基于多尺度特征选择网络的人脸表情识别

首先, 针对人脸表情识别问题提出一种新的多尺度特征选择网络识别方法, 该网络充分结合多尺度网络结构和特征选择结构的优点, 能更有效地提取面部静态图像中的空间信息. 其次, 为验证本文提出的多尺度特征选择网络的识别性能和泛化能力, 在两个经典的人脸表情识别数据集上与一些常用的方法进行对比和交叉验证实验. 实验结果表明, 该网络取得了更好的识别效果, 并且具有良好的泛化能力, 可以灵活地嵌入到人脸表情识别分析系统中.

Facial Expression Recognition Based on Multi-scale Feature Selection Network

Firstly, aiming at the problem of facial expression recognition, we proposed a new multi-scale feature selection network recognition method. The network fully combined the advantages of multi-scale network structure and feature selection structure, which could extract the spatial information in the facial static images more effectively. Secondly, in order to verify the recognition performance and generalization ability of the proposed multi-scale feature selection network, we carried out comparison and cross validation experiments with some common methods on two classical facial expression recognition databases. The experiment results show that the proposed network achieves better recognition effect and has good generalization ability, it can be flexibly embedded into the facial expression recognition and analysis system.