Chimpanzee face recognition from videos in the wild using deep learning
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Wild ape face recognition using artificial intelligence opens the way for fully automated analysis of large-scale video datasets.
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In that study, humans achieved identification accuracy between 20% (novices) and 42% (experts) with annotation time between 1 and 2 hours, while the DL model achieved 84% in seconds.
“where humans achieved identification accuracy between 20% (novices) and 42% (experts) with an annotation time between 1 and 2 h, the DL model achieved an identification accuracy of 84% in a matter of seconds.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [38]
A study of 23 chimpanzees in Guinea applied facial recognition to a multi-year dataset of 1 million images and achieved greater than 90% accuracy.
“a study of a small group of 23 chimpanzees in Guinea applied facial recognition techniques to a multi-year dataset comprising 1 million images and achieved >90% accuracy38.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [38]
Conventional and more recently DL-based methods have reached strong performance for specific taxa, especially across small populations.
“Yet, conventional101 and more recently DL-based38,54,102 methods have reached strong performance for specific taxa, especially across small populations.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [38]
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Cited by
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Perspectives in machine learning for wildlife conservation
Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., Mathis, A., Mathis, M. W., van Langevelde, F., Burghardt, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-27980-y · Cited by 740 · see citing works
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“More recently, a handful of studies have applied the similar methods to other animal species, allowing computers to individually recognize primates (Deb et al., 2018; Schofield et al., 2019), pigs (Hansen et al., 2018) and elephants (Körschens, Barz, & Denzler, 2018).”
BackgroundPerspectives on Individual Animal Identification from Biology and Computer Vision
Vidal, M., Wolf, N., Rosenberg, B., Harris, B. P., & Mathis, A. (2021) · Integrative and Comparative Biology · doi:10.1093/icb/icab107 · Cited by 104 · see citing works
- Authors
- Schofield, D., Nagrani, A., Zisserman, A., Hayashi, M., Matsuzawa, T., Biro, D., & Carvalho, S.
- Affiliations
- University of Oxford (GB)
- Kyoto University (JP)
- Corresponding author
- Schofield, Daniel
- Nagrani, Arsha
- ORCID
- Venue
- Science Advances
- Published
- 2019-09-06
- Volume
- 5
- Issue
- 9
- Pages
- eaaw0736-eaaw0736
- ISSN
- 2375-2548 (ISSN-L)
- PMC
- PMC6726454
- OpenAlex
- W2971892976
- Cited by
- 224
- References
- 38
- Citations by year
- 2026: 14 · 2025: 30 · 2024: 35 · 2023: 49 · 2022: 43 · 2021: 28 · 2020: 22 · 2019: 3
- FWCI
- 30.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Science Advances (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion, cc-by-nc)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc)
- Kyoto University Research Information Repository (Kyoto University) (submittedVersion, cc-by-nc)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
- Funders
- Leverhulme Trust (PLP-2016-114); MEXT-JSPS (#16H06283) and LGP-U04,)
- Japan Society for the Promotion of Science
- EPSRC (EP/M013774/1)
- Google PhD fellowship
- Clarendon Fund
- Boise Trust Fund
- Topics
- Social Sciences › Psychology › Social Psychology › Primate Behavior and Ecology
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- chimpanzees, face recognition, face detection, face tracking, personal identification, sex identification, social network structure, population aging, automated video analysis, animal behavior
- MeSH terms
- Facial Recognition, Animals, Pan troglodytes, Female, Male, Video Recording
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