Species-Agnostic Patterned Animal Re-identification by Aggregating Deep Local Features
Ekaterina Nepovinnykh,
Ilia Chelak,
Tuomas Eerola
et al.
Abstract:Access to large image volumes through camera traps and crowdsourcing provides novel possibilities for animal monitoring and conservation. It calls for automatic methods for analysis, in particular, when re-identifying individual animals from the images. Most existing re-identification methods rely on either hand-crafted local features or end-to-end learning of fur pattern similarity. The former does not need labeled training data, while the latter, although very data-hungry typically outperforms the former whe… Show more
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