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.
|Title of host publication||ISPA 2019 - 11th International Symposium on Image and Signal Processing and Analysis|
|Editors||Sven Loncaric, Robert Bregovic, Marco Carli, Marko Subasic|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|Publication status||Published - 17 Oct 2019|
|Event||11th International Symposium on Image and Signal Processing and Analysis, ISPA 2019 - Dubrovnik, Croatia|
Duration: 23 Sep 2019 → 25 Sep 2019
|Name||International Symposium on Image and Signal Processing and Analysis, ISPA|
|Conference||11th International Symposium on Image and Signal Processing and Analysis, ISPA 2019|
|Period||23/09/19 → 25/09/19|
Bibliographical notePublisher Copyright:
© 2019 IEEE.
Copyright 2019 Elsevier B.V., All rights reserved.
- Facial Expression Recognition
- Hemisphere differences
- Image Processing
- Neural Network