Real-Time Multi-View Face Recognition using Alignment-RMFRA

5 Pages Posted: 27 Apr 2021

See all articles by Ramya R S

Ramya R S

affiliation not provided to SSRN

Shreelakshmi Yadav N

University Visvesvaraya College of Engineering

Venugopal K R

Bangalore University

S. S. Iyengar

Louisiana State University, Baton Rouge

Patnaik L M

National Institute of Advanced Studies

Date Written: April 25, 2021

Abstract

Face Recognition plays an important role in most of the disciplines in the recent world. One of the most common discipline is security and fraud detection. Facial alignment is a method of arranging the facial landmarks points on the face and those landmarks gives fine points for face recognition. Face detection and identification is important in the fraud detection. Therefore, detection of profile and semi-profile faces plays a vital role in security purpose.The face alignment by utilizing Hourglass model gives better accuracy for face recognition by using Haar- Cascade Classifier can be obtained by facial aligned dataset. The performance is measured by the accuracy rate and precision. It gives better results when compared to face recognition by using Support Vector Machine[SVM] and Principal Component Analysis[PCA]. The model gives alignment of facial points with 68 landmark points and the aligned data is sent as an input for the face recognition. The face alignment and recognition gives most accurate and precise results.

Suggested Citation

R S, Ramya and Yadav N, Shreelakshmi and K R, Venugopal and Iyengar, S. S. and L M, Patnaik, Real-Time Multi-View Face Recognition using Alignment-RMFRA (April 25, 2021). Proceedings of the International Conference on Innovative Computing & Communication (ICICC) 2021, Available at SSRN: https://ssrn.com/abstract=3833799 or http://dx.doi.org/10.2139/ssrn.3833799

Ramya R S

affiliation not provided to SSRN

Shreelakshmi Yadav N (Contact Author)

University Visvesvaraya College of Engineering ( email )

India

Venugopal K R

Bangalore University ( email )

Bangalore, Karnataka 560056
India

S. S. Iyengar

Louisiana State University, Baton Rouge ( email )

Baton Rouge, LA 70803
United States

Patnaik L M

National Institute of Advanced Studies ( email )

Bangalore
India

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