This paper presents a new multimodal database and the associated results for
characterization of affect (valence, arousal and dominance) using the Magneto …

This paper presents characterization of affect (valence and arousal) using the
Magnetoencephalogram (MEG) brain signal. We attempt single-trial classification of movie …

Many algorithms and works have helped in the understanding and development of affective
analysis of films. In spite of the progress made up to now, it is still not very precise how the …

This paper describes a multimodal approach to detect viewers' engagement through psycho-
physiological affective signals. We investigate the individual contributions of the different …

We present a multimodal data set for the analysis of human affective states. The
electroencephalogram (EEG) and peripheral physiological signals of 32 participants were …

In this work, we present DECAF-a multimodal data set for decoding user physiological
responses to affective multimedia content. Different from data sets such as DEAP [15] and …

In this paper, we propose an approach for affective ranking of movie scenes based on the
emotions that are actually felt by spectators. Such a ranking can be used for characterizing …

In this paper, we propose an approach for affective characterization of movie scenes based
on the emotions that are actually felt by spectators. Such a representation can be used to …

The precondition of productive data mining is having an efficient database to work on. The
BioVid Emo DB is a multimodal database recorded for the purpose of analyzing human …

Implicit emotion tagging is a central theme in the area of affective computing. To this end,
Several physiological signals acquired from subjects can be employed, for example …