Group Movie Selection using Multi-channel Emotion Recognition
2024 IEEE AITU: Digital Generation, pp. 85–91
Elnara Kadyrgali, Adilet Yerkin, Yerdauit Torekhan, Pakizar Shamoi
School of Information Technology and Engineering, Kazakh-British Technical University
Abstract
Social activities often done in groups include watching television or movies. Choosing a film that appeals to the emotional inclinations of a varied group can be tricky. One of the most difficult aspects of making group movie suggestions is achieving agreement among members. At the same time, emotion is the most important component that connects the film and the viewer. Current research proposes a methodology for group movie selection that employs emotional analysis from numerous sources, such as film posters, soundtracks, and text. Our research stands at the intersection of emotion recognition technology in music, text, color images, and group decision-making, providing a practical tool for navigating the complex dynamics of film selection in a group setting. The survey participants were given emotion categories and asked to select the emotions that best suited a particular movie. Preliminary comparison results between real and predicted scores show the effectiveness of using emotion detection for group movie recommendation. Such systems have the potential to enhance movie recommendation systems.
Method
Emotion across music, text and color
The work sits at the intersection of four areas that rarely meet: emotion recognition in music, in text, in color images, and group decision-making. A film is described emotionally from its poster, its soundtrack and its written text, and those descriptions are what the group decision is made over.
Survey design
Participants were given a set of emotion categories and asked which best suited a particular film. Their answers form the ground truth against which the multi-channel predictions are compared.
Results
Preliminary but consistent
Comparing real against predicted scores showed emotion detection to be an effective basis for group movie recommendation. The paper is explicit that these results are preliminary — the follow-up work extended them into a full consensus framework with a larger survey and a measured Jaccard index.
Key points
- Best Paper Award, IEEE AITU: Digital Generation 2024.
- Multi-channel emotion recognition: posters, soundtracks, text.
- Sits between emotion recognition and group decision-making.
- Survey-based ground truth from participant emotion selections.
- Preliminary results; extended by the consensus-reaching paper.
Cite
@inproceedings{kadyrgali2024group,
title = {Group Movie Selection using Multi-channel Emotion Recognition},
author = {Kadyrgali, Elnara and Yerkin, Adilet and Torekhan, Yerdauit and
Shamoi, Pakizar},
booktitle = {2024 IEEE AITU: Digital Generation},
pages = {85--91},
year = {2024},
doi = {10.1109/IEEECONF61558.2024.10585521}
}