Leatherbacks Matching by Automated Image Recognition

Authors:
Eric J. Pauwels;Paul M. Zeeuw;Danielle M. Bounantony
Affiliations:
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands;Centrum Wiskunde & Informatica, Amsterdam, The Netherlands;Nicholas School of the Environment and Earth Sciences, Duke University, USA
Venue:
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Year:
2008

Citing 2
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Distinctive Image Features from Scale-Invariant Keypoints

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ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications

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Abstract

We describe a method that performs automated recognition of individual laetherback turtles within a large nesting population. With only minimal preprocessing required of the user, we prove able to produce unsupervised matching results. The matching is based on the Scale-Invariant Feature Transform by Lowe. A strict condition posed by biologists reads that matches should not be missed (no false negatives). A robust criterion is defined to meet this requirement. Results are reported for a considerable sample of leatherbacks.