Md. Zahangir Alom and Mei-Lan Piao and Md. Ashraful Alam and Nam Kim and Jae-Hyeung Park
Facial Expressions Recognition from Complex Background using Face Context and Adaptively Weighted subPattern PCA
418 - 423
2012
6
3
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/7541
https://publications.waset.org/vol/63
World Academy of Science, Engineering and Technology
A new approach for facial expressions recognition based on face context and adaptively weighted subpattern PCA (AwSpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, AwSpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. AwSpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.
Open Science Index 63, 2012