Towards an Integrated Method of Detection and Description for Face Authentication System

Abstract

The work in this paper aims to construct a face authentication system based on the deep learning. It is consisted of face detection module, face description system, and retrieval method. Neural network is utilized for both of the detection and description modules as an initial attempt to unify both of the system. In this case, the single shot detection network is utilized as the face detector while the descriptor extractor network is trained by triplet embedding loss function. The proposed system was tested on a novel dataset with several identities to evaluate its robustness. Experiment shows that the result is promising and can be used in a new environment with novel faces without re-training the network.