Automated audiovisual behavior recognition in wild primates.

Bibliographic Collection: 
CARTA-Inspired Publication
Publication Type: Journal Article
Authors: Bain, Max; Nagrani, Arsha; Schofield, Daniel; Berdugo, Sophie; Bessa, Joana; Owen, Jake; Hockings, Kimberley J; Matsuzawa, Tetsuro; Hayashi, Misato; Biro, Dora; Carvalho, Susana; Zisserman, Andrew
Year of Publication: 2021
Journal: Sci Adv
Volume: 7
Issue: 46
Pagination: eabi4883
Date Published: 2021 Nov 12
Publication Language: eng
ISSN: 2375-2548
Abstract:

Large video datasets of wild animal behavior are crucial to produce longitudinal research and accelerate conservation efforts; however, large-scale behavior analyses continue to be severely constrained by time and resources. We present a deep convolutional neural network approach and fully automated pipeline to detect and track two audiovisually distinctive actions in wild chimpanzees: buttress drumming and nut cracking. Using camera trap and direct video recordings, we train action recognition models using audio and visual signatures of both behaviors, attaining high average precision (buttress drumming: 0.87 and nut cracking: 0.85), and demonstrate the potential for behavioral analysis using the automatically parsed video. Our approach produces the first automated audiovisual action recognition of wild primate behavior, setting a milestone for exploiting large datasets in ethology and conservation.

DOI: 10.1126/sciadv.abi4883
Alternate Journal: Sci Adv