Deep Facial Emotion Recognition Using Local Features Based on Facial Landmarks for Security System  

作　　者：Youngeun An Jimin Lee Eunsang Bak Sungbum Pan 

机构地区：[1]IT Research Institute,Chosun University,Gwang-Ju,61452,Korea

出　　处：《Computers, Materials & Continua》2023年第8期1817-1832,共16页计算机、材料和连续体（英文）

基　　金：supported by the Healthcare AI Convergence R&D Program through the National IT Industry Promotion Agency of Korea(NIPA)funded by the Ministry of Science and ICT(No.S0102-23-1007);the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2017R1A6A1A03015496).

摘　　要：Emotion recognition based on facial expressions is one of the most critical elements of human-machine interfaces.Most conventional methods for emotion recognition using facial expressions use the entire facial image to extract features and then recognize specific emotions through a pre-trained model.In contrast,this paper proposes a novel feature vector extraction method using the Euclidean distance between the landmarks changing their positions according to facial expressions,especially around the eyes,eyebrows,nose,andmouth.Then,we apply a newclassifier using an ensemble network to increase emotion recognition accuracy.The emotion recognition performance was compared with the conventional algorithms using public databases.The results indicated that the proposed method achieved higher accuracy than the traditional based on facial expressions for emotion recognition.In particular,our experiments with the FER2013 database show that our proposed method is robust to lighting conditions and backgrounds,with an average of 25% higher performance than previous studies.Consequently,the proposed method is expected to recognize facial expressions,especially fear and anger,to help prevent severe accidents by detecting security-related or dangerous actions in advance.

关 键 词：Facial emotion recognition landmark-based feature extraction ensemble network robustness to the changes in illumination and background dangerous situation detection accident prevention 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]