Description: Matlab source codes for Multilinear Principal Component Analysis (MPCA)
The matlab codes provided here implement two algorithms presented in the paper "MPCA_TNN08Jan.pdf" included in this package:
Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008.
Algorithm 1: "MPCA.m" implements the MPCA algorithm described in this paper
Algorithm 2: "MPCALDA.m" implements the MPCA+LDA algorithm in this paper
Please refer to the comments in the codes, which include example usage on 2D data and 3D data below:
FERETC80A45.mat: 320 faces (32x32) of 80 subjects (4 samples per class) from the FERET database
USF17Gal.mat: 731 gait samples (32x22x10) of 71 subjects from the gallery set of the USF gait challenge data sets version 1.7
The code needs the tensor toolbox available at http://csmr.ca.sandia.gov/~tgkolda/TensorToolbox/
In all documents and papers reporting research work that uses the matlab codes provided here, the respective author(s) must reference the following paper:
 Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008.
Related: Samples, subjects, 32x32, Class, feret, usf galmat, Database, Faces, feretc mat
O/S:BSD, Linux, Solaris, Mac OS X
File Size: 3.2 MB