基于MobileNetV3多尺度特征融合的人脸表情识别
DOI:
CSTR:
作者:
作者单位:

新疆大学电气工程学院 乌鲁木齐 830017

作者简介:

通讯作者:

中图分类号:

TP391

基金项目:

国家自然科学基金(61866037,61462082)项目资助


Facial expression recognition based on MobileNetV3 multi-scale feature fusion
Author:
Affiliation:

School of Electrical Engineering, Xinjiang University,Urumqi 830017, China

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对人脸表情识别中普通卷积神经网络特征提取能力不足且识别效率低下的情况,本文提出了一种基于MobileNetV3多尺度特征融合的人脸表情识别。首先利用MobileNetV3进行特征提取以获得高层次情感信息;其次在骨干网络中借鉴DenseNet结构,增强特征复用并提升网络重要面部特征表达能力;然后利用特征金字塔模块充分获取人脸图像的深层和浅层多尺度融合特征,从而提高了MobileNetV3的特征提取能力和实时性;最后利用全连接层构建分类器对表情进行分类,从而完成了人脸表情识别。通过实验验证,结果表明,在CK+和FERPlus数据集上识别准确率可以达到88.3%和98.8%,与现有方法相比分别提高了2.3%和1.5%,表明了所提方法识别效果好,泛化能力强。

    Abstract:

    In view of the lack of feature extraction ability and low recognition efficiency of common convolutional neural network in facial expression recognition, this paper proposes a facial expression recognition based on multi-scale feature fusion of MobileNetV3. Firstly, MobileNetV3 was used for feature extraction to obtain high-level emotion information. Secondly, the DenseNet structure is used in the backbone network to enhance feature reuse and improve the expression ability of important facial features. Then the feature pyramid module is used to fully obtain the deep and shallow multi-scale fusion features of face images, so as to improve the feature extraction ability and real-time performance of MobileNetV3. Finally, the full connection layer is used to construct a classifier to classify the facial expression, so as to complete the facial expression recognition. Through experimental verification, the results show that the recognition accuracy on CK+and FERPlus datasets can reach 88.3% and 98.8%, which are improved by 2.3% and 1.5% respectively compared with the existing methods, indicating that the proposed method has good recognition effect and strong generalization.

    参考文献
    相似文献
    引证文献
引用本文

薛志超,伊力哈木·亚尔买买提,闫天星.基于MobileNetV3多尺度特征融合的人脸表情识别[J].电子测量技术,2023,46(8):38-44

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2024-02-07
  • 出版日期:
文章二维码
×
《电子测量技术》
财务封账不开票通知