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Efficient Multiple Object Tracking Using Mutually Repulsive Active Membranes

Author(s): Deng, Yi; Coen, Philip A; Sun, Mingzhai; Shaevitz, Joshua W

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Abstract: 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 xanthu 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 x10 {-6} per fly per second for Drosophila tracking and comparable results for Myxococcus xanthus.
Publication Date: 14-Jun-2013
Electronic Publication Date: 14-Jun-2013
Citation: Deng, Yi, Coen, Philip, Sun, Mingzhai, Shaevitz, Joshua W. (2013). Efficient Multiple Object Tracking Using Mutually Repulsive Active Membranes. PLoS ONE, 8 (6), e65769 - e65769. doi:10.1371/journal.pone.0065769
DOI: doi:10.1371/journal.pone.0065769
EISSN: 1932-6203
Pages: e65769 - e65769
Type of Material: Journal Article
Journal/Proceeding Title: PLoS ONE
Version: Final published version. This is an open access article.

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