Wrapper classes for the CSU facerec2010 classes

This package is part of the bob.bio packages. It provides wrapper classes for the CSU Face Recognition Resources. Two algorithms are provided by the CSU toolkit (and also by this satellite package): the local region PCA (LRPCA) and the LDA-IR (also known as CohortLDA). This package does not include the source code of the CSU Face Recognition Resources itself. For installation instructions of the original source code, please read Installation.

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.

In fact, this satallite package just provides the source to be able to execute experiments using LRPCA and LDA-IR. Please refer to the FaceRecLib Documentation to get more information on how to use this package to run face recognition experiments. A working example, which is able to re-run the original LRPCA and LDA-IR experiments, which are reported in [PBD+11] and [LBP+12], respectively, can be found under xfacereclib.paper.BeFIT2012.


In the above mentioned example, we were not able to perfectly re-generate the results from the original CSU toolkit, though our results were relatively close. It seems that different versions of the dependent packages (like OpenCV, PIL or similar) produce slightly different results.

[PBD+11]P.J. Phillips, J.R. Beveridge, B.A. Draper, G. Givens, A.J. O’Toole, D.S. Bolme, J. Dunlop, Y.M. Lui, H. Sahibzada and S. Weimer. “An introduction to the good, the bad, & the ugly face recognition challenge problem”. Automatic face gesture recognition and workshops (FG 2011), pages 346-353. 2011.
[LBP+12]Y.M. Lui, D. Bolme, P.J. Phillips, J.R. Beveridge and B.A. Draper. “Preliminary studies on the good, the bad, and the ugly face recognition challenge problem”. Computer vision and pattern recognition workshops (CVPRW), pages 9-16. 2012.