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General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(3): 309-312 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.328

Component-Based Real Time Facial Expression Recognition in Video Streams

Sara Alipour and Afsane Fathi
Abstract—In this article a new real-time approach is proposed to recognize facial expression in video database. First, face motion direction is estimated by using motion information and then according to the face width and direction, rectangular surrounding box is formed. The advantage of this method compared with previous methods is in improving classic rectangular surrounding box model and also, using the Steerable filters to determine face direction. As eyes and mouth are the most important components in a face, in this method, eye location is calculated by combining color features and morphological functions in surrounding box region. Afterwards, with regard to the lip contour and using image processing techniques, we are able to determine the detection of mouth very accurately with the help of four points. Finally, these features are modeled by using support vector machines (SVM). Experimental results show that this algorithm is more efficient than the previous ones.

Index Terms—Facial expression recognition, rectangular surrounding model, support vector machines.

Sara Alipour is with the Young Researchers Club, Islamic Azad University, Qazvin Branch, Qazvin, Iran (e-mail: alipour62@ yahoo.com). Afsane Fathi is with the Islamic Azad University, Qazvin, Iran (e-mail: Afsane.fathi@hotmail.com).


Cite:Sara Alipour and Afsane Fathi, "Component-Based Real Time Facial Expression Recognition in Video Streams," International Journal of Machine Learning and Computing vol.3, no. 3, pp. 309-312, 2013.

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