{"title":"Neural network method through facial expression recognition","authors":"Kavita Kushwah, Vikrant Sharma, Upendra Singh","doi":"10.1109/ICECA.2017.8212721","DOIUrl":null,"url":null,"abstract":"Humans are capable to produce thousands of facial actions during communication that vary in intensity, complexity and meaning. The purpose of this paper is to recognize the human emotions in terms of happy, sad, surprise, neutral and disgust. Its aim is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database. The purposed system depends upon the human face, as we know face also reflects the human brain activities or emotions. In this paper, the neural network has been used for better results. In the end of the paper comparisons of existing Human Emotion Recognition System has been made with new one.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECA.2017.8212721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Humans are capable to produce thousands of facial actions during communication that vary in intensity, complexity and meaning. The purpose of this paper is to recognize the human emotions in terms of happy, sad, surprise, neutral and disgust. Its aim is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database. The purposed system depends upon the human face, as we know face also reflects the human brain activities or emotions. In this paper, the neural network has been used for better results. In the end of the paper comparisons of existing Human Emotion Recognition System has been made with new one.