{"title":"触摸滚动传递功能","authors":"Philip Quinn, Sylvain Malacria, A. Cockburn","doi":"10.1145/2501988.2501995","DOIUrl":null,"url":null,"abstract":"Touch scrolling systems use a transfer function to transform gestures on a touch sensitive surface into scrolling output. The design of these transfer functions is complex as they must facilitate precise direct manipulation of the underlying content as well as rapid scrolling through large datasets. However, researchers' ability to refine them is impaired by: (1) limited understanding of how users express scrolling intentions through touch gestures; (2) lack of knowledge on proprietary transfer functions, causing researchers to evaluate techniques that may misrepresent the state of the art; and (3) a lack of tools for examining existing transfer functions. To address these limitations, we examine how users express scrolling intentions in a human factors experiment; we describe methods to reverse engineer existing `black box' transfer functions, including use of an accurate robotic arm; and we use the methods to expose the functions of Apple iOS and Google Android, releasing data tables and software to assist replication. We discuss how this new understanding can improve experimental rigour and assist iterative improvement of touch scrolling.","PeriodicalId":294436,"journal":{"name":"Proceedings of the 26th annual ACM symposium on User interface software and technology","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":"{\"title\":\"Touch scrolling transfer functions\",\"authors\":\"Philip Quinn, Sylvain Malacria, A. Cockburn\",\"doi\":\"10.1145/2501988.2501995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Touch scrolling systems use a transfer function to transform gestures on a touch sensitive surface into scrolling output. The design of these transfer functions is complex as they must facilitate precise direct manipulation of the underlying content as well as rapid scrolling through large datasets. However, researchers' ability to refine them is impaired by: (1) limited understanding of how users express scrolling intentions through touch gestures; (2) lack of knowledge on proprietary transfer functions, causing researchers to evaluate techniques that may misrepresent the state of the art; and (3) a lack of tools for examining existing transfer functions. To address these limitations, we examine how users express scrolling intentions in a human factors experiment; we describe methods to reverse engineer existing `black box' transfer functions, including use of an accurate robotic arm; and we use the methods to expose the functions of Apple iOS and Google Android, releasing data tables and software to assist replication. We discuss how this new understanding can improve experimental rigour and assist iterative improvement of touch scrolling.\",\"PeriodicalId\":294436,\"journal\":{\"name\":\"Proceedings of the 26th annual ACM symposium on User interface software and technology\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 26th annual ACM symposium on User interface software and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2501988.2501995\",\"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 26th annual ACM symposium on User interface software and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2501988.2501995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Touch scrolling systems use a transfer function to transform gestures on a touch sensitive surface into scrolling output. The design of these transfer functions is complex as they must facilitate precise direct manipulation of the underlying content as well as rapid scrolling through large datasets. However, researchers' ability to refine them is impaired by: (1) limited understanding of how users express scrolling intentions through touch gestures; (2) lack of knowledge on proprietary transfer functions, causing researchers to evaluate techniques that may misrepresent the state of the art; and (3) a lack of tools for examining existing transfer functions. To address these limitations, we examine how users express scrolling intentions in a human factors experiment; we describe methods to reverse engineer existing `black box' transfer functions, including use of an accurate robotic arm; and we use the methods to expose the functions of Apple iOS and Google Android, releasing data tables and software to assist replication. We discuss how this new understanding can improve experimental rigour and assist iterative improvement of touch scrolling.