GroupTracker: Video tracking system for multiple animals under severe occlusion

Computational Biology and Chemistry
Tsukasa FukunagaWataru Iwasaki

Abstract

Quantitative analysis of behaviors shown by interacting multiple animals can provide a key for revealing high-order functions of their nervous systems. To resolve these complex behaviors, a video tracking system that preserves individual identity even under severe overlap in positions, i.e., occlusion, is needed. We developed GroupTracker, a multiple animal tracking system that accurately tracks individuals even under severe occlusion. As maximum likelihood estimation of Gaussian mixture model whose components can severely overlap is theoretically an ill-posed problem, we devised an expectation-maximization scheme with additional constraints on the eigenvalues of the covariance matrix of the mixture components. Our system was shown to accurately track multiple medaka (Oryzias latipes) which freely swim around in three dimensions and frequently overlap each other. As an accurate multiple animal tracking system, GroupTracker will contribute to revealing unexplored structures and patterns behind animal interactions. The Java source code of GroupTracker is available at https://sites.google.com/site/fukunagatsu/software/group-tracker.

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Citations

Jun 9, 2016·PLoS Computational Biology·Yu ToyoshimaYuichi Iino
Jun 30, 2018·The Journal of Experimental Biology·Osamu Yamanaka, Rito Takeuchi
Oct 20, 2018·Frontiers in Genetics·Leire MoyaUNKNOWN Australian Prostate Cancer BioResource

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