AAAI Publications, 2017 AAAI Spring Symposium Series

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Animal Population Censusing at Scale with Citizen Science and Photographic Identification
Jason Remington Parham, Jonathan Crall, Charles Stewart, Tanya Berger-Wolf, Daniel Rubenstein

Last modified: 2017-03-20

Abstract


Population censusing is critical to monitoring the health of an animal population. A census results in a population size estimate, which is a fundamental metric for deciding the demo- graphic and conservation status of a species. Current methods for producing a population census are expensive, demand- ing, and may be invasive, leading to the use of overly-small sample sizes. In response, we propose to use volunteer citizen scientists to collect large numbers of photographs taken over large geographic areas, and to use computer vision algorithms to semi-automatically identify and count individual animals. Our data collection and processing are distributed, non-invasive, and require no specialized hardware and no scientific training. Our method also engages the community directly in conservation. We analyze the results of two population censusing events, the Great Zebra and Giraffe Count (2015) and the Great Grevy’s Rally (2016), where combined we processed over 50,000 photographs taken with more than 200 different cameras and over 300 on-the-ground volunteers.

Keywords


photographic census; photographic estimate; population census; population size estimate; computer vision; detection; identification; deep learning; convolutional neural networks; citizen science; Kenya; plains zebra; Grevy's zebra; Masai giraffe

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