TY - GEN
T1 - Yüz Ifadesi Çifti Eşleştirme
AU - Engin, Deniz
AU - Ekenel, Hazim Kemal
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/27
Y1 - 2017/6/27
N2 - 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.
AB - 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.
KW - facial expression pair matching
KW - local binary pattern
KW - support vector machine
UR - http://www.scopus.com/inward/record.url?scp=85026329408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85026329408&partnerID=8YFLogxK
U2 - 10.1109/SIU.2017.7960646
DO - 10.1109/SIU.2017.7960646
M3 - Conference contribution
AN - SCOPUS:85026329408
T3 - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017
BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th Signal Processing and Communications Applications Conference, SIU 2017
Y2 - 15 May 2017 through 18 May 2017
ER -