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
针对传统人脸识别方法在单样本条件下受姿态、表情、遮挡和光照影响识别效果不佳等问题,提出一种改进的纹理特征和边缘特征相结合的人脸描述算子ε-WLBD(ε-Weber Local Binary Descriptor)。先用改进的局部二值模式和改进的Kirsch算子...针对传统人脸识别方法在单样本条件下受姿态、表情、遮挡和光照影响识别效果不佳等问题,提出一种改进的纹理特征和边缘特征相结合的人脸描述算子ε-WLBD(ε-Weber Local Binary Descriptor)。先用改进的局部二值模式和改进的Kirsch算子进行纹理特征和边缘特征提取,然后分别进行直方图统计,并将其串接起来作为人脸识别的总体特征向量,最后利用最近邻算法进行分类识别。在YALE和AR人脸库上进行测试,实验结果表明所提方法简单有效,且对姿态、表情、遮挡和光照等变化具有较强鲁棒性,对单样本人脸描述具有较好的效果。展开更多
基金Supported by the National Natural Science Foundation of China(60772066)
文摘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.
文摘针对传统人脸识别方法在单样本条件下受姿态、表情、遮挡和光照影响识别效果不佳等问题,提出一种改进的纹理特征和边缘特征相结合的人脸描述算子ε-WLBD(ε-Weber Local Binary Descriptor)。先用改进的局部二值模式和改进的Kirsch算子进行纹理特征和边缘特征提取,然后分别进行直方图统计,并将其串接起来作为人脸识别的总体特征向量,最后利用最近邻算法进行分类识别。在YALE和AR人脸库上进行测试,实验结果表明所提方法简单有效,且对姿态、表情、遮挡和光照等变化具有较强鲁棒性,对单样本人脸描述具有较好的效果。
