Name
Abstract | ||
|---|---|---|
Emotion recognition is one of the hottest fields in affective computing research. Recognizing emotions is an important task for facilitating communication between machines and humans. However, it is a very challenging task based on a lack of ethnically diverse databases. In particular, emotional expressions tend to be very dissimilar between Western and Eastern people. Therefore, diverse emotion databases are required for studying emotional expression. However, majority of the well-known emotion databases focus on Western people, which exhibit different characteristics compared to Eastern people. In this study, we constructed a novel emotion dataset containing more than 1200 video clips collected from Korean movies, called Korean Video Dataset for Emotion Recognition in the Wild (KVDERW). Which are similar to real-world conditions, with the goal of studying the emotions of Eastern people, particularly Korean people. Additionally, we developed a semi-automatic video emotion labelling tool that could be used to generate video clips and annotate the emotions in clips. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s11042-020-10106-1 | MULTIMEDIA TOOLS AND APPLICATIONS |
Keywords | DocType | Volume |
Emotion recognition, Facial expression, Emotion dataset | Journal | 80 |
Issue | ISSN | Citations |
6 | 1380-7501 | 1 |
PageRank | References | Authors |
0.37 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Trinh Le Ba Khanh | 1 | 1 | 0.37 |
| Soo-Hyung Kim | 2 | 191 | 49.03 |
| Gueesang Lee | 3 | 208 | 52.71 |
| Hyungjeong Yang | 4 | 455 | 47.05 |
| Eu-Tteum Baek | 5 | 1 | 1.05 |