Package: xfacereclib.paper.BeFIT2012
This package provides the source code to run the experiments published in the paperAn Open Source Framework for Standardized Comparisons of Face Recognition Algorithms.
It relies on theFaceRecLibto execute all face recognition experiments.
Most of the face recognition algorithms are implemented inBob, while one of them is taken from theCSU Face Recognition Resources.NoteCurrently, this package only works in Unix-like environments and under MacOS.
Due to limitations of the Bob library, MS Windows operating systems are not supported.
We are working on a port of Bob for MS Windows, but it might take a while.NoteThe experiments described in this section use theFaceRecLibin version 1.1.3,Bobin version 1.2.0 and the January 2012 release of theCSU Face Recognition Resources.
These versions are pin-pointed in thesetup.pyfile (see theinstall_requiressection).
For other versions, the results might be slightly different.InstallationThe installation of this package relies on theBuildOutsystem. By default, the command line sequence:$ python bootstrap.py
$ bin/buildoutshould download and install most requirements, including theFaceRecLib, the Database interface packages for theBANCA databaseandthe Good, the Bad & the Ugly database, and, finally, theWrapper classes for the CSU Face Recognition Resources.
Unfortunately, some packages must be installed manually:BobTo install the Bob toolkit, please visithttp://www.idiap.ch/software/bob/and follow the installation instructions.
Please verify that you have at least version 1.2.0 of Bob installed.
If you have installed Bob in a non-standard directory, please open thebuildout.cfgfile from the base directory and set the ‘prefixes’ directory accordingly.CSU Face Recognition ResourcesDue to the fact that the CSU toolkit needs to be patched to work with the FaceRecLib, the setup is unfortunately slightly more complicated.
To be able to run the experiments based on the CSU toolkit, i.e., the LDA-IR algorithm, please download the CSU Face Recognition Resources fromhttp://www.cs.colostate.edu/facerec.
After unpacking the CSU toolkit, it needs to be patched.
For this reason, please follow the instructions:Patch the CSU toolkit:$ bin/buildout -c buildout-before-patch.cfg
$ bin/patch_CSU.py [YOUR_CSU_SOURCE_DIRECTORY]Update thebuildout.cfgfile by modifying thesources-dir= [YOUR_CSU_SOURCE_DIRECTORY]entry to point to the base directory of the patched version of the CSU toolkit.Make sure that you update your installation byagaincalling:$ bin/buildoutNoteThe patch file is only valid for the current version of the CSU toolkit (last checked in December 2012).
If you have another version, please see theGetting helpsection.NoteAt Idiap, you can also use the pre-patched version of the CSU toolkit.
Just use:$ bin/buildout -c buildout-idiap.cfginstead of downloading and patching the CSU toolkit.DatabasesOf course, we are not allowed to re-distribute the original images to run the experiments on.
To re-run the experiments, please make sure to have your own copy of theBANCAandthe Good, the Bad & the Uglyimages.DocumentationAfter installing you might want to create the documentation for this satellite package, which includes more detailed information on how to re-run the experiments and regenerate the scientific plots from the paper.
To generate and open the documentation execute:$ bin/sphinx-build docs sphinx
$ firefox sphinx/index.htmlOf course, you can use any web browser of your choice.Getting helpIn case anything goes wrong, please feel free to open a new ticket in ourGitHub page, or send an email tomanuel.guenther@idiap.ch.Cite our paperIf you use theFaceRecLibor this package in any of your experiments, please cite the following paper:@inproceedings{Guenther_BeFIT2012,
       author = {G{\"u}nther, Manuel AND Wallace, Roy AND Marcel, S{\'e}bastien},
       editor = {Fusiello, Andrea AND Murino, Vittorio AND Cucchiara, Rita},
     keywords = {Biometrics, Face Recognition, Open Source, Reproducible Research},
        month = oct,
        title = {An Open Source Framework for Standardized Comparisons of Face Recognition Algorithms},
    booktitle = {Computer Vision - ECCV 2012. Workshops and Demonstrations},
       series = {Lecture Notes in Computer Science},
       volume = {7585},
         year = {2012},
        pages = {547-556},
    publisher = {Springer Berlin},
     location = {Heidelberg},
          url = {http://publications.idiap.ch/downloads/papers/2012/Gunther_BEFIT2012_2012.pdf}
}