BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos
CoRR(2024)
Abstract
Using drones to track multiple individuals simultaneously in their natural
environment is a powerful approach for better understanding group primate
behavior. Previous studies have demonstrated that it is possible to automate
the classification of primate behavior from video data, but these studies have
been carried out in captivity or from ground-based cameras. To understand group
behavior and the self-organization of a collective, the whole troop needs to be
seen at a scale where behavior can be seen in relation to the natural
environment in which ecological decisions are made. This study presents a novel
dataset from drone videos for baboon detection, tracking, and behavior
recognition. The baboon detection dataset was created by manually annotating
all baboons in drone videos with bounding boxes. A tiling method was
subsequently applied to create a pyramid of images at various scales from the
original 5.3K resolution images, resulting in approximately 30K images used for
baboon detection. The tracking dataset is derived from the detection dataset,
where all bounding boxes are assigned the same ID throughout the video. This
process resulted in half an hour of very dense tracking data. The behavior
recognition dataset was generated by converting tracks into mini-scenes, a
video subregion centered on each animal; each mini-scene was manually annotated
with 12 distinct behavior types, resulting in over 20 hours of data. Benchmark
results show mean average precision (mAP) of 92.62% for the YOLOv8-X detection
model, multiple object tracking precision (MOTA) of 63.81% for the BotSort
tracking algorithm, and micro top-1 accuracy of 63.97% for the X3D behavior
recognition model. Using deep learning to classify wildlife behavior from drone
footage facilitates non-invasive insight into the collective behavior of an
entire group.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined