  Creating accurate 3D models of tree topology is an important task for tree
pruning. The 3D model is used to decide which branches to prune and then to
execute the pruning cuts. Previous methods for creating 3D tree models have
typically relied on point clouds, which are often computationally expensive to
process and can suffer from data defects, especially with thin branches. In
this paper, we propose a method for actively scanning along a primary tree
branch, detecting secondary branches to be pruned, and reconstructing their 3D
geometry using just an RGB camera mounted on a robot arm. We experimentally
validate that our setup is able to produce primary branch models with 4-5 mm
accuracy and secondary branch models with 15 degrees orientation accuracy with
respect to the ground truth model. Our framework is real-time and can run up to
10 cm/s with no loss in model accuracy or ability to detect secondary branches.
