A Low-Cost Modular Camera System for 3D Pose Estimation in the Field

The individual behavior of animals determines the outcome of ecological interactions and drives group organization and community dynamics. Considerable attention has been given to understanding these types of interactions by way of automated tracking of individuals and bio-logging; however, these methods rarely investigate the behaviors performed by animals. Recent developments in deep learning for pose estimation provide a promising avenue for understanding individual behavior at resolutions previously not possible. However, systems for generating datasets appropriate for these methods in the field are lacking. To fill this gap, we developed a low-cost, modular camera platform to generate 3D imaging data compatible with contemporary pose estimation techniques. We use a connected network of solar-powered cameras that supports synchronous capture, triggering, and the integration of multisensory metadata. We initially generated datasets from three camera modules that allow for 3D pose estimation in a large outdoor area of over 600m² and demonstrate its use in an open field experiment at the Mpala Research Centre and Wildlife Foundation in Nanyuki, Kenya. Our system is designed to be modular and extensible, facilitating the use of many camera modules in very large open areas.