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

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.