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Published June 28, 2021 | Accepted Version + Published
Book Section - Chapter Open

ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification

Abstract

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.

Additional Information

© 2021 Copyright held by the owner/author(s). We would like to thank the entire team at the Mara Elephant Project for their efforts in deploying this system. This work was supported, through funding, data storage, and computing resources, by Microsoft AI for Earth, the Caltech Resnick Sustainability Institute, and NSF GRFP Grant No. 1745301, the views are those of the authors and do not necessarily reflect the views of these organizations.

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Published - 3460112.3471947.pdf

Accepted Version - 2106.15083.pdf

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Additional details

Created:
August 20, 2023
Modified:
October 23, 2023