Haijun Xia, Ricardo Jota, Benjamin McCanny, Zhe Yu, C. Forlines, Karan Singh, Daniel J. Wigdor
{"title":"零延迟敲击:使用悬停信息来预测触摸位置,消除触地延迟","authors":"Haijun Xia, Ricardo Jota, Benjamin McCanny, Zhe Yu, C. Forlines, Karan Singh, Daniel J. Wigdor","doi":"10.1145/2642918.2647348","DOIUrl":null,"url":null,"abstract":"A method of reducing the perceived latency of touch input by employing a model to predict touch events before the finger reaches the touch surface is proposed. A corpus of 3D finger movement data was collected, and used to develop a model capable of three granularities at different phases of movement: initial direction, final touch location, time of touchdown. The model is validated for target distances >= 25.5cm, and demonstrated to have a mean accuracy of 1.05cm 128ms before the user touches the screen. Preference study of different levels of latency reveals a strong preference for unperceived latency touchdown feedback. A form of 'soft' feedback, as well as other uses for this prediction to improve performance, is proposed.","PeriodicalId":20543,"journal":{"name":"Proceedings of the 27th annual ACM symposium on User interface software and technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Zero-latency tapping: using hover information to predict touch locations and eliminate touchdown latency\",\"authors\":\"Haijun Xia, Ricardo Jota, Benjamin McCanny, Zhe Yu, C. Forlines, Karan Singh, Daniel J. Wigdor\",\"doi\":\"10.1145/2642918.2647348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method of reducing the perceived latency of touch input by employing a model to predict touch events before the finger reaches the touch surface is proposed. A corpus of 3D finger movement data was collected, and used to develop a model capable of three granularities at different phases of movement: initial direction, final touch location, time of touchdown. The model is validated for target distances >= 25.5cm, and demonstrated to have a mean accuracy of 1.05cm 128ms before the user touches the screen. Preference study of different levels of latency reveals a strong preference for unperceived latency touchdown feedback. A form of 'soft' feedback, as well as other uses for this prediction to improve performance, is proposed.\",\"PeriodicalId\":20543,\"journal\":{\"name\":\"Proceedings of the 27th annual ACM symposium on User interface software and technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 27th annual ACM symposium on User interface software and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2642918.2647348\",\"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 27th annual ACM symposium on User interface software and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2642918.2647348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Zero-latency tapping: using hover information to predict touch locations and eliminate touchdown latency
A method of reducing the perceived latency of touch input by employing a model to predict touch events before the finger reaches the touch surface is proposed. A corpus of 3D finger movement data was collected, and used to develop a model capable of three granularities at different phases of movement: initial direction, final touch location, time of touchdown. The model is validated for target distances >= 25.5cm, and demonstrated to have a mean accuracy of 1.05cm 128ms before the user touches the screen. Preference study of different levels of latency reveals a strong preference for unperceived latency touchdown feedback. A form of 'soft' feedback, as well as other uses for this prediction to improve performance, is proposed.