{"title":"Live Feed Emotion Detection During Project Meetings To Estimate Possible Success of Projects","authors":"Zeenat AIKassim","doi":"10.1109/CICN56167.2022.10008311","DOIUrl":null,"url":null,"abstract":"This paper describes a method done to collect emotions from people's faces during project meetings in one of the companies. The work includes the built algorithm and the working of the system, including the live feed display of the information, basically the emotions detected. The work describes the handling of a large number of images captured consecutively throughout the working hours. The algorithm was built using Support Vector Machine and Image processing. Other tools were used for displaying the live results. This research can result in valuable conclusions for companies to help in estimation of the success rate of projects, based on the emotions detected during project meetings.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"750 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICN56167.2022.10008311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes a method done to collect emotions from people's faces during project meetings in one of the companies. The work includes the built algorithm and the working of the system, including the live feed display of the information, basically the emotions detected. The work describes the handling of a large number of images captured consecutively throughout the working hours. The algorithm was built using Support Vector Machine and Image processing. Other tools were used for displaying the live results. This research can result in valuable conclusions for companies to help in estimation of the success rate of projects, based on the emotions detected during project meetings.
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