Robust hybrid framework for automatic facial expression recognition

  • Authors

    • Gunavathi H S Jain University, Bangalore
    • Siddappa M SSIT, Tumkur
    2018-04-17
    https://doi.org/10.14419/ijet.v7i2.10764
  • Compressive sensing, facial expressions, feature extraction, HOG and LBP.

  • Abstract

    Over the last few years, facial expression recognition is an active research field, which has an extensive range of applications in the area of social interaction, social intelligence, autism detection and Human-computer interaction. In this paper, a   robust hybrid framework is presented to recognize the facial expressions, which enhances the efficiency and speed of recognition system by extracting significant features of a face. In the proposed framework, feature representation and extraction are done by using Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). Later, the dimensionalities of the obtained features are reduced using Compressive Sensing (CS) algorithm and classified using multiclass SVM classifier. We investigated the performance of the proposed hybrid framework on two public databases such as CK+ and JAFFE data sets. The investigational results show that the proposed hybrid framework is a promising framework for recognizing and identifying facial expressions with varying illuminations and poses in real time.

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  • How to Cite

    H S, G., & M, S. (2018). Robust hybrid framework for automatic facial expression recognition. International Journal of Engineering & Technology, 7(2), 568-572. https://doi.org/10.14419/ijet.v7i2.10764

    Received date: 2018-03-28

    Accepted date: 2018-04-06

    Published date: 2018-04-17