{"title":"EmotiTEA:基于CNN面部情绪识别的视觉监控模块","authors":"Italo Oliveira, Jacqueline Lopes Silva, Facundo Palomino Quispe, Ana Beatriz Alvarez","doi":"10.1109/EIRCON52903.2021.9613399","DOIUrl":null,"url":null,"abstract":"The recognition of human facial emotions is a highly complex task and an open problem. This paper presents the EmotiTEA module that performs the recognition of facial emotions to be used in monitoring in real time. Two simple custom Convolutional Neural Networks (CNN) are studied, which were included in the module for specific tests. The results obtained under the test conditions indicate a satisfactory performance with the implemented CNNs and a promising behavior of the EmotiTEA module for the real time monitoring task.","PeriodicalId":403519,"journal":{"name":"2021 IEEE Engineering International Research Conference (EIRCON)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"EmotiTEA: A visual monitoring module based on the recognition of facial emotions with CNN\",\"authors\":\"Italo Oliveira, Jacqueline Lopes Silva, Facundo Palomino Quispe, Ana Beatriz Alvarez\",\"doi\":\"10.1109/EIRCON52903.2021.9613399\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recognition of human facial emotions is a highly complex task and an open problem. This paper presents the EmotiTEA module that performs the recognition of facial emotions to be used in monitoring in real time. Two simple custom Convolutional Neural Networks (CNN) are studied, which were included in the module for specific tests. The results obtained under the test conditions indicate a satisfactory performance with the implemented CNNs and a promising behavior of the EmotiTEA module for the real time monitoring task.\",\"PeriodicalId\":403519,\"journal\":{\"name\":\"2021 IEEE Engineering International Research Conference (EIRCON)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Engineering International Research Conference (EIRCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIRCON52903.2021.9613399\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Engineering International Research Conference (EIRCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIRCON52903.2021.9613399","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
EmotiTEA: A visual monitoring module based on the recognition of facial emotions with CNN
The recognition of human facial emotions is a highly complex task and an open problem. This paper presents the EmotiTEA module that performs the recognition of facial emotions to be used in monitoring in real time. Two simple custom Convolutional Neural Networks (CNN) are studied, which were included in the module for specific tests. The results obtained under the test conditions indicate a satisfactory performance with the implemented CNNs and a promising behavior of the EmotiTEA module for the real time monitoring task.