Y. Gupta, Aashish Prasad, Siddhant Touti, Kunal Sachdev, Vishal R. Jaiswal, V. Naranje
{"title":"实时人脸识别:一项调查","authors":"Y. Gupta, Aashish Prasad, Siddhant Touti, Kunal Sachdev, Vishal R. Jaiswal, V. Naranje","doi":"10.1109/ICCIKE51210.2021.9410792","DOIUrl":null,"url":null,"abstract":"Face recognition in real-time has always been challenging due various reasons such as poses, illumination, occlusions. In this letter, we propose a method that solve these issues and provide better accuracy over existing state-of-art technology. In particular, we consider the process of face recognition as a 3-part process: detection, feature extraction and selection, recognition. By providing this technology we further improve the existing technology by increasing its accuracy and scope to a new level. This method to ensemble the 3 components we achieve remarkable real-time performance.","PeriodicalId":254711,"journal":{"name":"2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Real-time face recognition: A survey\",\"authors\":\"Y. Gupta, Aashish Prasad, Siddhant Touti, Kunal Sachdev, Vishal R. Jaiswal, V. Naranje\",\"doi\":\"10.1109/ICCIKE51210.2021.9410792\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Face recognition in real-time has always been challenging due various reasons such as poses, illumination, occlusions. In this letter, we propose a method that solve these issues and provide better accuracy over existing state-of-art technology. In particular, we consider the process of face recognition as a 3-part process: detection, feature extraction and selection, recognition. By providing this technology we further improve the existing technology by increasing its accuracy and scope to a new level. This method to ensemble the 3 components we achieve remarkable real-time performance.\",\"PeriodicalId\":254711,\"journal\":{\"name\":\"2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIKE51210.2021.9410792\",\"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 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIKE51210.2021.9410792","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Face recognition in real-time has always been challenging due various reasons such as poses, illumination, occlusions. In this letter, we propose a method that solve these issues and provide better accuracy over existing state-of-art technology. In particular, we consider the process of face recognition as a 3-part process: detection, feature extraction and selection, recognition. By providing this technology we further improve the existing technology by increasing its accuracy and scope to a new level. This method to ensemble the 3 components we achieve remarkable real-time performance.