Sloop: A pattern retrieval engine for individual animal identification. Issue 4 (April 2015) - Duyck, James; Finn, Chelsea; Hutcheon, Andy; Vera, Pablo; Salas, Joaquin; Ravela, Sai
Abstract Identifying individuals in photographs of animals collected over time is a non-invasive approach for ecological monitoring and conservation. This paper describes the design and use of Sloop, the first image retrieval system for individual animal identification incorporating crowd-sourced relevance feedback. Sloop׳s iterative retrieval strategy using hierarchical and aggregated matching and relevance feedback consistently improves deformation and correspondence-based approaches for individual identification across several species. Its crowdsourcing strategy is successful in utilizing relevance feedback on a large scale. Sloop is in operational use. The user experience and results are presented here to facilitate the creation of a community-based individual identification system for conservation planning.