Open AccessA FACIAL RECOGNITION USING OPEN COMPUTER VISION
Author(s) -
Dr.C K Gomathy,
T. S. Suneel,
Y.Jeeevan Kumar Reddy
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v05i12.056
Subject(s) - facial recognition system , artificial intelligence , eigenface , computer science , computer vision , biometrics , principal component analysis , pattern recognition (psychology) , three dimensional face recognition , face recognition grand challenge , python (programming language) , face (sociological concept) , face detection , social science , sociology , operating system
The Face recognition and image or videorecognition are popular research topics in biometrictechnology. Real-time face recognition is an exciting fieldand a rapidly evolving issue. Key component analysis(PCA) may be a statistical technique collectively calledcorrelational analysis . The goal of PCA is to scale back themassive amount of knowledge storage to the dimensions ofthe functional space required to render the facerecognition system. The wide one-dimensional pixel vectorgenerated from the two-dimensional image of the face andtherefore the basic elements of the spatial function aredesigned for face recognition using PCA. this is often theprojection of your own space. Sufficient space is decidedby the brand. specialise in the eigenvectors of thecovariance matrix of the fingerprint image collection. i'mbuilding a camera-based real-time face recognition systemand installing an algorithm. Use OpenCV, Haar Cascade,Eigen face, Fisher Face, LBPH and Python for programdevelopment.