This paper summarizes an approach based on stereo vision to recover honeybee trajectories in 3D at the beehive entrance. The 3D advantage offered by stereo vision is crucial to overcome the rough constraints of the application (number of bees, target dynamics and light). Biologists have highlighted the close scale influence of the environment on bees dynamics. We propose to transpose this idea to enhance our tracking process based on Global Nearest Neighbors. Our method normalizes track/observation association costs that are originally not uniformly distributed over the scene. Therefore, the structure of the scene is needed in order to compute relative distances with the targets. The beehive and especially the flight board is the referent environment for bees, so we propose a method to reconstruct the flight board surface from the noisy and incomplete disparity maps provided by the stereo camera.