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Emotion Recognition System Based on Facial Expressions Using SVM

  • Ielaf Osaamah Abdul-MajjedEmail author
Conference paper
  • 312 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 555)

Abstract

In recent years, there has been a growing interest in improving all aspects of interactions between human and computers particularly in the area of human expression recognition. In this work, we design a robust system by combining various techniques from computer vision and pattern recognition. Our system is divided into four modules started with image preprocessing, followed by feature extraction including Prewitt. Subsequently, the feature selection module has been performed as a third step using the sequential forward selection (SFS). Finally, support vector machine (SVM) is used as a classifier. Training and testing have been done on the Radboud Faces Database. The goal of the system was attaining the highest possible classification rate for the seven facial expressions (neutral, happy, sad, surprise, anger, disgust, and fear). 75.8% recognition accuracy was achieved on training dataset.

Keywords

Facial expressions SVM SFS Emotion recognition 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Computer Science, College of Computer Science and MathematicsUniversity of MosulMosulIraq

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