Integral Curvature Representation and Matching Algorithms for Identification of Dolphins and Whales
By Hendrik J. Weideman, Zachary M. Jablons, Jason A. Holmberg, Kiirsten Flynn, John Calambokidis, Reny B. Tyson, Jason B. Allen, Randall S. Wells, Krista Hupman, K. Urian and 1 more. 2017
43 citations recorded by the source corpus.
We address the problem of identifying individual cetaceans from images showing the trailing edge of their fins. Given the trailing edge from an unknown individual, we produce a ranking of known individuals from a database. The nicks and notches along the trailing edge define an individual's unique signature. We define a representation based on integral curvature that is robust to changes in viewpoint and pose, and captures the pattern of nicks and notches in a local neighborhood at multiple scales. We explore two ranking methods that use this representation. The first uses a dynamic programming time-warping algorithm to align two representations, and interprets the alignment cost as a measure of similarity. This algorithm also exploits learned spatial weights to downweight matches from regions of unstable curvature. The second interprets the representation as a feature descriptor. Feature keypoints are defined at the local extrema of the representation. Descriptors for the set of known individuals are stored in a tree structure, which allows us to perform queries given the descriptors from an unknown trailing edge. We evaluate the top-k accuracy on two real-world datasets to demonstrate the effectiveness of the curvature representation, achieving top-1 accuracy scores of approximately 95% and 80% for bottlenose dolphins and humpback whales, respectively.
Subfields: Computer Vision and Pattern Recognition, Ecology, Oceanography, Algorithms & Complexity
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In Computer Vision and Pattern Recognition
- Per Berggren
- Georgia Atkinson
- Cameron Trotter
- Kirsten Richardson
- Nick Wright
- Stephen Mcgough
- Matt Sharpe
- Ben Burville
In Ecology
- Per Berggren
- Georgia Atkinson
- Cameron Trotter
- Kirsten Richardson
- Nick Wright
- Stephen Mcgough
- Matt Sharpe
- Ben Burville
Citations in the corpus
- NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation (2020, methodology): “As such it is believed that an automated photo-id process is achievable using computer vision (19), with work already beginning in this area (3, 5, 6, 18).”