Özet
In this study, facial expression recognition is defined as a pair matching problem. Our objectives to formulate this talk in this way are to be able to decide whether the facial expressions of the unlabeled images of two people are the same or different and to benefit from the proposed pair matching methods that have been studied for many years in the face recognition field. The Extended Cohn-Kanade (CK+) dataset which is commonly used for classification of facial expression is chosen to obtain match and mismatch pairs. To provide a baseline approach for the proposed pair matching formulation, in our paper, feature extraction by using local binary pattern is applied and match and mismatch facial expressions are classified by using support vector machines. 99.28% matching accuracy was achieved.
Tercüme edilen katkı başlığı | Facial expression pair matching |
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Orijinal dil | Türkçe |
Ana bilgisayar yayını başlığı | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Elektronik) | 9781509064946 |
DOI'lar | |
Yayın durumu | Yayınlandı - 27 Haz 2017 |
Etkinlik | 25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey Süre: 15 May 2017 → 18 May 2017 |
Yayın serisi
Adı | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 |
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???event.eventtypes.event.conference??? | 25th Signal Processing and Communications Applications Conference, SIU 2017 |
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Ülke/Bölge | Turkey |
Şehir | Antalya |
Periyot | 15/05/17 → 18/05/17 |
Bibliyografik not
Publisher Copyright:© 2017 IEEE.
Keywords
- facial expression pair matching
- local binary pattern
- support vector machine