@inproceedings{6b6c1fa49cbf48e5986421ce1dffd4d3,
title = "Facial expression recognition on partial facial sections",
abstract = "Research by psychologists have shown that subjects had a preference for a side of a face when it was expressing emotions. This paper seeks to find what accuracies can be attained when only a segment of the face is considered. We show that using one side of the face only reduces accuracy by 0.34% but at half the computationally time required. Various other sections of the face are evaluated for similar performance. We demonstrate that using smaller portions of the face have an expected computation reduction but dont suffer the same degree of accuracy loss. For evaluating we train with a Convolutional Neural Network. To test what portions of a facial image are useful, the full face, half face, eyes, single eye, mouth and half of the mouth are chosen. These images come from the JAFFE, CK+ and KDEF datasets.",
keywords = "CNN, Facial Expression Recognition, Hemisphere differences, Image Processing, Neural Network, Occlusion",
author = "Ryan Melaugh and Nazmul Siddique and Sonya Coleman and Pratheepan Yogarajah",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 11th International Symposium on Image and Signal Processing and Analysis, ISPA 2019 ; Conference date: 23-09-2019 Through 25-09-2019",
year = "2019",
month = oct,
day = "17",
doi = "10.1109/ISPA.2019.8868630",
language = "English",
series = "International Symposium on Image and Signal Processing and Analysis, ISPA",
publisher = "IEEE Computer Society",
pages = "193--197",
editor = "Sven Loncaric and Robert Bregovic and Marco Carli and Marko Subasic",
booktitle = "ISPA 2019 - 11th International Symposium on Image and Signal Processing and Analysis",
address = "United States",
}