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We address the problem of identifying individual cetaceans from imagesshowing the trailing edge of their fins. Given the trailing edge from anunknown individual, we produce a ranking of known individuals from a database.The nicks and notches along the trailing edge define an individual's uniquesignature. We define a representation based on integral curvature that isrobust to changes in viewpoint and pose, and captures the pattern of nicks andnotches in a local neighborhood at multiple scales. We explore two rankingmethods that use this representation. The first uses a dynamic programmingtime-warping algorithm to align two representations, and interprets thealignment cost as a measure of similarity. This algorithm also exploits learnedspatial weights to downweight matches from regions of unstable curvature. Thesecond interprets the representation as a feature descriptor. Feature keypointsare defined at the local extrema of the representation. Descriptors for the setof known individuals are stored in a tree structure, which allows us to performqueries given the descriptors from an unknown trailing edge. We evaluate thetop-k accuracy on two real-world datasets to demonstrate the effectiveness ofthe curvature representation, achieving top-1 accuracy scores of approximately95% and 80% for bottlenose dolphins and humpback whales, respectively.

Integral Curvature Representation and Matching Algorithms for Identification of Dolphins and Whales