Title :
Edge based mean LBP for valence facial expression detection
Author :
Agada, Ruth ; Jie Yan
Author_Institution :
Comput. Sci. Dept., Bowie State Univ., Bowie, MD, USA
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 mu LBP, this modified mean LBP adds a discriminating factor to the examined feature via the addition of an edge detector. Hence, the Sobel based μ 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 :
emotion recognition; face recognition; feature extraction; human computer interaction; support vector machines; SVM classifier; edge detector; emotion recognition; feature extraction; holistic method; human computer interaction; local binary pattern; local features; mean LBP; valence facial expression detection; Accuracy; Face; Feature extraction; Image edge detection; Kernel; Support vector machines; Local binary pattern; SVM; feature extraction; imporved local binary pattern; sobel edges;
Conference_Titel :
Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6084-2
DOI :
10.1109/ICECCT.2015.7226014