ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification
This work addresses the challenge of scalable and non-expert-friendly elephant monitoring for conservation NGOs, though it is incremental as it combines existing methods.
The authors tackled the problem of monitoring elephant populations by developing ElephantBook, a semi-automated human-in-the-loop system for elephant re-identification, which is currently deployed at the Mara Elephant Project to aid conservation efforts.
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.