DNNFG: DNN based on Fourier Transform Followed by Gabor Filtering for the Modular FER

Sujata, Suman Mitra

Abstract

The modular approach mimics the capability of the human brain to identify a person with a limited facial part. In this article, we experimentally show that some facial parts like eyes, nose, lips, and forehead contribute more in the expression recognition task. Deep neural network, VGG16 ft, is proposed to automatically extricate features from the given facial images. Fine-tuning is very fruitful to the FER (Facial Expression Recognition) with pre-trained models, if sufficient facial images are not collected. Two preprocessing approaches, Fourier transform followed by Gabor filters and Data Augmentation (DA), are implemented to restrain the regions used for Facial expression recognition (FER). The features from four facial regions are concatenated and classification is done using SVM and KNN (with different distance measure). The experimental result shows that the proposed framework can recognize the facial expressions like happy, anger, sad, surprise, disgust and fear with high accuracy for the benchmark datasets like “JAFFE”, “VIDEO”, “CK+” and “Oulu-Casia”.

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Paper Citation


in Harvard Style

Sujata. and Mitra S. (2020). DNNFG: DNN based on Fourier Transform Followed by Gabor Filtering for the Modular FER.In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-397-1, pages 212-219. DOI: 10.5220/0009144102120219


in Bibtex Style

@conference{icpram20,
author={Sujata and Suman Mitra},
title={DNNFG: DNN based on Fourier Transform Followed by Gabor Filtering for the Modular FER},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2020},
pages={212-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009144102120219},
isbn={978-989-758-397-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - DNNFG: DNN based on Fourier Transform Followed by Gabor Filtering for the Modular FER
SN - 978-989-758-397-1
AU - Sujata.
AU - Mitra S.
PY - 2020
SP - 212
EP - 219
DO - 10.5220/0009144102120219