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Convolutional Neural Networks based Method for Improving Facial Expression Recognition

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Intelligent Systems Technologies and Applications 2016 (ISTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 530))

Abstract

Recognizing facial expressions via algorithms has been a problematic mission among researchers from fields of science. Numerous methods of emotion recognition were previously proposed based on one scheme using one data set or using the data set as it is collected to evaluate the system without performing extra preprocessing steps such as data balancing process that is needed to enhance the generalization and increase the accuracy of the system. In this paper, a technique for recognizing facial expressions using different imbalanced data sets of facial expression is presented. The data is preprocessed, then, balanced, next, a technique for extracting significant features of face is implemented. Finally, the significant features are used as inputs to a classifier model. Four main classifier models are selected, namely; Decision Tree (DT), Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN). The Convolutional Neural Network is determined to produce the best recognition accuracy.

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Author information

Authors and Affiliations

  1. Software and Informatics Engineering, Salahaddin University, Kurdistan, Erbil, Iraq

    Tarik A. Rashid

Authors
  1. Tarik A. Rashid
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Correspondence to Tarik A. Rashid .

Editor information

Editors and Affiliations

  1. Dept. of CS, School of Science, University of Salamanca Dept. of CS, School of Science, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  2. Machine Intelligence Unit, Indian Statistical Institute Machine Intelligence Unit, Kolkata, India

    Sushmita Mitra

  3. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  4. King Fahd Univ of Petroleum and Minerals , Dhahran, Saudi Arabia

    El-Sayed El-Alfy

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© 2016 Springer International Publishing AG

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Rashid, T.A. (2016). Convolutional Neural Networks based Method for Improving Facial Expression Recognition. In: Corchado Rodriguez, J., Mitra, S., Thampi, S., El-Alfy, ES. (eds) Intelligent Systems Technologies and Applications 2016. ISTA 2016. Advances in Intelligent Systems and Computing, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-319-47952-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-47952-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47951-4

  • Online ISBN: 978-3-319-47952-1

  • eBook Packages: EngineeringEngineering (R0)

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