Emotion Recognition on Multi View Static Action Videos Using Multi Blocks Maximum Intensity Code (MBMIC)

R. Santhoshkumar and M. Kalaiselvi Geetha
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R. Santhoshkumar: Annamalai University, Department of Computer Science and Engineering
M. Kalaiselvi Geetha: Annamalai University, Department of Computer Science and Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1143-1151 from Springer

Abstract: Abstract Recognition of emotions from human plays a vital role in our day to day life and is essential for social communication. In many application of human computer interaction non-verbal communication method like body movements, facial expression, eye movements and gestures are used. Among these methods body movements is widely used because it conveys the emotions of human from all views of camera. In this paper Multi Block Maximum Intensity Code (MBMIC) feature is proposed for emotion recognition from human body movements. The GEMEP corpus (straight and side view) videos are used for this experiment. The 36 dimensions MBMIC features were extracted from the motion of body movements of the human present in the difference frame. The extracted features are fed to the Random Forest classifier to predict the human emotions. The performance measure can be calculated using qualitative and quantitative analysis.

Keywords: Emotion recognition; Non-verbal communication; Body movements; Multi blocks maximum intensity code (MBMIC); Random Forest classifier (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_116

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DOI: 10.1007/978-3-030-41862-5_116

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