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| Face Image Analysis Based on Multiple Separated Component Sparse Coding |
| LIU Wei-Feng,LIU Hong-Li,WANG Yan-Jiang |
| College of Information and Control Engineering,China University of Petroleum East China,Qingdao 266580 |
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Abstract Considering the different contributions of different facial components to face analysis,e.g. eyes,mouth etc.,a face analysis based on multi-component sparse coding is proposed. Firstly,some facial components which play important role to face analysis are selected. Then,the dictionaries of multiple components are learnt by using multi-view sparse coding algorithm,and the sparse codes of each face image are computed based on the dictionary. The final decision is made through pooling the sparse codes into support vector machines and least squares classifiers. Face analysis experiments include face recognition,facial expression recognition,face recognition with occlusion,and facial expression recognition with occlusion. The experimental results show that the proposed method based on multi-component sparse coding learns optimal weights of different facial components and outperforms single facial component method and simple multi-component fusion method.
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Received: 12 December 2012
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2013, Vol. 26 
