Resumen
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.
Idioma original | Inglés |
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Páginas (desde-hasta) | 1059-1073 |
Número de páginas | 15 |
Publicación | Pattern Recognition |
Volumen | 48 |
N.º | 4 |
DOI | |
Estado | Publicada - 1 abr. 2015 |
Publicado de forma externa | Sí |