A literature survey on Facial Expression Recognition using Global Features
Vaibhav kumar J. Mistry1, Mahesh M. Goyani2
1Vaibhav kumar J. Mistry, Department of Information Technological University, Gujarat, India.
2Mahesh M. Goyani, Department of Computer Science, Technological University, Gujarat, India.
Manuscript received on March 02, 2013. | Revised Manuscript received on April 13, 2013. | Manuscript published on April 30, 2013. | PP: 653-657 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1563042413/2013©BEIESP
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© The Authors. 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: Facial Expression Recognition (FER) is a rapidly growing and ever green research field in the area of Computer Vision, Artificial Intelligent and Automation. There are many application which uses Facial Expression to evaluate human nature, feelings, judgment, opinion. Recognizing Human Facial Expression is not a simple task because of some circumstances due to illumination, facial occlusions, face color/shape etc. In these paper, we present some method/techniques such as Principal Component Analysis (PCA), Linear Discriminate Analysis (LDA), Gabor Filter/Energy, Line Edge Mapping (LEM), Neural Network, Independent Component Analysis (ICA) which will directly or/and indirectly used to recognize human expression in various condition.
Keywords: Facial Expression, Expression Recognition, Gabor Filter, Gabor Energy, Principal Component Analysis, Neural Network, Eigenface.