Face Hallucination via Semi-Kernel Partial Least Squares

DOI

10.2991/isrme-15.2015.236How to use a DOI?

Keywords

face super-resolution (SR); collaborative representation (CR); semi-kernel partial least squares (semi-KPLS);

Abstract

In this paper, a patch-based super-resolution (SR) method is proposed to hallucinate facial images. Two steps are involved in this method. In the first step, semi-kernel partial least squares (semi-KPLS) algorithm is used to generate a nonlinear correlative space. In the second step, we use collaborative representation (CR) to infer a high-resolution (HR) face. The experiments conducted on FERET database demonstrate the proposed algorithm can generate better results, in comparison with some state-of-the-art approaches.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiang Zhang
AU  - Fei Zhou
AU  - Fan Yang
AU  - Qingmin Liao
PY  - 2015/04
DA  - 2015/04
TI  - Face Hallucination via Semi-Kernel Partial Least Squares
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 1143
EP  - 1149
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.236
DO  - 10.2991/isrme-15.2015.236
ID  - Zhang2015/04
ER  -