ABSTRACT
Human facial expression can convey rich information, let the computer understand the human intention, and make correct responses through facial expression recognition, which is a hot spot in artificial intelligence research at present. Compared with a single frame image, a video sequence image contains the information of expression changing along the time axis, which can provide more help for expression recognition. Therefore, this paper proposes an expression recognition method based on video sequence images. Firstly, the facial landmark points are extracted from the sequence images. Secondly, four key regions that contribute greatly to expression recognition are calculated through the landmark points. Then the LBP features of these four regions are calculated and fused to form the expression features of a single frame image. Finally, these expression features are sequentially sent to the GRU network for training to obtain the face expression classification model. The experimental results show that the proposed algorithm has high recognition accuracy.
- Mehrabian.1968. A.Communication without words[J].Psychological Today,1968(2):53-55Google Scholar
- Ekman.P and Friesen.W.V. 1971. Constants across cultures in the face and emotion[J].Journal of Personality & Social Psychology,1971,17(2):124-129.Google Scholar
- Yong.Li,Xiaozhu.Lin and Mengying.Jiang.2018. Facial expression recognition based on cross connected lenet-5 network[J]. Acta Automatica Sinica,2018,44(1):176-182Google Scholar
- Mingdu.Ding and Lin.Li.2020. Facial expression recognition based on CNN and hog feature fusion [J]. Information and control, 2020, 49 (1):47-54Google Scholar
- Dapeng.Jiang, Biao.Yang and Ling.Zou. 2018.Facial expression recognition based on LBP convolutional neural network [J]. Computer Engineering and Design, 2018, 39 (7):1971-1977Google Scholar
- Min.Hu, Wendi.Teng, Xiaohua.Wang and Liangfeng.Xu.2018. Facial expression recognition based on local texture and shape features [J]. Journal of Electronics & Information Technology, 2018, 40 (6):1338-1344Google Scholar
- Liwen.Huang, Huanhuan.Yang and Bo.Wang.2018.Asymmetric directional local binary pattern facial expression recognition [J]. Computer Engineering and Applications, 2018, 54 (23): 183-188Google Scholar
- Hong.Shao, Yang.Wang and Yi.Wang.2017.Dynamic sequential expression recognition based on AM and optical flow [J]. Computer Engineering and Design, 2017, 38 (6): 1642-1647Google Scholar
- Tian.Xia, Yifeng.Zhang and Yuan.Liu. Expression recognition based on joint training of feature points and multiple networks [J]. Journal of Computer-Aided Design & Computer Graphics, 2019, 31(4): 552-559Google ScholarCross Ref
- Suqin.Wang, Feng.Zhang, Yudou.Gao and Min.Shi.2020.Learning expression recognition based on image sequence [J]. Journal of System Simulation, https://doi.org/10.16182/j.issn1004731x.joss.19-VR0470Google Scholar
- Xiaohua.Wang, Chen.Xia, Min.Hu and Fuji.Ren. 2018.Video Sequence Emotion Recognition Combining Spatial and Temporal Characteristics [J]. Journal of Electronics & Information Technology, 2018,40(3): 626-632Google Scholar
- LUCEY P, COHN J F, KANADE T, 2010. The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression[C]. 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), California, USA,2010: 94-101. doi: 10.1.1.182.3759.Google Scholar
Recommendations
Image ratio features for facial expression recognition application
Special issue on game theoryVideo-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised ...
Person-Similarity Weighted Feature for Expression Recognition
Computer Vision – ACCV 2007AbstractIn this paper, a new method to extract person-independent expression feature based on HOSVD (Higher-Order Singular Value Decomposition) is proposed for facial expression recognition. With the assumption that similar persons have similar facial ...
A simple approach to facial expression recognition
CEA'07: Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and ApplicationsHuman face-to-face communication plays an important role in human communication and interaction. In recent years, several different approaches have been proposed for developing methods of automatic facial expression analysis. In this paper, a simple ...
Comments