Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition

Pratikshya Sharma, Sonya Coleman, Pratheepan Yogarajah, Laurence Taggart, Pradeepa Samarasinghe

2022

Abstract

The Advancements in micro expression recognition techniques are accelerating at an exceptional rate in recent years. Envisaging a real environment, the recordings captured in our everyday life are prime sources for many studies, but these data often suffer from poor quality. Consequently, this has opened up a new research direction involving low resolution micro expression images. Identifying a particular class of micro expression among several classes is extremely challenging due to less distinct inter-class discriminative features. Low resolution of such images further diminishes the discriminative power of micro facial features. Undoubtedly, this increases the recognition challenge by twofold. To address the issue of low-resolution for facial micro expression, this work proposes a novel approach that employs a super resolution technique using Generative Adversarial Network and its variant. Additionally, Local Binary Pattern & Local phase quantization on three orthogonal planes are used for extracting facial micro features. The overall performance is evaluated based on recognition accuracy obtained using a support vector machine. Also, image quality metrics are used for evaluating reconstruction performance. Low resolution images simulated from the SMIC-HS dataset are used for testing the proposed approach and experimental results demonstrate its usefulness.

Paper Citation

in Harvard Style

Sharma P., Coleman S., Yogarajah P., Taggart L. and Samarasinghe P. (2022). Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-549-4, pages 560-569. DOI: 10.5220/0010820100003122

in Bibtex Style

@conference{icpram22,
author={Pratikshya Sharma and Sonya Coleman and Pratheepan Yogarajah and Laurence Taggart and Pradeepa Samarasinghe},
title={Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2022},
pages={560-569},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010820100003122},
isbn={978-989-758-549-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Evaluation of Generative Adversarial Network Generated Super Resolution Images for Micro Expression Recognition
SN - 978-989-758-549-4
AU - Sharma P.
AU - Coleman S.
AU - Yogarajah P.
AU - Taggart L.
AU - Samarasinghe P.
PY - 2022
SP - 560
EP - 569
DO - 10.5220/0010820100003122