@inproceedings{59828a65d662435eae64c5b791ee758a,
title = "A multi-modal approach for emotion recognition of TV drama characters using image and text",
abstract = "Research on facial emotion recognition has long been popular for various purposes. This paper investigates the recognition of the character emotions, to assist in understanding the story. The goal of this research is to classify the facial images of the characters in the Korean TV series 'Misaeng: The Incomplete'1 into 7 emotions: Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise. We built a multi-modal deep learning model which utilizes facial images as well as textual information describing the situations, to classify the facial images. Our experiments indicate that employing multi-modality enhances the performance of facial emotion recognition of story characters.We concludes with discussions and future work.",
keywords = "Asian-face, CNN, Contextualized-embedding, Face-emotion-classification, Multi-modal",
author = "Lee, \{Jung Hoon\} and Kim, \{Hyun Ju\} and Cheong, \{Yun Gyung\}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020 ; Conference date: 19-02-2020 Through 22-02-2020",
year = "2020",
month = feb,
doi = "10.1109/BigComp48618.2020.00-37",
language = "English",
series = "Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "420--424",
editor = "Wookey Lee and Luonan Chen and Yang-Sae Moon and Julien Bourgeois and Mehdi Bennis and Yu-Feng Li and Young-Guk Ha and Hyuk-Yoon Kwon and Alfredo Cuzzocrea",
booktitle = "Proceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020",
}