基于过渡帧概念训练的微表情检测深度网络

付晓峰,牛力,胡卓群,李建军,吴卿

Deep micro-expression spotting network training based on concept of transition frame

Xiao-feng FU,Li NIU,Zhuo-qun HU,Jian-jun LI,Qing WU

表 4 CASME II数据库上MesNet与已有方法的性能对比

Tab.4 Performance comparison among MesNet and existing methods on CASME II

方法 Precision Recall F-Measure Accuracy AUC 3D HOG – XT[29] 0.534 1 0.623 5 0.575 4 0.735 5 0.726 1 Frame differences[14] − − − 0.817 5 − HOOF[30] − − − − 0.649 9 LBP[30] − − − − 0.929 8 CFD[28] − − − − 0.941 9 MesNet 0.939 6 0.947 8 0.943 7 0.914 6 0.955 6