Meerkat Behaviour Recognition Dataset

This project contains annotated and unannotated behavioural video footage of meerkats at Wellington Zoo. Data is annotated as bounding boxes with a behaviour class for each frame.

Abstract:
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. 

Associated annotations: https://meerkat-dataset.github.io/Annotations.zip
More information: https://meerkat-dataset.github.io/

本项目汇集了惠灵顿动物园（新西兰惠灵顿）土拨鼠（Suricata Suricatta）的行为视频资料，包括标注与未标注的视频片段。数据标注以边框框选的形式呈现，每帧视频均对应一个行为类别。

摘要：记录动物行为是评估动物福祉及深入理解自然世界的重要步骤。目前，在动物园环境中记录动物行为的方法，如扫描采样，需要大量人力，不适合全天候监控，且可能产生人类偏差的结果。已存在多个主要关注野生动物互动的数据集，部分数据集扩展至动作或行为识别。然而，关于动物园环境或专注于群居动物群体行为的数据则相对匮乏。本研究所引入的大型土拨鼠行为识别视频数据集，包含了多样化的标注行为，如群体社会互动、摄像机视野内个体追踪、类别分布失衡以及不同的光照条件。该数据集包含了惠灵顿动物园土拨鼠围栏内两个位置的848,400帧标注视频以及20段视频和15段未标注视频。

相关标注：https://meerkat-dataset.github.io/Annotations.zip
更多信息：https://meerkat-dataset.github.io/