Jonathan Wonner, J. Grosjean, Antonio Capobianco, D. Bechmann
{"title":"SPEED: prédiction de cibles","authors":"Jonathan Wonner, J. Grosjean, Antonio Capobianco, D. Bechmann","doi":"10.1145/2044354.2044378","DOIUrl":null,"url":null,"abstract":"We present the SPEED method to predict endpoints, based on analysis of the kinetic characteristics of the pointing gesture. Our model splits the gesture into an acceleration phase and a deceleration phase to precisely detect target. The first phase allows us to identify a velocity peak that marks the beginning of the second phase. This phase is approached with a quadratic model to predict gesture endpoint. A pilot study shows that SPEED predicts a target more precisely than other existing methods, for 1D tasks without distractors.","PeriodicalId":131420,"journal":{"name":"Interaction Homme-Machine","volume":"162 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interaction Homme-Machine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2044354.2044378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
We present the SPEED method to predict endpoints, based on analysis of the kinetic characteristics of the pointing gesture. Our model splits the gesture into an acceleration phase and a deceleration phase to precisely detect target. The first phase allows us to identify a velocity peak that marks the beginning of the second phase. This phase is approached with a quadratic model to predict gesture endpoint. A pilot study shows that SPEED predicts a target more precisely than other existing methods, for 1D tasks without distractors.