Micro-expression Recognition Under Low-resolution Cases

Guifeng Li, Jingang Shi, Jinye Peng, Guoying Zhao

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.

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Paper Citation


in Harvard Style

Li G., Shi J., Peng J. and Zhao G. (2019). Micro-expression Recognition Under Low-resolution Cases.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 427-434. DOI: 10.5220/0007373604270434


in Bibtex Style

@conference{visapp19,
author={Guifeng Li and Jingang Shi and Jinye Peng and Guoying Zhao},
title={Micro-expression Recognition Under Low-resolution Cases},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={427-434},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007373604270434},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Micro-expression Recognition Under Low-resolution Cases
SN - 978-989-758-354-4
AU - Li G.
AU - Shi J.
AU - Peng J.
AU - Zhao G.
PY - 2019
SP - 427
EP - 434
DO - 10.5220/0007373604270434