DocumentCode :
3756846
Title :
A Model of Local Binary Pattern Feature Descriptor for Valence Facial Expression Classification
Author :
Ruth Agada;Jie Yan
Author_Institution :
Dept. of Comput. Sci., Bowie State Univ., Bowie, MD, USA
fYear :
2015
Firstpage :
634
Lastpage :
639
Abstract :
Recognition of spontaneous emotion would significantly influence human-computer interaction and emotion-related studies in many related fields. This paper endeavors to explore a holistic method for detecting emotional facial expressions by examining local features. In recent years, examining local features has gained traction for nuanced expression detection. The local binary pattern is one such technique. Using the modified LBP adds a discriminating factor to the examined feature via the addition of an edge detector. Hence, the edge based local binary pattern for the extraction of features in the human face. Using this method, the extracted feature is classified into its valence classes (positive and negative) using an SVM classifier.
Keywords :
"Image edge detection","Feature extraction","Face","Support vector machines","Histograms","Kernel","Databases"
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on
Type :
conf
DOI :
10.1109/ICMLA.2015.185
Filename :
7424389
Link To Document :
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