mloss.org Uncorrelated Multilinear Discriminant Analysishttp://mloss.orgUpdates and additions to Uncorrelated Multilinear Discriminant AnalysisenSat, 07 Jul 2012 06:27:56 -0000Uncorrelated Multilinear Discriminant Analysis 1.0http://mloss.org/software/view/416/<html><p>This archive contains a Matlab implementation of the Uncorrelated Multilinear Discriminant Analysis (UMLDA) algorithm (as well as its regularized and aggregated versions), as described in the paper: </p> <p>Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Uncorrelated Multilinear Discriminant Analysis with Regularization and Aggregation for Tensor Object Recognition", IEEE Transactions on Neural Networks, Vol. 20, No. 1, Page: 103-123, Jan. 2009. </p> <p>%[Data]% </p> <p>All data used in the paper are included in this package, except the PIE faces due to the 10MB size limit: </p> <p>Directory "FERETC80A45S6" contains the FERET face data for C=80 and their partitions. Directory "FERETC160A45S6" contains the FERET face data for C=160 and their partitions. Directory "FERETC240A45S6" contains the FERET face data for C=240 and their partitions. Directory "FERETC320A45S6" contains the FERET face data for C=320 and their partitions. Directory "USFGait17_32x22x10" contains the gait data used in the paper. </p> <p>The PIE face data used in the paper can be downloaded from http://www.dsp.toronto.edu/~haiping/CodeData/piep3i3.zip </p> <p>%[Usages]% </p> <p>Please refer to "demoR-UMLDA-Aggr.m" for example usage on 2D data "FERETC80A45S6_32x32" in the directory "FERETC80A45S6", which is used in the paper above. The partition used in the paper is included in the directory "FERETC80A45S64Train" for L=4. </p> <p>%[Toolbox needed]%: </p> <p>This code needs the tensor toolbox available at http://csmr.ca.sandia.gov/~tgkolda/TensorToolbox/ This package includes tensor toolbox version 2.1 for convenience. </p> <p>%[Restriction]% </p> <p>In all documents and papers reporting research work that uses the matlab codes provided here, the respective author(s) must reference the following paper: </p> <p>[1] Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Uncorrelated Multilinear Discriminant Analysis with Regularization and Aggregation for Tensor Object Recognition", IEEE Transactions on Neural Networks, Vol. 20, No. 1, Page: 103-123, Jan. 2009. </p> <p>%[Additional Resources]% </p> <p>The BibTeX file "UMLDApublications" contains the BibTex for UMLDA and related works. The included survey paper "SurveyMSL_PR2011.pdf" discusses the relations between UMLDA and related works. </p></html>Haiping LuSat, 07 Jul 2012 06:27:56 -0000http://mloss.org/software/rss/comments/416http://mloss.org/software/view/416/ldadimensionality reductionfeature extractionlinear discriminant analysismultilinear subspace learningtensorsubspace learning