論文アブストラクト： Acoustic levitation enables a radical new type of human-computer interface composed of small levitating objects. For the first time, we investigate the selection of such objects, an important part of interaction with a levitating object display. We present Point-and-Shake, a mid-air pointing interaction for selecting levitating objects, with feedback given through object movement. We describe the implementation of this technique and present two user studies that evaluate it. The first study found that users could accurately (96%) and quickly (4.1s) select objects by pointing at them. The second study found that users were able to accurately (95%) and quickly (3s) select occluded objects. These results show that Point-and-Shake is an effective way of initiating interaction with levitating object displays.
論文アブストラクト： Head and eye movement can be leveraged to improve the user's interaction repertoire for wearable displays. Head movements are deliberate and accurate, and provide the current state-of-the-art pointing technique. Eye gaze can potentially be faster and more ergonomic, but suffers from low accuracy due to calibration errors and drift of wearable eye-tracking sensors. This work investigates precise, multimodal selection techniques using head motion and eye gaze. A comparison of speed and pointing accuracy reveals the relative merits of each method, including the achievable target size for robust selection. We demonstrate and discuss example applications for augmented reality, including compact menus with deep structure, and a proof-of-concept method for on-line correction of calibration drift.
論文アブストラクト： In contrast to the extensive studies on static target pointing, much less formal understanding of moving target acquisition can be found in the HCI literature. We designed a set of experiments to identify regularities in 1D unidirectional moving target selection, and found a Ternary-Gaussian model to be descriptive of the endpoint distribution in such tasks. The shape of the distribution as characterized by μ and σ in the Gaussian model were primarily determined by the speed and size of the moving target. The model fits the empirical data well with 0.95 and 0.94 R2 values for μ and σ , respectively. We also demonstrated two extensions of the model, including 1) predicting error rates in moving target selection; and 2) a novel interaction technique to implicitly aid moving target selection. By applying them in a game interface design, we observed good performances in both predicting error rates (e.g., 2.7% mean absolute error) and assisting moving target selection (e.g., 33% or a greater increase in pointing accuracy).
論文アブストラクト： This paper presents Rolling-Menu, a technique for selecting toolbar items, based on the use of roll gestures with a multidimensional device, the Roly-Poly Mouse (RPM). Rolling-Menu reduces object-command transition, resulting in a better integration between command selection and direct manipulation of application objects. Selecting a toolbar item with Rolling-Menu requires rolling RPM in a predefined direction corresponding to the item. We propose a design space of Rolling-Menu that includes different roll mapping and validation modes. A first user's study, with a simple toolbar containing up to 14 items, establishes that the best version of Rolling-Menu takes, on average, up to 29% less time than the Mouse to select a toolbar item. Moreover accuracy of the selection with Rolling-Menu is above 90%. Both the validation mode and the mapping between roll direction and toolbar items influence the performance of Rolling-Menus. A second study compares the three best versions of Rolling-Menu with the Mouse to select an item in two types of multidimensional toolbars: a toolbar containing dropdown lists, and a grid toolbar. Results confirm the advantage of Rolling-Menu over a Mouse.