{"title":"基于DCNN和弧面损失函数的印尼大流行背景下人脸识别模型的开发","authors":"Mauritsius T. Wirianto","doi":"10.24507/ijicic.17.05.1513","DOIUrl":null,"url":null,"abstract":"The advancement of technology opens opportunities for implementation that benefits the social and economic aspects of human life. Given the latest achievement in face recognition technology that surpasses human ability to identify a face, the research explores the application of this scientific discovery in the Indonesian context during the current pandemic situation. Toward the effort to achieve this goal, the study develops an Indonesia Labelled Face in the Wild (ILFW) that collects face images of famous Indonesian people from the Internet in various poses, expressions, lighting/illumination, and fashion attribute. In response to the recent COVID-19 pandemic situation, the study also augmented a face mask to a portion of collected face images. Using DCNN, RetinaFace as the face detection model, and Arcface loss function, and adopting CRISP DM, the research contributes by providing a method to develop a face dataset with 1,200 identities, and face recognition model with 92 percent accuracy and be able to recognize Indonesian people with a face mask. The researchers also recommend use cases for realtime face recognition in the business organization. It uses CCTV to perform automatic attendance, security surveillance, and employee location tracking and exhibits deployment consideration. Future research could increase the accuracy of face recognition model by adding more identities to the face dataset.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"THE DEVELOPMENT OF FACE RECOGNITION MODEL IN INDONESIA PANDEMIC CONTEXT BASED ON DCNN AND ARCFACE LOSS FUNCTION\",\"authors\":\"Mauritsius T. Wirianto\",\"doi\":\"10.24507/ijicic.17.05.1513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advancement of technology opens opportunities for implementation that benefits the social and economic aspects of human life. Given the latest achievement in face recognition technology that surpasses human ability to identify a face, the research explores the application of this scientific discovery in the Indonesian context during the current pandemic situation. Toward the effort to achieve this goal, the study develops an Indonesia Labelled Face in the Wild (ILFW) that collects face images of famous Indonesian people from the Internet in various poses, expressions, lighting/illumination, and fashion attribute. In response to the recent COVID-19 pandemic situation, the study also augmented a face mask to a portion of collected face images. Using DCNN, RetinaFace as the face detection model, and Arcface loss function, and adopting CRISP DM, the research contributes by providing a method to develop a face dataset with 1,200 identities, and face recognition model with 92 percent accuracy and be able to recognize Indonesian people with a face mask. The researchers also recommend use cases for realtime face recognition in the business organization. It uses CCTV to perform automatic attendance, security surveillance, and employee location tracking and exhibits deployment consideration. Future research could increase the accuracy of face recognition model by adding more identities to the face dataset.\",\"PeriodicalId\":50314,\"journal\":{\"name\":\"International Journal of Innovative Computing Information and Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Computing Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24507/ijicic.17.05.1513\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Computing Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24507/ijicic.17.05.1513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
THE DEVELOPMENT OF FACE RECOGNITION MODEL IN INDONESIA PANDEMIC CONTEXT BASED ON DCNN AND ARCFACE LOSS FUNCTION
The advancement of technology opens opportunities for implementation that benefits the social and economic aspects of human life. Given the latest achievement in face recognition technology that surpasses human ability to identify a face, the research explores the application of this scientific discovery in the Indonesian context during the current pandemic situation. Toward the effort to achieve this goal, the study develops an Indonesia Labelled Face in the Wild (ILFW) that collects face images of famous Indonesian people from the Internet in various poses, expressions, lighting/illumination, and fashion attribute. In response to the recent COVID-19 pandemic situation, the study also augmented a face mask to a portion of collected face images. Using DCNN, RetinaFace as the face detection model, and Arcface loss function, and adopting CRISP DM, the research contributes by providing a method to develop a face dataset with 1,200 identities, and face recognition model with 92 percent accuracy and be able to recognize Indonesian people with a face mask. The researchers also recommend use cases for realtime face recognition in the business organization. It uses CCTV to perform automatic attendance, security surveillance, and employee location tracking and exhibits deployment consideration. Future research could increase the accuracy of face recognition model by adding more identities to the face dataset.
期刊介绍:
The primary aim of the International Journal of Innovative Computing, Information and Control (IJICIC) is to publish high-quality papers of new developments and trends, novel techniques and approaches, innovative methodologies and technologies on the theory and applications of intelligent systems, information and control. The IJICIC is a peer-reviewed English language journal and is published bimonthly