CG-MER: a card game-based multimodal dataset for emotion recognition

Nisrine Farhat; Amine Bohi; Leila Ben Letaifa; Rim Slama

doi:10.1117/12.3023377

3 April 2024 CG-MER: a card game-based multimodal dataset for emotion recognition

Nisrine Farhat, Amine Bohi, Leila Ben Letaifa, Rim Slama

Proceedings Volume 13072, Sixteenth International Conference on Machine Vision (ICMV 2023); 130721C (2024) https://doi.org/10.1117/12.3023377
Event: Sixteenth International Conference on Machine Vision (ICMV 2023), 2023, Yerevan, Armenia

Abstract

The field of affective computing has seen significant advancements in exploring the relationship between emotions and emerging technologies. This paper presents a novel and valuable contribution to this field with the introduction of a comprehensive French multimodal dataset designed specifically for emotion recognition. The dataset encompasses three primary modalities: facial expressions, speech, and gestures, providing a holistic perspective on emotions. Moreover, the dataset has the potential to incorporate additional modalities, such as Natural Language Processing (NLP) to expand the scope of emotion recognition research. The dataset was curated through engaging participants in card game sessions, where they were prompted to express a range of emotions while responding to diverse questions. The study included 10 sessions with 20 participants (9 females and 11 males). The dataset serves as a valuable resource for furthering research in emotion recognition and provides an avenue for exploring the intricate connections between human emotions and digital technologies.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Nisrine Farhat, Amine Bohi, Leila Ben Letaifa, and Rim Slama "CG-MER: a card game-based multimodal dataset for emotion recognition", Proc. SPIE 13072, Sixteenth International Conference on Machine Vision (ICMV 2023), 130721C (3 April 2024); https://doi.org/10.1117/12.3023377

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