A face recognition system using off-the-shelf feature extractors and an ad-hoc classier

Face recognition systems are of great interest in many appli- cations. We present some results from a comparison on dierent classi- cation methods using an open source tool that works with Convolutional Neural Networks to extract facial features. This work focuses on the per- formance obtainable from a multi-class classier, trained with a reduced number images, to identify a person between a group of known and un- known subjects . The overall system has been implemented in an Odroid XU-4 Platform.