Automatic group emotion recognition plays an important role in understanding complex human-human interaction. This paper introduces, Emolysis, a Python-based, standalone open-source group emotion analysis toolkit for use in different social situations upon getting consent from the users. Given any input video, Emolysis processes synchronized multimodal input and maps it to group level emotion, valence and arousal. Additionally, the toolkit supports major mobile and desktop platforms (Android, iOS, Windows). The Emolysis platform also comes with an intuitive graphical user interface that allows users to select different modalities and target persons for more fine-grained emotion analysis. Emolysis is freely available for academic research and encourages application developers to extend it to application specific environments on top of the existing system. We believe that the extension mechanism is quite straightforward. Our code models and interface are available at https://github.com/ControlNet/emolysis.
@article{arxiv.2305.05255,
title = {Emolysis: A Multimodal Open-Source Group Emotion Analysis and Visualization Toolkit},
author = {Shreya Ghosh and Zhixi Cai and Parul Gupta and Garima Sharma and Abhinav Dhall and Munawar Hayat and Tom Gedeon},
journal= {arXiv preprint arXiv:2305.05255},
year = {2024}
}
Comments
Accepted by ACII Demo 2024. Both Shreya Ghosh and Zhixi Cai contributed equally to this research