caa a22 4500 606159428 CHVBK 20210128100624.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00521-015-1834-y doi (NATIONALLICENCE)springer-10.1007/s00521-015-1834-y Low-resolution degradation face recognition over long distance based on CCA [Elektronische Daten] [Zhenyu Wang, Wankou Yang, Xianye Ben] Canonical correlation analysis (CCA) is a kind of classical multivariate analysis method. Less canonical correlation variables are used to describe the relationship between two variables completely but easily. To get high face recognition rate under low-resolution degradation over a long distance solidly, in this work, CCA is used to extract the correlation between high-resolution face images and low-resolution ones and to find the transform pair between them. Therefore, face images of the same individual with variable resolutions can be matched accurately. This is the first method that uses CCA to do low-resolution degradation face recognition over long distances. We conduct the experiments on the Extended Yale B and ORL database, and the experimental results validate the efficacy of the proposed method. The Natural Computing Applications Forum, 2015 Canonical correlation analysis (CCA) nationallicence Low resolution nationallicence Correlation nationallicence Dimension matching nationallicence Degradation face recognition nationallicence Wang Zhenyu School of Automation, Southeast University, 210096, Nanjing, China aut Yang Wankou School of Automation, Southeast University, 210096, Nanjing, China aut Ben Xianye School of Information Science and Engineering, Shandong University, 250100, Jinan, China aut Neural Computing and Applications Springer London 26/7(2015-10-01), 1645-1652 0941-0643 26:7<1645 2015 26 521 https://doi.org/10.1007/s00521-015-1834-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1834-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Zhenyu School of Automation, Southeast University, 210096, Nanjing, China aut NATIONALLICENCE 700 1- Yang Wankou School of Automation, Southeast University, 210096, Nanjing, China aut NATIONALLICENCE 700 1- Ben Xianye School of Information Science and Engineering, Shandong University, 250100, Jinan, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/7(2015-10-01), 1645-1652 0941-0643 26:7<1645 2015 26 521