  African elephants are vital to their ecosystems, but their populations are
threatened by a rise in human-elephant conflict and poaching. Monitoring
population dynamics is essential in conservation efforts; however, tracking
elephants is a difficult task, usually relying on the invasive and sometimes
dangerous placement of GPS collars. Although there have been many recent
successes in the use of computer vision techniques for automated identification
of other species, identification of elephants is extremely difficult and
typically requires expertise as well as familiarity with elephants in the
population. We have built and deployed a web-based platform and database for
human-in-the-loop re-identification of elephants combining manual attribute
labeling and state-of-the-art computer vision algorithms, known as
ElephantBook. Our system is currently in use at the Mara Elephant Project,
helping monitor the protected and at-risk population of elephants in the
Greater Maasai Mara ecosystem. ElephantBook makes elephant re-identification
usable by non-experts and scalable for use by multiple conservation NGOs.
