Evaluation of preference of multimedia content using deep neural networks for electroencephalography

Seong Eun Moon; Soobeom Jang; Jong Seok Lee

doi:10.1109/QoMEX.2018.8463373

Evaluation of preference of multimedia content using deep neural networks for electroencephalography

Seong Eun Moon, Soobeom Jang, Jong Seok Lee

School of Integrated Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ 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.

Original language	English
Title of host publication	2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538626054
DOIs	https://doi.org/10.1109/QoMEX.2018.8463373
Publication status	Published - 2018 Sept 11
Event	10th International Conference on Quality of Multimedia Experience, QoMEX 2018 - Sardinia, Italy Duration: 2018 May 29 → 2018 Jun 1

Publication series

Name	2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018

Other

Other	10th International Conference on Quality of Multimedia Experience, QoMEX 2018
Country/Territory	Italy
City	Sardinia
Period	18/5/29 → 18/6/1

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

Media Technology
Safety, Risk, Reliability and Quality

Access to Document

10.1109/QoMEX.2018.8463373

Cite this

Moon, S. E., Jang, S., & Lee, J. S. (2018). Evaluation of preference of multimedia content using deep neural networks for electroencephalography. In 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018 Article 8463373 (2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/QoMEX.2018.8463373

Moon, Seong Eun ; Jang, Soobeom ; Lee, Jong Seok. / Evaluation of preference of multimedia content using deep neural networks for electroencephalography. 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018).

@inproceedings{91bc3c5eda89414b89452375fe916d84,

title = "Evaluation of preference of multimedia content using deep neural networks for electroencephalography",

abstract = "Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ 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.",

author = "Moon, {Seong Eun} and Soobeom Jang and Lee, {Jong Seok}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th International Conference on Quality of Multimedia Experience, QoMEX 2018 ; Conference date: 29-05-2018 Through 01-06-2018",

year = "2018",

month = sep,

day = "11",

doi = "10.1109/QoMEX.2018.8463373",

language = "English",

isbn = "9781538626054",

series = "2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018",

address = "United States",

}

Moon, SE, Jang, S & Lee, JS 2018, Evaluation of preference of multimedia content using deep neural networks for electroencephalography. in 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018., 8463373, 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018, Institute of Electrical and Electronics Engineers Inc., 10th International Conference on Quality of Multimedia Experience, QoMEX 2018, Sardinia, Italy, 18/5/29. https://doi.org/10.1109/QoMEX.2018.8463373

Evaluation of preference of multimedia content using deep neural networks for electroencephalography. / Moon, Seong Eun; Jang, Soobeom; Lee, Jong Seok.
2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8463373 (2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Evaluation of preference of multimedia content using deep neural networks for electroencephalography

AU - Moon, Seong Eun

AU - Jang, Soobeom

AU - Lee, Jong Seok

PY - 2018/9/11

Y1 - 2018/9/11

N2 - Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ 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.

AB - Evaluation of quality of experience (Qo $E$) based on electroencephalography (EEG) has received great attention due to its capability of real-time Qo $E$ 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.

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M3 - Conference contribution

AN - SCOPUS:85054402325

SN - 9781538626054

T3 - 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018

BT - 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Quality of Multimedia Experience, QoMEX 2018

Y2 - 29 May 2018 through 1 June 2018

ER -

Moon SE, Jang S, Lee JS. Evaluation of preference of multimedia content using deep neural networks for electroencephalography. In 2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8463373. (2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018). doi: 10.1109/QoMEX.2018.8463373

Evaluation of preference of multimedia content using deep neural networks for electroencephalography

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