Lemurs are the world’s most endangered mammals. Analyzing individual lemur movements and
interactions among a group of lemurs is essential for tracking the health of lemur populations. Current
methods for identifying lemurs are limited to capturing and tagging individuals or visually identifying
them via appearance. Tagging individual lemurs is expensive and disruptive to the population both in
terms of causing injury and the possibility of group social dynamic shifts. Visual identification requires
substantial expertise gained over time and produces results which are difficult to generalize.
Automatic facial recognition of humans is a mature technology and has many uses, from unlocking
smartphones to finding suspects in surveillance video. A novel application of this technology, however,
is recognizing other mammalian species. By creating a facial detection and recognition application to
identify lemurs from images, this project will allow for simple and inexpensive tracking of individual lemurs in their habitat. The presence of distinctive facial features among lemurs allows for accurate recognition
by extending and adapting techniques used in human face recognition to the facial anatomy of lemurs.
|Fig. 1 A Red-Bellied Lemur
1. Jacobs, RL, Tecot, SR, Klum, S, Crouse, D, Jain, AK (2014) Developing novel face recognition techniques for population assessments and long-term research of threatened lemurs. International Primatological Society XXV Congress, Hanoi, Vietnam.