Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sample-Relaxed Two-Dimensional Color Principal Component Analysis for
  Face Recognition and Image Reconstruction   A sample-relaxed two-dimensional color principal component analysis
(SR-2DCPCA) approach is presented for face recognition and image reconstruction
based on quaternion models. A relaxation vector is automatically generated
according to the variances of training color face images with the same label. A
sample-relaxed, low-dimensional covariance matrix is constructed based on all
the training samples relaxed by a relaxation vector, and its eigenvectors
corresponding to the $r$ largest eigenvalues are defined as the optimal
projection. The SR-2DCPCA aims to enlarge the global variance rather than to
maximize the variance of the projected training samples. The numerical results
based on real face data sets validate that SR-2DCPCA has a higher recognition
rate than state-of-the-art methods and is efficient in image reconstruction.

13
The categories of this paper are: quant-ph
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph