面向非特定表情的加权和稀疏分类方法

针对在非特定人脸表情识别中，表情纹理特征的利用率不高问题，提出了一种改进的加权局部二值模式（LBP）和稀疏表示相结合的人脸表情识别方法。为了有效利用面部器官的局部纹理信息，采用改进的加权LBP算子提取人脸局部纹理特征，然后用获取的特征值组成训练样本，最后根据稀疏表示理论进行表情分类。在 JAFFE和CK人脸库上的实验结果表明，该方法对非特定人脸表情的识别效果有了明显提高。

Nonspecific Facial Expression Recognition via the Sparse Representation and Weighted

On the person-independent facial expression recognition, the utilization rate of the facial expression texture is not high. Facing with the problem of the person-independent face, this paper proposes a method about facial expression recognition based on the improved weighted local binary pattern (LBP) and sparse representation. In order to use the local texture information of the facial organs effectively, first it uses the improved weighted LBP operator to extracting the local texture feature, the extracted features to construct the training samples, and classified via the sparse representation last. Experimental results show a better performance on the JAFFE and CK database.