Evaluation of quality of experience (QoE) based on electroencephalography (EEG) has received great attention due to its capability of real-time QoE monitoring of users. However, it still suffers from rather low recognition accuracy. In this paper, we propose a novel method using deep neural networks toward improved modeling of EEG and thereby improved recognition accuracy. In particular, we aim to model spatio-temporal characteristics relevant for QoE analysis within learning models. The results demonstrate the effectiveness of the proposed method.
@article{arxiv.1809.03650,
title = {Evaluation of Preference of Multimedia Content using Deep Neural Networks for Electroencephalography},
author = {Seong-Eun Moon and Soobeom Jang and Jong-Seok Lee},
journal= {arXiv preprint arXiv:1809.03650},
year = {2018}
}
Comments
Accepted for the 10th International Conference on Quality of Multimedia Experience (QoMEX 2018)