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Facial Expression Recognition for Human Computer Interaction

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

Author

Listed:
  • Joyati Chattopadhyay

    (Techno International Newtown, Department of ECE)

  • Souvik Kundu

    (Iowa State University, Department of Electrical and Computer Engineering)

  • Arpita Chakraborty

    (Bengal Institute of Technology, Department of ECE)

  • Jyoti Sekhar Banerjee

    (Bengal Institute of Technology, Department of ECE)

Abstract

Facial expressions consisting of various emotions play a significant role in interpersonal relations. Emotion detection from various expressions of the face can be performed broadly in three major steps which involve face detection-normalization, extraction of features and classification. An automated facial expression detection methodology has been introduced by the authors in this letter. Here, after face detection and normalization we extract three different types of facial features: Geometric, Texture and Structural. Based on these extracted features we employ SVM classifier to separate the face expressions which includes Happy, Sad, Disgust, Angry, Surprise and Fear. We have applied our algorithm on two databases: JAFFE and COHEN. We have successfully detected over 80% expressions from JAFFE and COHEN database.

Suggested Citation

  • Joyati Chattopadhyay & Souvik Kundu & Arpita Chakraborty & Jyoti Sekhar Banerjee, 2020. "Facial Expression Recognition for Human Computer Interaction," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1181-1192, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_119
    DOI: 10.1007/978-3-030-41862-5_119
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