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Python implementation of the Multiple Hypothesis Tracking algorithm

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Multiple Hypothesis Tracking

This is an implementation of the Multiple Hypothesis Tracking filter, implemented for educational purposes and for the purpose of the article ''Spatially Indexed Clustering for Scalable Tracking of Remotely Sensed Drift Ice'' accepted for the IEEE Aerospace 2017 conference, Big Sky, MT.

In particular, this implementation studies the use of Spatial Indexing in the MHT clustering process.

More details will be available after the publication of the conference proceedings.

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This software is released under the GPLv3 license.

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Python implementation of the Multiple Hypothesis Tracking algorithm

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  • Python 86.5%
  • C++ 13.5%