Automated audiovisual behavior recognition in wild primates

Author:

Bain Max1ORCID,Nagrani Arsha1ORCID,Schofield Daniel2ORCID,Berdugo Sophie23ORCID,Bessa Joana4ORCID,Owen Jake4ORCID,Hockings Kimberley J.5ORCID,Matsuzawa Tetsuro6,Hayashi MisatoORCID,Biro Dora47ORCID,Carvalho Susana28910ORCID,Zisserman Andrew1ORCID

Affiliation:

1. Visual Geometry Group, Department of Engineering Science, University of Oxford, Oxford, UK.

2. Primate Models for Behavioural Evolution Lab, Institute of Human Sciences, School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK.

3. Social Body Lab, Institute of Human Sciences, School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK.

4. Department of Zoology, University of Oxford, Oxford, UK.

5. Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Exeter, UK.

6. Division of the Humanities and Social Sciences, California Institute of Technology, 1200 E. California Blvd., MC 228-77, Pasadena, CA 91125, USA.

7. Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA.

8. Gorongosa National Park, Sofala, Mozambique.

9. Centre for Functional Ecology, Department of Life Sciences, Coimbra University, Coimbra, Portugal.

10. Interdisciplinary Centre for Archaeology and Evolution of Human Behaviour, Algarve University, Faro, Portugal.

Abstract

Deep learning using audiovisual data from chimpanzee percussive behaviors enables action recognition in the wild.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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