This package implements the LBP counter-measure to spoofing attacks to face recognition systems as described at the paper:

@INPROCEEDINGS{Chingovska_BIOSIG_2012,
author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
keywords = {Attack, Counter-Measures, Counter-Spoofing, Face Recognition, Liveness Detection, Replay, Spoofing},
month = sep,
title = {On the Effectiveness of Local Binary Patterns in Face Anti-spoofing},
journal = {IEEE BIOSIG 2012},
year = {2012},
}

The dataset used in the paper is REPLAY-ATTACK database and it is publicly available. It should be downloaded and installed prior to using the programs described in this package. Visit the REPLAY-ATTACK database page for more information.

To run the code in this package, you will also need Bob, an open-source toolkit for Signal Processing and Machine Learning. The code has been tested to work with Bob 1.0.x.

To follow these instructions locally you will need a local copy of this package. Start by cloning this project with something like (shell commands are marked with a $ signal):

$ git clone --depth=1 https://github.com/bioidiap/antispoofing.lbp.git
$ cd antispoofing.lbp
$ rm -rf .git # you don't need the git directories...

Alternatively, you can use the github tarball API to download the package:

$ wget --no-check-certificate https://github.com/bioidiap/antispoofing.lbp/tarball/master -O- | tar xz 
$ mv bioidiap-antispoofing-* antispoofing.lbp

Installation of the toolkit uses the buildout build environment. You don't need to understand its inner workings to use this package. Here is a recipe to get you started:

$ python bootstrap.py
$ ./bin/buildout

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

$ python boostrap.py
$ # edit localbob.cfg
$ ./bin/buildout -c localbob.cfg

Please refer to the documentation inside the doc directory of this package for further instructions on the functionality available.

If you need to cite this work, please use the following:

@INPROCEEDINGS{Chingovska_BIOSIG_2012,
author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
keywords = {Attack, Counter-Measures, Counter-Spoofing, Face Recognition, Liveness Detection, Replay, Spoofing},
month = sep,
title = {On the Effectiveness of Local Binary Patterns in Face Anti-spoofing},
journal = {IEEE BIOSIG 2012},
year = {2012},
}