Authors:
Guifeng Li
1
;
Jingang Shi
2
;
Jinye Peng
1
and
Guoying Zhao
3
Affiliations:
1
Department of Information Science and Technology, Northwest University, Xi’an, China
;
2
Center for Machine Vision and Signal Analysis, University of Oulu, Oulu, Finland
;
3
Department of Information Science and Technology, Northwest University, Xi’an, China, Center for Machine Vision and Signal Analysis, University of Oulu, Oulu and Finland
Keyword(s):
Micro-expression Recognition, Surveillance Video, Low-resolution, Super-resolution, Fast LBP-TOP.
Abstract:
Micro-expression is an essential non-verbal behavior that can faithfully express the human’s hidden emotions. It has a wide range of applications in the national security and computer aided diagnosis, which encourages us to conduct the research of automatic micro-expression recognition. However, the images captured from surveillance video easily suffer from the low-quality problem, which causes the difficulty in real applications. Due to the low quality of captured images, the existing algorithms are not able to perform as well as expected. For addressing this problem, we conduct a comprehensive study about the micro-expression recognition problem under low-resolution cases with face hallucination method. The experimental results show that the proposed framework obtains promising results on micro-expression recognition under low-resolution cases.