Facial Expression Recognition Based on Dual-Channel Fusion with Edge Features

被引：6
作者：
Tang, Xiaoyu [1 ,2 ]
Liu, Sirui [1 ]
Xiang, Qiuchi [2 ]
Cheng, Jintao [1 ]
He, Huifang [3 ]
Xue, Bohuan [4 ]
机构：
[1] South China Normal Univ, Sch Phys & Telecommun Engn, Guangzhou 510006, Peoples R China
[2] South China Normal Univ, Xingzhi Coll, Shanwei 516600, Peoples R China
[3] Guangdong Engn Polytech, Guangzhou 510520, Peoples R China
[4] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Hong Kong, Peoples R China
来源：
SYMMETRY-BASEL | 2022年 / 14卷 / 12期
关键词：
facial expression recognition; channel weighting; feature fusion; edge detection; SCALE;
D O I：
10.3390/sym14122651
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
In the era of artificial intelligence, accomplishing emotion recognition in human-computer interaction is a key work. Expressions contain plentiful information about human emotion. We found that the canny edge detector can significantly help improve facial expression recognition performance. A canny edge detector based dual-channel network using the OI-network and EI-Net is proposed, which does not add an additional redundant network layer and training. We discussed the fusion parameters of alpha and beta using ablation experiments. The method was verified in CK+, Fer2013, and RafDb datasets and achieved a good result.
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页数：12
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