Multimodal Engagement Classification for Affective Cinema

This paper describes a multimodal approach to detect viewers' engagement through psycho-physiological affective signals. We investigate the individual contributions of the different modalities, and report experimental results obtained using several fusion strategies, in both per-clip and per-subject cross-validation settings. A sequence of clips from a short movie was showed to 15 participants, from whom we collected per-clip engagement self-assessments. Cues of the users' affective states were collected by means of (i) galvanic skin response (GSR), (ii) automatic facial tracking, and (iii) electroencephalogram (EEG) signals. The main findings of this study can be summarized as follows: (i) each individual modality significantly encodes the level of engagement of the viewers in response to movie clips, (ii) the GSR and EEG signals provide comparable contributions, and (iii) the best performance is obtained when the three modalities are used together.