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Talk · IEEE AITU: Digital Generation · April 3, 2024

Group Movie Selection using Multi-channel Emotion Recognition

Elnara Kadyrgali, Adilet Yerkin, Yerdauit Torekhan, Pakizar Shamoi

Yerdauit Torekhan
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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.

Recommender Systems and TechniquesEmotion and Mood RecognitionSentiment Analysis and Opinion Miningmusic emotion recognitionfilm postersfilm soundtrack

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