Optimistic Programming of Touch Interaction

Abstract

Touch-sensitive surfaces have become a predominant input medium for computing devices. In particular, multitouch capability of these devices has given rise to developing rich interaction vocabularies for “real” direct manipulation of user interfaces. However, the richness and flexibility of touch interaction often comes with significant complexity for programming these behaviors. Particularly, finger touches, though intuitive, are imprecise and lead to ambiguity. Touch input often involves coordinated movements of multiple fingers as opposed to the single pointer of a traditional WIMP interface. It is challenging in not only detecting the intended motion carried out by these fingers but also in determining the target objects being manipulated due to multiple focus points. Currently, developers often need to build touch behaviors by dealing with raw touch events that is effort consuming and error-prone. In this article, we present Touch, a tool that allows developers to easily specify their desired touch behaviors by demonstrating them live on a touch-sensitive device or selecting them from a list of common behaviors. Developers can then integrate these touch behaviors into their application as resources and via an API exposed by our runtime framework. The integrated tool support enables developers to think and program optimistically about how these touch interactions should behave, without worrying about underlying complexity and technical details in detecting target behaviors and invoking application logic. We discuss the design of several novel inference algorithms that underlie these tool supports and evaluate them against a multitouch dataset that we collected from end users. We also demonstrate the usefulness of our system via an example application.