OMG - Emotion Challenge Solution

Abstract--This short paper describes our solution to the 2018 IEEE World Congress on Computational Intelligence One-Minute Gradual-Emotional Behavior Challenge, whose goal was to estimate continuous arousal and valence values from short videos. We designed four base regression models using visual and audio features, and then used a spectral approach to fuse them to obtain improved performance. (IEEE WCCI 2018). The dataset was composed of 420 relatively long emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Videos were separated into clips based on utterances, and each utterance's valence and arousal levels were annotated by at least five independent subjects using the Amazon Mechanical Turk tool.