Ajay Jain
Mohit Chandra
Abstract
This work1 provides an intelligent algorithm that analyzes the success (and failure) rate of a touch gesture in order to determine best size and layout of icons. Dynamic adaptation of icon size is done to best match device user's finger impression size resulting into reduction in failed tapings which would have otherwise occurred due to variations between icon size and finger's impression.
Gravity of the said problem is analyzed by conducting a survey amongst 100 plus users. The implementation is also tested by building an android gaming application. The game is then released to limited set of users where dynamic icons sizes are generated based on user's score on successful taps on rapidly changing icons.
- http://www.appszoom.com/android_applications/tools/icon-changer_bhgma.html {1} Icon Changer applicationGoogle Scholar
- Make bigger Ad application http://www.appszoom.com/android_applications/productivity/make-bigger-ad_cbvyr.htmlGoogle Scholar
- Microsoft Touch Guidelines http://msdn.microsoft.com/en-us/library/windows/desktop/cc872774.aspxGoogle Scholar
- iOS Human Interface Guidelines http://developer.apple.com/library/ios/#documentation/userexperience/conceptual/mobilehig/Characteristics/Characteristics.htmlGoogle Scholar
- Foley, J.D. et al. 1984. The human factors of computer graphics interaction techniques. IEEE Computer Graphics and Applications. 4, 11 (1984). Google ScholarDigital Library
- Forlines, C. et al. 2007. Direct-touch vs. mouse input for tabletop displays. CHI (2007). http://www.merl.com/papers/docs/TR2007-053.pdf Google ScholarDigital Library
- Shneiderman, B. (1991). Touchscreens now offer compelling uses. IEEE Software, 8(2). Google ScholarDigital Library
- Jain, Ajay. "Touch Target Optimization Technique Using Virtual Finger-tip Library." ACM SIGSOFT Software Engineering Notes, 38.3 (2013). Google ScholarDigital Library
Index Terms
- Heuristics-based algorithm to dynamically adapt icon sizes and layouts on touch devices
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