Multimodal Affective Computing: Affective Information Representation, Modelling, and Analysis

Emotions Modelling in 3D Space

Author(s): Gyanendra K. Verma * .

Pp: 128-147 (20)

DOI: 10.2174/9789815124453123010013

* (Excluding Mailing and Handling)


In this study, we have discussed emotion representation in two and threedimensional space. The three-dimensional space is based on the three emotion primitives, i.e., valence, arousal, and dominance. The multimodal cues used in this study are EEG, Physiological signals, and video (under limitations). Due to the limited emotional content in videos from the DEAP database, we have considered only three classes of emotions, i.e., happy, sad, and terrible. The wavelet transforms, a classical transform, were employed for multi-resolution analysis of signals to extract features. We have evaluated the proposed emotion model with standard multimodal datasets, DEAP. The experimental results show that SVM and MLP can predict emotions in single and multimodal cues.

Keywords: Arousal, DEAP database, Dominance, EEG, Multiresolution analysis, Support vector machine, Valence.

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