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Multiple Hypothesis Hypergraph Tracking for Posture Identification in Embryonic Caenorhabditis elegans

2021-11-11 19:15:07
Andrew Lauziere, Evan Ardiel, Stephen Xu, Hari Shroff
arXiv_CV
           
Abstract

Current methods in multiple object tracking (MOT) rely on independent object trajectories undergoing predictable motion to effectively track large numbers of objects. Adversarial conditions such as volatile object motion and imperfect detections create a challenging tracking landscape in which established methods may yield inadequate results. Multiple hypothesis hypergraph tracking (MHHT) is developed to perform MOT among interdependent objects amid noisy detections. The method extends traditional multiple hypothesis tracking (MHT) via hypergraphs to model correlated object motion, allowing for robust tracking in challenging scenarios. MHHT is applied to perform seam cell tracking during late-stage embryogenesis in embryonic C. elegans.

Abstract (translated)

URL

https://arxiv.org/abs/2111.06425

PDF

https://arxiv.org/pdf/2111.06425.pdf

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