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Facial expression recognition from still images

Access

info:eu-repo/semantics/closedAccess

Date

2017

Author

Gazioglu, Bilge Suheyla Akkoca
Gökmen, Muhittin

Metadata

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Citation

Gazioglu, B. S. A., & Gokmen, M. (2017). Facial expression recognition from still images. Conference: 11th International Conference on Universal Access in Human-Computer Interaction (UAHCI) held as part of 19th International Conference on Human-Computer Interaction (HCI International) Location: Vancouver, CANADA. 10284, p.413-428

Abstract

With the development of technology, Facial Expression Recognition (FER) become one of the important research areas in Human Computer Interaction. Changes in the movement of some muscles in face create the facial expressions. By defining these changes, facial expressions can be recognized. In this study, a cascaded structure consists of Local Zernike Moments (LZM), Local XOR Patterns (LXP) and Global Zernike Moments (GZM) methods is proposed for the FER problem. The generally used database is the Extended Chon - Kanade (CK +) in FER problems. The database consists of image sequences of 327 expressions of 118 people. Most FER system includes recognition of 7 classes of emotions happiness, sadness, surprise, anger, disgust, fear and contempt, and we use Library of Support Vector Machines (LIBSVM) classifier for multi class classification with the leave one out cross-validation method. Our overall system performance is measured as 90.34% for FER.

Source

Conference: 11th International Conference on Universal Access in Human-Computer Interaction (UAHCI) held as part of 19th International Conference on Human-Computer Interaction (HCI International) Location: Vancouver, CANADA Date: JUL 09-14, 2017

Volume

10284

URI

http://dx.doi.org/10.1007/978-3-319-58628-1_32
https://hdl.handle.net/20.500.11779/725

Collections

  • Araştırma Çıktıları, Scopus İndeksli Yayınlar Koleksiyonu [429]
  • Araştırma Çıktıları, WOS İndeksli Yayınlar Koleksiyonu [470]
  • MF, BM, Bildiri ve Sunum Koleksiyonu [37]



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