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Identifying individual snow leopards from camera trap images
Author(s): Agnieszka Miguel; Rana Bayrakçismith; Eddy Ferre; Chleo Bales-Heisterkamp; Joshua Beard; Matt Dioso; David Grob; Ross Hartley; Tim Nguyen; Noah Weller
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Paper Abstract

Conservation biologists use camera traps to study snow leopards. In this research, we introduce a method that streamlines the process of recognizing individual snow leopards in a large camera trap study. The proposed solution is based on an open-source software called HotSpotter, which was originally developed to identify uniquely patterned animals, such as Grevy’s zebras. The legacy HotSpotter involves time-consuming tasks such as manual selection of a region of interest (ROI) within each image, manual querying of each individual image against a database, and manual interpretation of results of each query to arrive at an estimate of a population count in a camera trap study. We introduce autonomous selection of multiple ROIs in motion templates corresponding to camera trap images, automate the query process, and propose a method to build associations between individual ROIs based on clustering of similarity scores using Markov Clustering Algorithm. The proposed technique with its promising results of correctly recognizing individual snow leopards has the potential to save conservation biologists thousands of hours of manual labor.

Paper Details

Date Published: 17 April 2019
PDF: 5 pages
Proc. SPIE 11071, Tenth International Conference on Signal Processing Systems, 110710O (17 April 2019); doi: 10.1117/12.2521856
Show Author Affiliations
Agnieszka Miguel, Seattle Univ. (United States)
Rana Bayrakçismith, Panthera Corp. (United States)
Eddy Ferre, Seattle Univ. (United States)
Chleo Bales-Heisterkamp, Seattle Univ. (United States)
Joshua Beard, Seattle Univ. (United States)
Matt Dioso, Seattle Univ. (United States)
David Grob, Seattle Univ. (United States)
Ross Hartley, Seattle Univ. (United States)
Tim Nguyen, Seattle Univ. (United States)
Noah Weller, Seattle Univ. (United States)


Published in SPIE Proceedings Vol. 11071:
Tenth International Conference on Signal Processing Systems
Kezhi Mao; Xudong Jiang, Editor(s)

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