Yi Wu, Vimal Kakaraparthi, Zhuohang Li, Tien Pham, Jian Liu, V. P. Nguyen
{"title":"BioFace-3D","authors":"Yi Wu, Vimal Kakaraparthi, Zhuohang Li, Tien Pham, Jian Liu, V. P. Nguyen","doi":"10.1145/3539668.3539676","DOIUrl":null,"url":null,"abstract":"Over the last decade, facial landmark tracking and 3D reconstruction have gained considerable attention due to their numerous applications, such as human-computer interactions, facial expression analysis, emotion recognition, etc. However, existing camera-based solutions require users to be confined to a particular location and face a camera at all times without occlusions, which largely limits their usage in practice. To overcome these limitations, we propose the first single-earpiece lightweight biosensing system, Bioface-3D, that can unobtrusively, continuously, and reliably sense the entire facial movements, track 2D facial landmarks, and further render 3D facial animations. Without requiring a camera positioned in front of the user, this paradigm shift from visual sensing to biosensing would introduce new opportunities in many emerging mobile and IoT applications.","PeriodicalId":29918,"journal":{"name":"GetMobile-Mobile Computing & Communications Review","volume":"23 1","pages":"21 - 24"},"PeriodicalIF":0.7000,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GetMobile-Mobile Computing & Communications Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3539668.3539676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Over the last decade, facial landmark tracking and 3D reconstruction have gained considerable attention due to their numerous applications, such as human-computer interactions, facial expression analysis, emotion recognition, etc. However, existing camera-based solutions require users to be confined to a particular location and face a camera at all times without occlusions, which largely limits their usage in practice. To overcome these limitations, we propose the first single-earpiece lightweight biosensing system, Bioface-3D, that can unobtrusively, continuously, and reliably sense the entire facial movements, track 2D facial landmarks, and further render 3D facial animations. Without requiring a camera positioned in front of the user, this paradigm shift from visual sensing to biosensing would introduce new opportunities in many emerging mobile and IoT applications.