Robust facial feature points extraction in color images

Authors:
Yue Zhou;Yin Li;Zheng Wu;Meilin Ge
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China
Venue:
Engineering Applications of Artificial Intelligence
Year:
2011

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Abstract

A method of facial feature points extraction based on improved active appearance model (AAM) with Gabor wavelet features was presented in the paper. After the pre-processing of a standard face detector and lighting compensation, the paper proposed a hybrid AAM by combining the local skin similarity with the original local grey-level appearance model. Moreover, the feature points by the hybrid AAM and their neighbors were considered by a classification problem to further refine the results. Namely, the Gabor feature around the feature points was extracted, trained by linear discriminant analysis (LDA) and classified by K Nearest Neighbor (KNN) to give the precise location of the feature points. Experimental results indicated that facial feature points can be located robustly and precisely by the proposed method.