000165907 001__ 165907
000165907 005__ 20181226130039.0
000165907 037__ $$aREP_WORK
000165907 245__ $$aParts-Based Face Verification using Local Frequency Bands
000165907 269__ $$a2011
000165907 260__ $$bIdiap$$c2011
000165907 336__ $$aReports
000165907 520__ $$aIn this paper we extend the Parts-Based approach of face verification by performing a frequency-based decomposition. The Parts-Based approach divides the face into a set of blocks which are then considered to be separate observations, this is a spatial decomposition of the face. This paper extends the Parts-Based approach by also dividing the face in the frequency domain and treating each frequency response from an observation separately. This can be expressed as forming a set of sub-images where each sub-image represents the response to a different frequency of, for instance, the Discrete Cosine Transform. Each of these sub-images is treated separately by a Gaussian Mixture Model (GMM) based classifier. The classifiers from each sub-image are then combined using weighted summation with the weights being derived using linear logistic regression. It is shown on the BANCA database that this method improves the performance of the system from an Average Half Total Error Rate of 26.59% for a baseline GMM Parts-Based system to 14.85% for a column-based approach on the frequency sub-images, for Protocol P.
000165907 700__ $$aMcCool, Chris
000165907 700__ $$0243994$$aMarcel, Sébastien$$g143942
000165907 8564_ $$s823097$$uhttps://infoscience.epfl.ch/record/165907/files/McCool_Idiap-RR-06-2011.pdf$$zn/a
000165907 909C0 $$0252189$$pLIDIAP$$xU10381
000165907 909CO $$ooai:infoscience.tind.io:165907$$pSTI$$preport$$qGLOBAL_SET
000165907 937__ $$aEPFL-REPORT-165907
000165907 970__ $$aMcCool_Idiap-RR-06-2011/LIDIAP
000165907 973__ $$aEPFL$$sPUBLISHED
000165907 980__ $$aREPORT