epiTracker: A Framework for Highly Reliable Particle Tracking for the Quantitative Analysis of Fish Movements in Tanks

摘要: Behavioral analysis of moving animals relies on a faithful recording and track to extract relevant parameters movement. To study group behavior social interactions, often simultaneous analyses individuals are required. detect for example identify the leader as opposed followers, one needs an error-free segmentation individual tracks throughout time. While automated tracking algorithms exist that quick easy use, inevitable errors will occur during tracking. solve this problem, we introduce robust algorithm called epiTracker multiple in two-dimensional (2D) videos along with easy-to-use correction method allows obtain segmentation. We have implemented two graphical user interfaces allow user-friendly control functions. Using six labeled 2D datasets, effort accurate labels is quantified compared alternative available software solutions. Both datasets publicly available.