Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition

Sensors (Basel). 2020 Aug 13;20(16):4543. doi: 10.3390/s20164543.


Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove our argument. We also sample several scenes of these emotions from visual contents and control the contrast of the scenes. We manipulate the contrast of the scenes and measure the change of valence and arousal from human participants who watch the contents using a deep emotion recognition module based on electroencephalography (EEG) signals. As a result, we conclude that the enhancement of contrast induces the increase of valence, while the reduction of contrast induces the decrease. Meanwhile, the contrast control affects arousal on a very minute scale.

Keywords: Dataset for Emotion Analysis using Physiological Signals (DEAP); EEG; contrast; convolutional neural network (CNN); emotion; visual contents.

MeSH terms

  • Arousal
  • Electroencephalography*
  • Emotions*
  • Female
  • Humans
  • Interior Design and Furnishings
  • Male