Face Recognition in Unconstrained Environments: A Comparative Study

Abstract

The development of face recognition methods for unconstrained environments is a challenging problem. The aim of this work is to carry out a comparative study of existing face recognition methods that are suitable to work properly in these environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to be real-time, to require just one image per person, and to be fully online (no requirements of offline enrollment). The methods are compared using the LFW database, which was built to evaluate face recognition methods in real-world conditions. The results of this comparative study are intended to be a guide for developers of face recognition systems.