An RJMCMC-Based Method for Tracking and Resolving Collisions of Drosophila Larvae

Drosophila melanogaster is an important model organism for ongoing research in neuro- and behavioral biology. Especially the locomotion analysis has become an integral part of such studies and thus elaborated automated tracking systems have been proposed in the past. However, most of these approaches share the inability to precisely segment the contours of colliding animals leading to the absence of model and motion-related features during collisions. Here, we translate the task of tracking and resolving colliding animals into a filtering problem solvable by Markov Chain Monte Carlo methods and elaborate an adequate larva model. By comparing our method with state-of-the-art approaches, we demonstrate that our algorithm produces significantly better results in a fraction of time and facilitates the analysis of animal behavior during interaction in more detail.