  Studies of social and group behavior in interacting organisms require
high-throughput analysis of the motion of a large number of individual
subjects. Computer vision techniques offer solutions to specific tracking
problems, and allow automated and efficient tracking with minimal human
intervention. In this work, we adopt the open active contour model to track the
trajectories of moving objects at high density. We add repulsive interactions
between open contours to the original model, treat the trajectories as an
extrusion in the temporal dimension, and show applications to two tracking
problems. The walking behavior of Drosophila is studied at different population
density and gender composition. We demonstrate that individual male flies have
distinct walking signatures, and that the social interaction between flies in a
mixed gender arena is gender specific. We also apply our model to studies of
trajectories of gliding Myxococcus xanthus bacteria at high density. We examine
the individual gliding behavioral statistics in terms of the gliding speed
distribution. Using these two examples at very distinctive spatial scales, we
illustrate the use of our algorithm on tracking both short rigid bodies
(Drosophila) and long flexible objects (Myxococcus xanthus). Our repulsive
active membrane model reaches error rates better than $5\times 10^{-6}$ per fly
per second for Drosophila tracking and comparable results for Myxococcus
xanthus.
