Head-mounted camera for reconstructing outdoor behavior in freely flying birds
Year: 2026
Type: software
Abstract: Code repository for Nature Methods article "Head-mounted camera for reconstructing outdoor behavior in freely flying birds" (NMETH-A65482B) Abstract Capturing the fine details of behavior when animals perform complex tasks, such as prey pursuit and capture, in natural environments is a challenging endeavor. For birds of prey, commonly used tracking approaches, such as lightweight GPS and inertia measurement units (IMUs), cannot simultaneously track the birds position and the fine details of body part motion or moving external objects. Here we designed a head-mounted, tetherless, 4π camera system which, combined with a high-resolution environmental scan, enabled detailed three-dimensional measurement of both head position and orientation in freely flying Harris’ hawks (Parabuteo unicinctus) performing aerial pursuit in the wild. This stable head-mounted imaging approach enabled reconstruction of flight trajectories in natural environments, detailed quantification of head motion, optic flow and target position calculations, while the bird tracked and captured airborne targets. Description bboVisO-voit_sawinski_2026.zip: Contains the code for simple pose and orientation estimation for omnidirectional cameras for reproduction purposes. For new projects, we recommend using the current version at https://github.com/bbo-lab/bboVisO tetherless-extractor-round2_4pi.zip: Data extraction code for interpreation of yml configs, interpolation, construction of transformations between coordinate systems etc. Manuscript version for reproduction purposes. For new projects, we recommend using bbo-therelessextracter on PyPI. junker-bird.zip: Contains analysis and figure code for manuscript. Subfolder /python_package needs to be installed as a python package, e.g. using `pip install python_package`.
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Max-Planck-Gesellschaft
OpenAlex ID: W7204262263