Sumanto, B. Wijonarko, Muhammad Qommarudin, Aji Sudibyo, Pudji Widodo, Afit Muhammad Lukman
{"title":"Viola-Jones Algorithm for Face Detection using Wider Face Dataset","authors":"Sumanto, B. Wijonarko, Muhammad Qommarudin, Aji Sudibyo, Pudji Widodo, Afit Muhammad Lukman","doi":"10.1109/CITSM56380.2022.9935830","DOIUrl":null,"url":null,"abstract":"Face detection has been one of the most explored problems in computer vision for several years. Using the WIDER FACES data set, this study investigates how the Viola-Jones method can be used to identify faces in 179 photos and how it performs compared to other face detection algorithms. In a previous study for face detection using Viola-jones, the highest accuracy results were obtained at 90.9% for facial images and 75.5% for non-face images. In this study, the Viola-Jones approach had a 100 percent success rate. This approach will be used in the MATLAB algorithm for face identification to get better results than currently available. Experiments using two classes had promising results.","PeriodicalId":342813,"journal":{"name":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 10th International Conference on Cyber and IT Service Management (CITSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITSM56380.2022.9935830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Face detection has been one of the most explored problems in computer vision for several years. Using the WIDER FACES data set, this study investigates how the Viola-Jones method can be used to identify faces in 179 photos and how it performs compared to other face detection algorithms. In a previous study for face detection using Viola-jones, the highest accuracy results were obtained at 90.9% for facial images and 75.5% for non-face images. In this study, the Viola-Jones approach had a 100 percent success rate. This approach will be used in the MATLAB algorithm for face identification to get better results than currently available. Experiments using two classes had promising results.