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https://hdl.handle.net/10316/107366
Título: | Chimpanzee face recognition from videos in the wild using deep learning | Autor: | Schofield, Daniel Nagrani, Arsha Zisserman, Andrew Hayashi, Misato Matsuzawa, Tetsuro Biro, Dora Carvalho, Susana |
Data: | Set-2019 | Editora: | American Association for the Advancement of Science | Projeto: | This work is supported by the EPSRC program grant Seebibyte: Visual Search for the Era of Big Data (EP/M013774/1), and the Cooperative Research Program of Primate Research Institute, Kyoto University. A.N. is funded by a Google PhD fellowship in machine perception, speech technology, and computer vision. D.S. is funded by the Clarendon Fund, Boise Trust Fund, and Wolfson College, University of Oxford. S.C. is funded by the Leverhulme Trust (PLP-2016-114). T.M. is funded by MEXT-JSPS (#16H06283) and LGP-U04, as well as the Japan Society for the Promotion of Science (JSPS) Core-to-Core Program CCSN. | Título da revista, periódico, livro ou evento: | Science Advances | Volume: | 5 | Número: | 9 | Resumo: | Video recording is now ubiquitous in the study of animal behavior, but its analysis on a large scale is prohibited by the time and resources needed to manually process large volumes of data. We present a deep convolutional neural network (CNN) approach that provides a fully automated pipeline for face detection, tracking, and recognition of wild chimpanzees from long-term video records. In a 14-year dataset yielding 10 million face images from 23 individuals over 50 hours of footage, we obtained an overall accuracy of 92.5% for identity recognition and 96.2% for sex recognition. Using the identified faces, we generated co-occurrence matrices to trace changes in the social network structure of an aging population. The tools we developed enable easy processing and annotation of video datasets, including those from other species. Such automated analysis unveils the future potential of large-scale longitudinal video archives to address fundamental questions in behavior and conservation. | URI: | https://hdl.handle.net/10316/107366 | ISSN: | 2375-2548 | DOI: | 10.1126/sciadv.aaw0736 | Direitos: | openAccess |
Aparece nas coleções: | I&D CFE - Artigos em Revistas Internacionais |
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Chimpanzee face recognition from videos in the wildusing deep learning.pdf | 1.24 MB | Adobe PDF | Ver/Abrir |
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