Local Feature Methods Based Facial Recognition

Abstract

In both business and academics, 3D face recognition is a hot topic. This technology's wide range of uses and the natural recognition procedure make traditional 2D face recognition a superior choice. Additionally, 3D face recognition systems are able to successfully identify human faces even in low light and with varying facial postures and expressions, while 2D face recognition systems would have a tough time operating in these settings. Attempting to recognize faces based on their statistical distribution is pointless. Local traits may be used to identify these faces, though. It is hypothesized here that local feature-based face recognition may be achieved by acquiring local features and their dimensions.