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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Facial Expression Recognition Using 3D Convolutional Neural Network

Author 1: Young-Hyen Byeon
Author 2: Keun-Chang Kwak*

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.051215

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 12, 2014.

  • Abstract and Keywords
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Abstract: This paper is concerned with video-based facial expression recognition frequently used in conjunction with HRI (Human-Robot Interaction) that can naturally interact between human and robot. For this purpose, we design a 3D-CNN(3D Convolutional Neural Networks) by augmenting dimensionality reduction methods such as PCA(Principal Component Analysis) and TMPCA(Tensor-based Multilinear Principal Component Analysis) to recognize simultaneously the successive frames with facial expression images obtained through video camera. The 3D-CNN can achieve some degree of shift and deformation invariance using local receptive fields and spatial subsampling through dimensionality reduction of redundant CNN’s output. The experimental results on video-based facial expression database reveal that the presented method shows a good performance in comparison to the conventional methods such as PCA and TMPCA.

Keywords: convolutional neural network; facial expression recognition; deep learning

Young-Hyen Byeon and Keun-Chang Kwak*, “Facial Expression Recognition Using 3D Convolutional Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 5(12), 2014. http://dx.doi.org/10.14569/IJACSA.2014.051215

@article{Byeon2014,
title = {Facial Expression Recognition Using 3D Convolutional Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.051215},
url = {http://dx.doi.org/10.14569/IJACSA.2014.051215},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {12},
author = {Young-Hyen Byeon and Keun-Chang Kwak*}
}


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