Abstract
In everyday office work, people smoothly use the space on their physical desks to work with documents of interest, and to keep tools and materials nearby for easy use. In contrast, the limited screen space of computer displays imposes interface constraints. Associated material is placed off-screen (i.e., temporarily hidden) and requires extra work to access (window switching, menu selection) or crowds and competes with the work area (e.g., palettes and icons). This problem is worsened by the increasing popularity of small displays such as tablets and laptops. To mitigate this problem, we investigate how we can exploit an unadorned physical desk space as an additional input canvas. With minimal augmentation, our Unadorned Desk detects coarse hovering over and touching of discrete areas (‘items’) within a given area on an otherwise regular desk, which is used as input to the desktop computer. We hypothesize that people’s spatial memory will let them touch particular desk locations without looking. In contrast to other augmented desks, our system provides optional feedback of touches directly on the computer’s screen. We conducted a user study to understand how people make use of this input space. Participants freely placed and retrieved items onto/from the desk. We found that participants organize items in a grid-like fashion for easier access later on. In a second experiment, participants had to retrieve items from a predefined grid. When only few (large) items are located in the area, participants were faster without feedback and there was (surprisingly) no difference in error rates with or without feedback. As the item number grew (i.e., items shrank to fit the area), participants increasingly relied on feedback to minimize errors – at the cost of speed.
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Hausen, D., Boring, S., Greenberg, S. (2013). The Unadorned Desk: Exploiting the Physical Space around a Display as an Input Canvas. In: Kotzé, P., Marsden, G., Lindgaard, G., Wesson, J., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2013. INTERACT 2013. Lecture Notes in Computer Science, vol 8117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40483-2_10
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DOI: https://doi.org/10.1007/978-3-642-40483-2_10
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