TY - JOUR
T1 - Tensor locally linear discriminative analysis
AU - Zhang, Zhao
AU - Chow, W. S.
PY - 2011
Y1 - 2011
N2 - This letter presents a Tensor Locally Linear Discriminative Analysis (TLLDA) method for image presentation. TLLDA is originated from the Local Fisher Discriminant Analysis (LFDA), but TLLDA offers some advantages over LFDA. 1) TLLDA can preserve the local discriminative information of image data as LFDA. 2) TLLDA represents images as matrices or 2-order tensors rather than vectors, so TLLDA keeps the spatial locality of pixels in the images. 3) TLLDA avoids the singularity that may be suffered by LFDA. 4) TLLDA is faster than LFDA. Simulations on two real databases verified the validity of TLLDA. Results show that TLLDA is highly competitive with some widely used techniques. © 2011 IEEE.
AB - This letter presents a Tensor Locally Linear Discriminative Analysis (TLLDA) method for image presentation. TLLDA is originated from the Local Fisher Discriminant Analysis (LFDA), but TLLDA offers some advantages over LFDA. 1) TLLDA can preserve the local discriminative information of image data as LFDA. 2) TLLDA represents images as matrices or 2-order tensors rather than vectors, so TLLDA keeps the spatial locality of pixels in the images. 3) TLLDA avoids the singularity that may be suffered by LFDA. 4) TLLDA is faster than LFDA. Simulations on two real databases verified the validity of TLLDA. Results show that TLLDA is highly competitive with some widely used techniques. © 2011 IEEE.
KW - Dimensionality reduction
KW - discriminant analysis
KW - tensor representation
KW - trace ratio optimization
UR - http://www.scopus.com/inward/record.url?scp=80053228485&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-80053228485&origin=recordpage
U2 - 10.1109/LSP.2011.2165538
DO - 10.1109/LSP.2011.2165538
M3 - RGC 21 - Publication in refereed journal
SN - 1070-9908
VL - 18
SP - 643
EP - 646
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
IS - 11
M1 - 5993499
ER -