Gaussian Mixture Model based Algorithms

This package is part of the bob.bio packages, which provide open source tools to run comparable and reproducible biometric recognition experiments. In this package, algorithms for executing experiments based on Gaussian Mixture Models are provided, including scripts to run the training procedures of the Expectation-Maximization loops in parallel.

For more detailed information about the structure of the bob.bio packages, please refer to the documentation of bob.bio.base. Particularly, the installation of this and other bob.bio packages, please read the Installation Instructions.

In the following, we provide more detailed information about the particularities of this package only.

References

Todo

Provide the correct references for the algorithms defined in this package.

ToDo-List

This documentation is still under development. Here is a list of things that needs to be done:

Todo

Document the details of the GMM-based algorithms.

(The original entry is located in /scratch/builds/bob/bob.bio.gmm/doc/implementation.rst, line 6.)

Todo

Provide the correct references for the algorithms defined in this package.

(The original entry is located in ../../../../doc/references.rst, line 5.)

Todo

improve the documentation of the parallelized scripts.

(The original entry is located in /scratch/builds/bob/bob.bio.gmm/doc/parallel.rst, line 20.)

Todo

Improve documentation of the functions and classes of bob.bio.gmm.

(The original entry is located in /scratch/builds/bob/bob.bio.gmm/doc/py_api.rst, line 6.)

Todo

Provide the correct references for the algorithms defined in this package.

(The original entry is located in /scratch/builds/bob/bob.bio.gmm/doc/references.rst, line 5.)

Indices and tables