Open AccessMultiple Face Detection Using Haar - AdaBoosting, LBP-AdaBoosting and Neural Networks
Author(s) -
B. Thirumaleshwari Devi,
Shitharth Selvarajan
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1042/1/012017
Subject(s) - adaboost , artificial intelligence , haar like features , face (sociological concept) , computer science , face detection , pattern recognition (psychology) , artificial neural network , facial recognition system , computer vision , image (mathematics) , object class detection , machine learning , support vector machine , social science , sociology
Multiple Face Detection may be a process of identifying or recognizing quite one face on a picture. Face detections have recently attracted increasing interests thanks to the multitude of applications that end in format. There are numerous methods for identifying the face on the image but here we are using ‘Haar-AdaBoost’, ‘LBP-AdaBoost’, and ‘Neural Networks’ for identifying the faces on the image. And also we are comparing each of the methods to urge which method is giving highly accurate results and which method is giving results very quickly. In humans, by seeing the positions of Eyes, Nose, and Mouth another person can identify the face. The neural mechanism within the brain controls these all and provides the result. We are implementing an equivalent concept on the machine so that the machine can identify the faces by using the positions of the Eyes, Nose, and Mouth. The machine will identify quite one face or multiple faces within the image by using this, and that we also can compare which algorithm will provide a good percentage of accurate results.