Human-Computer Interaction Using Deep Fusion Model-Based Facial Expression Recognition System

查看全文 作　　者：Saiyed [1]Umer;Ranjeet Kumar [2]Rout;Shailendra [3]Tiwari;Ahmad Ali [4]AlZubi;Jazem Mutared [4]Alanazi;Kulakov [5]Yurii 机构地区：[1]Department of Computer Science&Engineering,Aliah University,Kolkata,700156,India;[2]Department of Computer Science and Engineering,National Institute of Technology,Srinagar,Jammu and Kashmir,190006,India;[3]Department of Computer Science&Engineering,Thapar University,Patiala,147004,India;[4]Computer Science Department,King Saud University,Riyadh,11451,Saudi Arabia;[5]Department of Computer Engineering,National Technical University of Ukraine,Igor Sikorsky Kyiv Polytechnic Institute,Kyiv,03056,Ukraine 出　　处：《Computer Modeling in Engineering & Sciences》索引2023年第5期,共21页 基　　金：supported by the Researchers Supporting Project (No.RSP-2021/395),King Saud University,Riyadh,Saudi Arabia. 摘　　要：A deep fusion model is proposed for facial expression-based human-computer Interaction system.Initially,image preprocessing,i.e.,the extraction of the facial region from the input image is utilized.Thereafter,the extraction of more discriminative and distinctive deep learning features is achieved using extracted facial regions.To prevent overfitting,in-depth features of facial images are extracted and assigned to the proposed convolutional neural network(CNN)models.Various CNN models are then trained.Finally,the performance of each CNN model is fused to obtain the final decision for the seven basic classes of facial expressions,i.e.,fear,disgust,anger,surprise,sadness,happiness,neutral.For experimental purposes,three benchmark datasets,i.e.,SFEW,CK+,and KDEF are utilized.The performance of the proposed systemis compared with some state-of-the-artmethods concerning each dataset.Extensive performance analysis reveals that the proposed system outperforms the competitive methods in terms of various performance metrics.Finally,the proposed deep fusion model is being utilized to control a music player using the recognized emotions of the users. 关 键 词：Deep learning facial expression emotions RECOGNITION CNN