Author: Nesli Erdogmus


 Spoofing Face Recognition with 3D Masks

This package implements the baseline verification algorithms and LBP-based counter-measures against spoofing attacks with 3d masks to 2D, 2.5D and 3D face recognition systems as described in the paper `Spoofing Face Recognition with 3D Masks`, by N. Erdogmus and S. Marcel.

If you use this package and/or its results, please cite the following publications:

1. The original paper with the baseline verification and counter-measure algorithms explained in details::

2. Bob as the core framework used to run the experiments::

        author = {A. Anjos AND L. El Shafey AND R. Wallace AND M. G\"unther AND C. McCool AND S. Marcel},
        title = {Bob: a free signal processing and machine learning toolbox for researchers},
        year = {2012},
        month = oct,
        booktitle = {20th ACM Conference on Multimedia Systems (ACMMM), Nara, Japan},
        publisher = {ACM Press},

If you wish to report problems or improvements concerning this code, please contact the authors of the above mentioned papers.

Raw data

The data used in the paper is publicly available and should be downloaded and installed **prior** to try using the programs described in this package. Visit `the 3D MASK ATTACK database portal <>`_ for more information.


.. note:: 

  If you are reading this page through our GitHub portal and not through PyPI, note **the development tip of the package may not be stable** or become unstable in a matter of moments.

  Go to `  <>`_ to download the latest stable version of this package.

There are 2 options you can follow to get this package installed and operational on your computer: you can use automatic installers like `pip <>`_ (or `easy_install <>`_) or manually download, unpack and use `zc.buildout <>`_ to create a virtual work environment just for this package.

Using an automatic installer

Using ``pip`` is the easiest (shell commands are marked with a ``$`` signal)::

  $ pip install

You can also do the same with ``easy_install``::

  $ easy_install

This will download and install this package plus any other required dependencies. It will also verify if the version of Bob you have installed is compatible.

This scheme works well with virtual environments by `virtualenv <>`_ or if you have root access to your machine. Otherwise, we recommend you use the next option.

Using ``zc.buildout``

Download the latest version of this package from `PyPI <>`_ and unpack it in your working area. The installation of the toolkit itself uses `buildout <>`_. You don't need to understand its inner workings to use this package. Here is a recipe to get you started::
  $ python 
  $ ./bin/buildout

These 2 commands should download and install all non-installed dependencies and get you a fully operational test and development environment.

.. note::

  The python shell used in the first line of the previous command set determines the python interpreter that will be used for all scripts developed inside this package. Because this package makes use of `Bob <>`_, you must make sure that the ```` script is called with the **same** interpreter used to build Bob, or unexpected problems might occur.

  If Bob is installed by the administrator of your system, it is safe to consider it uses the default python interpreter. In this case, the above 3 command lines should wor