{"title":"β轻叩:设备后端轻叩输入，内置传感器","authors":"Emilio Granell, Luis A. Leiva","doi":"10.1145/3098279.3125440","DOIUrl":null,"url":null,"abstract":"We present βTap, a Back-of-device (BoD) tap detection software for mobile devices that uses commodity sensors, without the need to instrument the device. Although just basic interactions are supported (namely, single and double taps), βTap is highly accurate and performance-friendly, since it uses a low-cost yet highly discriminative set of features. Our software is publicly available at the Google Play Store, so that others can build upon our work.","PeriodicalId":120153,"journal":{"name":"Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"βTap: back-of-device tap input with built-in sensors\",\"authors\":\"Emilio Granell, Luis A. Leiva\",\"doi\":\"10.1145/3098279.3125440\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present βTap, a Back-of-device (BoD) tap detection software for mobile devices that uses commodity sensors, without the need to instrument the device. Although just basic interactions are supported (namely, single and double taps), βTap is highly accurate and performance-friendly, since it uses a low-cost yet highly discriminative set of features. Our software is publicly available at the Google Play Store, so that others can build upon our work.\",\"PeriodicalId\":120153,\"journal\":{\"name\":\"Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3098279.3125440\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3098279.3125440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
βTap: back-of-device tap input with built-in sensors
We present βTap, a Back-of-device (BoD) tap detection software for mobile devices that uses commodity sensors, without the need to instrument the device. Although just basic interactions are supported (namely, single and double taps), βTap is highly accurate and performance-friendly, since it uses a low-cost yet highly discriminative set of features. Our software is publicly available at the Google Play Store, so that others can build upon our work.
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