Probabilistic state machines: dialog management for inputs with uncertainty
UIST '92 Proceedings of the 5th annual ACM symposium on User interface software and technology
The “prince” technique: Fitts' law and selection using area cursors
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Providing integrated toolkit-level support for ambiguity in recognition-based interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Interaction techniques for ambiguity resolution in recognition-based interfaces
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Semantic pointing: improving target acquisition with control-display ratio adaptation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor's activation area
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
"Beating" Fitts' law: virtual enhancements for pointing facilitation
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
A framework for robust and flexible handling of inputs with uncertainty
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
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Many new input technologies (such as touch and voice) hold the promise of more natural user interfaces. However, many of these technologies create inputs with some uncertainty. Unfortunately, conventional infrastructure lacks a method for easily handling uncertainty, and as a result input produced by these technologies is often converted to conventional events as quickly as possible, leading to a stunted interactive experience. Our ongoing work aims to design a unified framework for modeling uncertain input and dispatching it to interactors. This should allow developers to easily create interactors which can interpret uncertain input, give the user appropriate feedback, and accurately resolve any ambiguity. This abstract presents an overview of the design of a framework for handling input with uncertainty and describes topics we hope to pursue in future work. We also give an example of how we built highly accurate touch buttons using our framework. For examples of what interactors can be built and a more detailed description of our framework we refer the reader to [8].