Reproducible-Research.md

+In this page, we provide a list of Reproducible Research publications and other examples that build on top of Bob.
+If you want your publication to be listed here, please [contact us](https://groups.google.com/forum/?fromgroups#!forum/bob-devel).
+
+# Active Publications (using Bob v2)
+
+These publications use the new Bob framework and should work out-of-the-box.
+Please, [let us know](https://groups.google.com/forum/?fromgroups#!forum/bob-devel) in case you have trouble installing or executing any of the papers below.
+
+## Face Recognition in Challenging Environments: A Reproducible Research Survey
+
+We compare a list of face recognition algorithms' performances on different aspects of face recognition, such as facial expression, occlusion, pose and the availability of video data.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/3313)
+* [Source code package](https://pypi.python.org/pypi/bob.chapter.FRICE)
+* [Documentation](http://pythonhosted.org/bob.chapter.FRICE/index.html)
+
+
+## Gender Classification by LUT based boosting of Overlapping Block Patterns
+
+We perform gender classification using a boosted strong classifier build out of weak look-up-table based classifiers, which are build from overlapping multi-block LBP codes.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/3112)
+* [Source code package](https://pypi.python.org/pypi/bob.paper.SCIA2015)
+
+
+## Impact of Eye Detection Error on Face Recognition Performance
+
+We test, how several face recognition algorithms perform, when the images are mis-aligned due to an imprecise eye localization.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/2981)
+* [Source code package](https://pypi.python.org/pypi/xfacereclib.paper.IET2015)
+
+
+# Older Publications (relying on Bob v1)
+
+These publications rely on an older version of Bob, which need [Bob v1 to be installed](Old Releases).
+
+## Score Calibration in Face Recognition
+
+We perform score calibration, a technique adopted from the speaker recognition domain, to perform score calibration using face recognition scores.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/2822)
+* [Source code package](https://pypi.python.org/pypi/xfacereclib.paper.IET2014)
+
+
+## On the Improvements of Uni-modal and Bi-modal Fusions of Speaker and Face Recognition for Mobile Biometrics
+
+We use score calibration techniques to fuse the recognition scores from several speaker and face recognition algorithms and show that the fusion outperforms each single algorithm by far.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/2688)
+* [Source code package](https://pypi.python.org/pypi/xbob.paper.BTFS2013)
+
+
+## An Open Source Framework for Standardized Comparisons of Face Recognition Algorithms
+
+We introduce the FaceRecLib (which in Bob v2 is split into the bob.bio packages), a tool to provide a fair comparison of face recognition algorithms.
+
+* [Publication](http://publications.idiap.ch/index.php/publications/show/2431)
+* [Source code package](https://pypi.python.org/pypi/xfacereclib.paper.BeFIT2012)