Facial Expression Recognition on partial facial sections

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...

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Bibliographic Details
Published in2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA) pp. 193 - 197
Main Authors Melaugh, Ryan, Siddique, Nazmul, Coleman, Sonya, Yogarajah, Pratheepan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2019
Subjects
Bridges
CNN
Face
Facial Expression Recognition
Hemisphere differences
Image Processing
Mouth
Muscles
Neural Network
Nose
Occlusion
Signal processing
Online AccessGet full text
ISSN1849-2266
DOI10.1109/ISPA.2019.8868630

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Summary: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.
ISSN:1849-2266
DOI:10.1109/ISPA.2019.8868630