{"title":"KissLoc: A Spatio-temporal Kissing Recognition System Using Commercial Smart Glasses","authors":"Hamada Rizk, Hirozumi Yamaguchi","doi":"10.1109/SMARTCOMP58114.2023.00049","DOIUrl":null,"url":null,"abstract":"In this paper, we propose KissLoc: a system that leverages onboard micro-size sensors of consumer eyewear devices for the dual purpose of activity recognition and localization. Specifically, the system trains a deep learning model for recognizing kissing activity and simultaneously identifying the timestamped location of its occurrence. Consequently, several predefined actions could be taken, including logging or controlling the smart environment. The evaluation shows that KissLoc can recognize the kissing activity with 82% accuracy while locating its occurrence with a median localization error of 1.25m.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMARTCOMP58114.2023.00049","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
In this paper, we propose KissLoc: a system that leverages onboard micro-size sensors of consumer eyewear devices for the dual purpose of activity recognition and localization. Specifically, the system trains a deep learning model for recognizing kissing activity and simultaneously identifying the timestamped location of its occurrence. Consequently, several predefined actions could be taken, including logging or controlling the smart environment. The evaluation shows that KissLoc can recognize the kissing activity with 82% accuracy while locating its occurrence with a median localization error of 1.25m.