000192440 001__ 192440
000192440 005__ 20190316235759.0
000192440 037__ $$aREP_WORK
000192440 088__ $$aIdiap-RR-29-2012
000192440 245__ $$aAn Open Source Framework for Standardized Comparisons of Face Recognition Algorithms
000192440 269__ $$a2012
000192440 260__ $$bIdiap$$c2012
000192440 336__ $$aReports
000192440 520__ $$aIn this paper we introduce the facereclib, the first software library that allows to compare a variety of face recognition algorithms on most of the known facial image databases and that permits rapid prototyping of novel ideas and testing of meta-parameters of face recognition algorithms. The facereclib is built on the open source signal processing and machine learning library Bob. It uses well-specified face recognition protocols to ensure that results are comparable and reproducible. We show that the face recognition algorithms implemented in Bob as well as third party face recognition libraries can be used to run face recognition experiments within the framework of the facereclib. As a proof of concept, we execute four different state-of-the-art face recognition algorithms: local Gabor binary pattern histogram sequences (LGBPHS), Gabor graph comparisons with a Gabor phase based similarity measure, inter-session variability modeling (ISV) of DCT block features, and the linear discriminant analysis on two different color channels (LDA-IR) on two different databases: The Good, The Bad, & The Ugly, and the BANCA database, in all cases using their fixed protocols. The results show that there is not one face recognition algorithm that outperforms all others, but rather that the results are strongly dependent on the employed database.
000192440 700__ $$aGünther, Manuel
000192440 700__ $$aWallace, Roy
000192440 700__ $$0243994$$g143942$$aMarcel, Sébastien
000192440 8564_ $$uhttps://infoscience.epfl.ch/record/192440/files/Gunther_Idiap-RR-29-2012.pdf$$zn/a$$s634048$$yn/a
000192440 909C0 $$xU10381$$0252189$$pLIDIAP
000192440 909CO $$qGLOBAL_SET$$pSTI$$ooai:infoscience.tind.io:192440$$preport
000192440 937__ $$aEPFL-REPORT-192440
000192440 970__ $$aGunther_Idiap-RR-29-2012/LIDIAP
000192440 973__ $$aEPFL
000192440 980__ $$aREPORT