Tree Motion in Three Dimensions: Video-Based Reconstruction using a Calibrated Multi-Camera System

Abstract

Wind-induced tree damage poses a significant risk in both managed forests and urban environments. While computational models could improve how these risks are assessed, their development and validation require reliable experimental data, including spatially resolved measurements of tree motion. A low-cost, non-invasive video-based method is presented for reconstructing time-resolved three-dimensional tree motion from a calibrated three-camera system. Physically attached colour markers are detected through image segmentation, initialised using triangulation and tracked using an Extended Kalman Filter with a Singer acceleration model, requiring no training data. The method was tested and validated in a controlled motion-tracking experiment against an industrial robot arm and a terrestrial Li- DAR scanner. It achieves sub-centimetre accuracy with point-wise variation close to the limit set by the camera resolution. The method produced reproducible threedimensional trajectories and relatively consistent frequency estimates wherever the markers remained sufficiently visible when it was applied to pull-and-release experiments on a spruce, pine and birch tree. The reconstructed motion revealed locationdependent dynamics, with stem and branch features showing different apparent frequencies and decay behaviour. Branch features generally sustained oscillations longer than stem features, consistent with the role branches are thought to play in damping tree motion. Tracking reliability depended strongly on marker visibility, with spruce performing best and pine proving most challenging due to dense foliage and marker occlusion. The thesis establishes that a small, low-cost multi-camera system can deliver accurate, physically interpretable three-dimensional measurements at multiple points simultaneously, providing a foundation for extending the method to mature trees under natural wind loading outdoors.