期刊
PATTERN RECOGNITION
卷 48, 期 4, 页码 1059-1073出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2014.07.017
关键词
Photo-identification; Animal biometrics; Individual identification; Relevance feedback; Crowdsourcing; Conservation; Scale-cascaded alignment; Local features; Hybrid shape contexts; Gecko; Skink; Whale shark; Salamander
资金
- AFOSR [FA9550-12-1-0313]
- NSF [DBI-1146747]
- MIT-Mexico Seed Fund (MISTI)
- FOMIX CONACYT-GDF [189085]
- SIP-IPN [20140325]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1146747] Funding Source: National Science Foundation
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. (C) 2014 Elsevier Ltd. All rights reserved.
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