Facial Expression Recognition using Neural Network –An Overview
Pushpaja V. Saudagare1, D.S. Chaudhari2
1Pushpaja V. Saudagare, Eectronics and Telecommunication Dept. Amravati University, GCOE Amravati, India.
2Devendra S. Chaudhari, Electronics and Telecommunication Dept, BE, ME, from Marathwada University, Aurangabad and PhD from Indian Institute of Technology, Bombay, Mumbai, India.
Manuscript received on February 15, 2012. | Revised Manuscript received on February 20, 2012. | Manuscript published on March 05, 2012. | PP: 224-227 | Volume-2 Issue-1, March 2012. | Retrieval Number: A0419022112/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In many face recognition systems the important part is face detection. The task of detecting face is complex due to its variability present across human faces including color, pose, expression, position and orientation. So using various modeling techniques it is convenient to recognize various facial expressions. In the field of image processing it is very interesting to recognize the human gesture by observing the different movement of eyes, mouth, nose, etc. Classification of face detection and token matching can be carried out any neural network for recognizing the facial expression. This paper reviews various techniques of facial expression recognition systems using MATLAB (neural network) toolbox.
Keywords: Face recognition, neural network, and facial expression recognition.