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An efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling

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Gibbs Sampling

Python package for an efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling. The implementation is done in C++ and based on Algorithm 1. Gibbs (and "Algorithm 1a") of the following paper.

Vo, Ba-Ngu, Ba-Tuong Vo, and Hung Gia Hoang. "An efficient implementation of the generalized labeled multi-Bernoulli filter." IEEE Transactions on Signal Processing 65, no. 8 (2016): 1975-1987.

Requirements

  • Python 3.7
  • C++ compiler (eg. Windows: Visual Studio 15 2017, Ubuntu: g++)
  • git clone https://github.com/pybind/pybind11.git

Install

python setup.py build develop

License

GPLv3

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An efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling

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