{"title":"Implicit Palm Rejection Using Real-Time Hand Model Filters on Tablet Devices","authors":"Riyeth P. Tanyag, Rowel Atienza","doi":"10.1109/NGMAST.2015.45","DOIUrl":null,"url":null,"abstract":"Most tablet devices usually suffer from the \"palm rejection problem\", where unintended multiple touches while writing often cause erroneous application behavior and unsightly imprints on the display. We designed a real-time implicit palm rejection algorithm based on hand model filters and touch characteristics. We focus our approach on accurately determining the context of the touch in real-time to provide users with an experience that is close to natural handwriting as possible. Our algorithm uses a model-based filtering method to define the palm rejection region and automatically adjust to palm-first or write-first scenarios. Our implementation can correctly filter 99% of stylus touches with a low errant touch rate of 0.87%. In summary, our palm rejection algorithm is shown to be comparable or better than most currently available note-taking applications.","PeriodicalId":217588,"journal":{"name":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"392 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGMAST.2015.45","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
Most tablet devices usually suffer from the "palm rejection problem", where unintended multiple touches while writing often cause erroneous application behavior and unsightly imprints on the display. We designed a real-time implicit palm rejection algorithm based on hand model filters and touch characteristics. We focus our approach on accurately determining the context of the touch in real-time to provide users with an experience that is close to natural handwriting as possible. Our algorithm uses a model-based filtering method to define the palm rejection region and automatically adjust to palm-first or write-first scenarios. Our implementation can correctly filter 99% of stylus touches with a low errant touch rate of 0.87%. In summary, our palm rejection algorithm is shown to be comparable or better than most currently available note-taking applications.