Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm

Xuan-Bac Nguyen, Gueesang Lee, Soo-Hyung Kim, Hyung-Jeong Yang

ICCVW 2019 pp. 3737-3741

doi:10.1109/ICCVW.2019.00464 /iccvw/2019/nguyen2019iccvw-audiovideo/

Abstract

In this paper, we present an efficient system for Audio-Video based emotion recognition with a limited dataset in the wild. To recognize the emotion, we use both acoustic and facial features mode together. To deal with Audio-Video data, we utilize both temporal and non-temporal information. To solve the problem of a small amount of dataset, we experiment from conventional methods to the deep learning-based methods. Finally, to address the unbalanced and skewed distribution problems, we apply a graph theory called Minimum Cost Flow Algorithm. By those approaches, our methods perform 61.56% on the test set in Audio-Video Emotion Recognition sub-challenge of 2019 Emotion Recognition in the Wild (Emotiw) Challenge and rank 5th among several teams.

ICCVW Semantic Scholar

Cite

Text

Nguyen et al. "Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00464

Markdown

[Nguyen et al. "Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/nguyen2019iccvw-audiovideo/) doi:10.1109/ICCVW.2019.00464

BibTeX

@inproceedings{nguyen2019iccvw-audiovideo,
  title     = {{Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm}},
  author    = {Nguyen, Xuan-Bac and Lee, Gueesang and Kim, Soo-Hyung and Yang, Hyung-Jeong},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2019},
  pages     = {3737-3741},
  doi       = {10.1109/ICCVW.2019.00464},
  url       = {https://mlanthology.org/iccvw/2019/nguyen2019iccvw-audiovideo/}
}