2023/06/20 by Mitchell Rogers, Rogers, Mitchell, G. Gendron +23
Biochemistry, Genetics and Molecular Biology · Environmental Science · Veterinary · #Animal Behavior and Welfare Studies #Animal Vocal Communication and Behavior #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Wildlife Ecology and Conservation
paper · pdf · doi:10.48550/arxiv.2306.11326
openalex publication_date 2023/06/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recording animal behaviour is an important step in evaluating the well-being of animals and further understanding the natural world. Current methods for documenting animal behaviour within a zoo setting, such as scan sampling, require excessive human effort, are unfit for around-the-clock monitoring, and may produce human-biased results. Several animal datasets already exist that focus predominantly on wildlife interactions, with some extending to action or behaviour recognition. However, there is limited data in a zoo setting or data focusing on the group behaviours of social animals. We introduce a large meerkat (Suricata Suricatta) behaviour recognition video dataset with diverse annotated behaviours, including group social interactions, tracking of individuals within the camera view, skewed class distribution, and varying illumination conditions. This dataset includes videos from two positions within the meerkat enclosure at the Wellington Zoo (Wellington, New Zealand), with 848,400 annotated frames across 20 videos and 15 unannotated videos.