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Facial expression recognition with contextualized histograms
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作者 岳雷 沈庭芝 +2 位作者 杜部致 张超 赵三元 《Journal of Beijing Institute of Technology》 EI CAS 2015年第3期392-397,共6页
A new algorithm taking the spatial context of local features into account by utilizing contextualized histograms was proposed to recognize facial expression. The contextualized histograms were extracted fromtwo widely... A new algorithm taking the spatial context of local features into account by utilizing contextualized histograms was proposed to recognize facial expression. The contextualized histograms were extracted fromtwo widely used descriptors—the local binary pattern( LBP) and weber local descriptor( WLD). The LBP and WLD feature histograms were extracted separately fromeach facial image,and contextualized histogram was generated as feature vectors to feed the classifier. In addition,the human face was divided into sub-blocks and each sub-block was assigned different weights by their different contributions to the intensity of facial expressions to improve the recognition rate. With the support vector machine(SVM) as classifier,the experimental results on the 2D texture images fromthe 3D-BU FE dataset indicated that contextualized histograms improved facial expression recognition performance when local features were employed. 展开更多
关键词 facial expression recognition local binary pattern weber local descriptor spatial context contextualized histogram
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