  We present a new method of primate face recognition, and evaluate this method
on several endangered primates, including golden monkeys, lemurs, and
chimpanzees. The three datasets contain a total of 11,637 images of 280
individual primates from 14 species. Primate face recognition performance is
evaluated using two existing state-of-the-art open-source systems, (i) FaceNet
and (ii) SphereFace, (iii) a lemur face recognition system from literature, and
(iv) our new convolutional neural network (CNN) architecture called PrimNet.
Three recognition scenarios are considered: verification (1:1 comparison), and
both open-set and closed-set identification (1:N search). We demonstrate that
PrimNet outperforms all of the other systems in all three scenarios for all
primate species tested. Finally, we implement an Android application of this
recognition system to assist primate researchers and conservationists in the
wild for individual recognition of primates.
