The objective of this work is automatically to identify individual great white sharks in a database of thousands of unconstrained fin images. The approach put forward appreciates shark fins in natural imagery as smooth, flexible and partially occluded objects with an individuality encoding trailing edge.
REFERENCES:
– Automated Identification of Individual Great White Sharks from Unrestricted Fin Imagery
Hughes, B. & Burghardt, T. 2015 Proceedings of the 26th British Machine Vision Conference (BMVC). British Machine Vision Association, p. 92.1-92.14
– Affinity Matting for Pixel-accurate Fin Shape Recovery from Great White Shark Imagery
Hughes, B. & Burghardt, T. 2015, Machine Vision of Animals and their Behaviour Workshop at BMVC, British Machine Vision Association, p. 8.1-8.8
