes in the world. Humans have god-gifted facilities to recognize any gender and their age, but they cannot notice all the people, so the author team has trained the machine to work at those which are not capable of recognizing by simply seeing the people. Nowadays, the age and gender classification have a major role in the market, surveillance, security, etc. This research work for age and gender detection is different from the other project for facial recognition. As in this research, fisherface algorithm has been used which is very easy and accurate, and which simply works on the basis of facial recognition. The authors have used an audience dataset which is today's most demanding dataset as it is a self-updated dataset, and easily available on the open source. It basically depends on the deep learning in which openCv is used for the implementation of the given algorithm and dataset. As it does not require any complex calculations to recognize the faces, it is very fast and easy to use as compared to the other projects.