ABSTRACT
In this paper we propose a novel method to obtain 3D motion trajectories of dense particle swarms using multiple cameras, which facilitates the study of animal grouping behavior. The proposed method aims at minimizing the two kinds of ambiguities: stereo matching ambiguity and motion correspondence ambiguity. We introduce Verification View which provides additional epipolar constraint to significantly reduce stereo matching ambiguity. The proposed method employs optimal assignment with state prediction and candidate filtering to establish temporal association of particles. The performance on simulated particle swarms demonstrates the superiority of our methods in reducing the two kinds of ambiguities, compared with state-of-the-art. Besides, the proposed method successfully reconstructs hundreds of trajectories of Drosophila in real-world experiment, in only a few seconds.
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Index Terms
Accurate and fast 3D tracking of dense particle swarms
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