Automated Audiovisual Behaviour Recognition in Wild Primates [Science Adv.'21]

Abstract

Large video datasets of wild animal behaviour are crucial to produce longitudinal research and accelerate conservation efforts; however, large-scale behaviour analyses continue to be severely constrained by time and resources. We present a deep convolutional neural network (CNN) approach and fully automated pipeline to detect and track two audio-visually distinctive actions in wild chimpanzees: buttress-drumming and nut-cracking.

Publication
In Science Advances (in press)