Facial Expression Recognition for Human Computer Interaction

Joyati Chattopadhyay, Souvik Kundu, Arpita Chakraborty and Jyoti Sekhar Banerjee
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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

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1181-1192 from Springer

Abstract: 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.

Keywords: Features extraction; Facial expressions; Emotion recognition; Face detection; SVM classifier (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_119

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DOI: 10.1007/978-3-030-41862-5_119

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