Simultaneous measurements of three-dimensional trajectories and wingbeat frequencies of birds in the field

This is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recordData accessibility: We provide data including images recorded by four cameras, camera parameters, videos showing the time variation of the bird 3D positions, and plain text files that include bird id number, positions, times, velocities, accelerations, and wingbeat frequencies at every time step. We also provide the Matlab codes that were used to: (i) detect birds on images; (ii) reconstruct birds' 3D locations using the new stereo-matching algorithm; (iii) track individual's 3D motions; and (iv) calculate wing motion and wingbeat frequency from tracking results. The code and data are available at: https://github.com/linghj/3DTracking.git and https://figshare.com/s/3c572f91b07b06ed30aa.Tracking the movements of birds in three dimensions is integral to a wide range of problems in animal ecology, behaviour and cognition. Multi-camera stereo-imaging has been used to track the three-dimensional (3D) motion of birds in dense flocks, but precise localization of birds remains a challenge due to imaging resolution in the depth direction and optical occlusion. This paper introduces a portable stereo-imaging system with improved accuracy and a simple stereo-matching algorithm that can resolve optical occlusion. This system allows us to decouple body and wing motion, and thus measure not only velocities and accelerations but also wingbeat frequencies along the 3D trajectories of birds. We demonstrate these new methods by analysing six flocking events consisting of 50 to 360 jackdaws (Corvus monedula) and rooks (Corvus frugilegus) as well as 32 jackdaws and 6 rooks flying in isolated pairs or alone. Our method allows us to (i) measure flight speed and wingbeat frequency in different flying modes; (ii) characterize the U-shaped flight performance curve of birds in the wild, showing that wingbeat frequency reaches its minimum at moderate flight speeds; (iii) examine group effects on individual flight performance, showing that birds have a higher wingbeat frequency when flying in a group than when flying alone and when flying in dense regions than when flying in sparse regions; and (iv) provide a potential avenue for automated discrimination of bird species. We argue that the experimental method developed in this paper opens new opportunities for understanding flight kinematics and collective behaviour in natural environments.Human Frontier Science Progra