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2020 | OriginalPaper | Chapter

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

Authors : R. Santhoshkumar, M. Kalaiselvi Geetha

Published in: New Trends in Computational Vision and Bio-inspired Computing

Publisher: Springer International Publishing

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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.

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previous chapter Multimodal Medical Image Fusion Using Discrete Fractional Wavelet Transform (DFRWT) with Non-subsampled Contourlet Transform (NSCT) Hybrid Fusion Algorithm
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Metadata
Title
Emotion Recognition on Multi View Static Action Videos Using Multi Blocks Maximum Intensity Code (MBMIC)
Authors
R. Santhoshkumar
M. Kalaiselvi Geetha
Copyright Year
2020
Publisher
Springer International Publishing
Book
New Trends in Computational Vision and Bio-inspired Computing

Print ISBN: 978-3-030-41861-8

Electronic ISBN: 978-3-030-41862-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-41862-5_116

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