Name
Abstract | ||
|---|---|---|
Two-dimensional partial least squares (2DPLS) is an effective two-view data analysis technique. However, conventional 2DPLS only takes into account the column information of two-dimensional images. In this paper, we simultaneously consider the column-wise and row-wise information of two-dimensional face images. We first propose a row-based two-dimensional PLS (r(2)DPLS) approach and then further present a novel double-directional PLS (D-2 PLS) method. The proposed D-2 PLS method can be optimized by two eigenvalue subproblems. Experimental results on the AR, Yale, and AT&T face databases show that our (DPLS)-P-2 method can overall achieve better recognition accuracy than existing related methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-36808-1_44 | NEURAL INFORMATION PROCESSING (ICONIP 2019), PT IV |
Keywords | DocType | Volume |
Partial least squares, Feature fusion, Face recognition | Conference | 1142 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun-Hao Yuan | 1 | 235 | 22.18 |
| Li Zhu | 2 | 0 | 0.34 |
| Yun Li | 3 | 443 | 53.24 |
| Jipeng Qiang | 4 | 42 | 13.63 |
| Bin Li | 5 | 318 | 30.27 |
| Jianping Gou | 6 | 116 | 24.01 |
| Chao-feng Li | 7 | 148 | 16.45 |