| 한글제목(Korean Title) |
Deep Learning based Emotion Recognition through Biosensor Observations |
| 영문제목(English Title) |
Deep Learning based Emotion Recognition through Biosensor Observations |
| 저자(Author) |
Md. Golam Rabiul Alam
Sarder Fakhrul Abedin
Seung Il Moon
Seon Hyeok Kim
Ashis Talukder
Anupam Kumar Bairagi
Saeed Ullah
Choong Seon Hong
|
| 원문수록처(Citation) |
VOL 43 NO. 02 PP. 1231 ~ 1232 (2016. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Emotion is the conscious experience which can be characterized by functional mental activity and by the degree of contentment and discontentment. In this paper, we have studied physiological changes to infer emotions from biosensor observations. We have considered four basic emotions i.e. Joy, Sad, Surprise and Disgust. The emotions are stimulated through video stimuli. The Likert scale is used to collect subject’s aerosol and valence level to determine the ground truth emotions of the user while watching and listening video stimuli. The wearable ECG, GSR and BVP sensor observations are collected from human subject to infer the emotion which is internally exposed through video stimuli. The convolutional neural network (CNN) of deep learning architecture is used to infer emotions from biosensor’s signal features. The simulation results show higher accuracy of the proposed CNN based emotion recognition approach.
|
| 키워드(Keyword) |
|
| 파일첨부 |
PDF 다운로드
|
