Relevance Feedback in Biometric Retrieval of Animal Photographs

摘要

The characterization of individual animal life history is crucial for conservation efforts. In this paper, Sloop, an operational pattern retrieval engine for animal identification, is extended by coupling crowdsourcing with image retrieval. The coupled system delivers scalable performance by using aggregated computational inference to effectively deliver precision and by using human feedback to efficiently improve recall. To the best of our knowledge, this is the first coupled human-machine animal biometrics system, and results on multiple species indicate that it is a promising approach for large-scale use.