基于并行Gan的有遮挡动态表情识别  

Dynamic Expression Recognition with Partial Occlusion Based on Parallel Gan

作　　者：杨鲁月 张树美 赵俊莉 YANG Luyue;ZHANG Shumei;ZHAO Junli(School of Data Science and Software Engineering,Qingdao University,Qingdao,Shandong 266071,China)

机构地区：[1]青岛大学数据科学与软件工程学院,山东青岛266071

出　　处：《计算机工程与应用》2021年第24期168-178,共11页Computer Engineering and Applications

基　　金：国家自然科学基金(61702293,41506198);虚拟现实应用教育部工程研究中心开发基金(MEOBNUEVRA201601)。

摘　　要：为了解决实际中动态表情识别存在的局部遮挡问题,提出一种基于并行Gan网络的有遮挡动态表情识别方法。构建一个并联网络P-IncepNet进行上下文特征提取,利用条件对抗网络训练了一个处理不同程度遮挡的图像修复网络。将构建的并联网络与LSTM进行级联,充分利用并联网络的特征提取和LSTM的时空信息获取能力,训练得到一个更具鲁棒性的动态表情识别网络。实验结果表明,在CelebA和MMI数据集上训练的局部遮挡补全网络对中小程度遮挡的补全优于其他网络;构建的级联表情识别网络对于不同程度遮挡的识别结果显示,修复表情图的平均识别率比未修复表情图高4.45个百分点,尤其愤怒、惊讶、高兴有6.36个百分点的较大识别率提升得益于遮挡图像的修复;在AFEW和MMI数据集的无遮挡实验表明,该网络对无遮挡的识别同样具有优越性能,平均识别准确率达51.12%和80.31%。因此构建的P-IncepNet是稳定的,对图像的遮挡修复和表情识别性能均有明显改善。In order to reduce the influence of partial occlusion in dynamic Facial Expression Recognition(FER),a method of dynamic FER with occlusion based on parallel Gan network is proposed.The P-IncepNet(Para Inception Network)constructed for context feature extraction is connected to the Gan,this connected net is trained for image repairing.The P-IncepNet is cascaded with LSTM to train a more robust dynamic FER network,which makes full use of the feature extraction of P-IncepNet and the Spatio-temporal information acquisition of the LSTM.The experimental results show that on CelebA and MMI datasets,the occlusion completion network is better than other networks for medium-sized occlu-sion.In the cascade expression recognition network,the average recognition rate of the repaired image is 4.45 percentage points higher than that of the unrepaired image.Especially with regard to anger,surprise and happy,6.36 percentage points of the recognition rates are improved due to the repair of the occlusion.The experiments on AFEW and MMI data-bases show that the dynamic FER network is also superior to other networks in uncovered recognition,the average recogni-tion is 51.12%and 80.31%.Therefore,the P-IncepNet is stable,and the performance of occlusion repair and expression rec-ognition is significantly improved.

关 键 词：局部遮挡 动态表情识别 深度学习 并行处理 级联网络 生成对抗网络 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]