Our short paper was accepted at RFIAP. This work explore the use of Convolutional Neural Networks for the pose estimation of honeybees (localization of their body parts) from images, using a user trainable model. It shows promising results with over 95% of correct detection. These results open new possibilities for automated tracking of a rich set of honeybee behavior at their colony in the field.
[1] I. F. Rodríguez, K. Branson, E. Acuña, J. L. Agosto-Rivera, T. Giray, R. Mégret, “Honeybee Detection and Pose Estimation using Convolutional Neural Networks”, Reconnaissance des Formes, Image, Apprentissage et Perception, Paris, june 2018. [PDF]
https://rfiap2018.ign.fr/programmeRFIAP