Textile interfaces enable designers to integrate unobtrusive media and smart home controls into furniture such as sofas. While the technical aspects of such controllers have been the subject of numerous research projects, the physical form factor of these controls has received little attention so far. This work investigates how general design properties, such as overall slider shape, raised vs. recessed sliders, and number and layout of tick marks, affect users’ preferences and performance. Our first user study identified a preference for certain design combinations, such as recessed, closed-shaped sliders. Our second user study included performance measurements on variations of the preferred designs from study 1, and took a closer look at tick marks. Tick marks supported orientation better than slider shape. Sliders with at least three tick marks were preferred, and performed well. Non-uniform, equally distributed tick marks reduced the movements users needed to orient themselves on the slider.

In Handheld Augmented Reality, users look at AR scenes through the smartphone held in their hand. In this setting, having a mid-air pointing device like a pen in the other hand greatly expands the interaction possibilities. For example, it lets users create 3D sketches and models while on the go. However, perceptual issues in Handheld AR make it difficult to judge the distance of a virtual object, making it hard to align a pen to it. To address this, we designed and compared different visualizations of the pen's position in its virtual environment, measuring pointing precision, task time, activation patterns, and subjective ratings of helpfulness, confidence, and comprehensibility of each visualization. While all visualizations resulted in only minor differences in precision and task time, subjective ratings of perceived helpfulness and confidence favor a 'heatmap' technique that colors the objects in the scene based on their distance to the pen.

We present Headbang, an interaction technique that enriches touch input on handheld devices through slight head movement gestures. This way, users can easily execute shortcuts, like Copy, Paste, or Share, to on-screen targets while touching them. Headbang utilizes the capabilities of commodity smartphones to track the user’s head with their front facing cameras. We evaluated Headbang in two studies and show that the system can be reliably used while sitting and walking and offers a similar accuracy and speed as touch interaction.

Adding a mid-air pen to Handheld Augmented Reality creates a new kind of bimanual interaction for which many fundamental interaction design questions have not been answered yet. In particular, menus are an essential component in most visual interfaces, but it is unclear how to best interact with them in this setting: using the pen in mid-air or on a surface, using the touchscreen, or by moving the smartphone itself. We compared basic menus for these methods by analyzing success rates, selection times, device movement, and subjective ratings. Our results indicate that interacting with a mid-air menu using the pen, and operating a menu with the hand holding the smartphone, are sufficiently competitive to the current standard of two-handed touchscreen interaction, so that interaction designers can freely choose among them based on the interaction context of their application.

Modeling in Augmented Reality (AR) lets users create and manipulate virtual objects in mid-air that are aligned to their real environment. We present ARPen, a bimanual input technique for AR modeling that combines a standard smartphone with a 3D-printed pen. Users sketch with the pen in mid-air, while holding their smartphone in the other hand to see the virtual pen traces in the live camera image. ARPen combines the pen's higher 3D input precision with the rich interactive capabilities of the smartphone touchscreen. We studied subjective preferences for this bimanual input technique, such as how people hold the smartphone while drawing, and analyzed the performance of different bimanual techniques for selecting and moving virtual objects. Users preferred a bimanual technique casting a ray through the pen tip for both selection and translation. We provide initial design guidelines for this new class of bimanual AR modeling systems.

Traditional audio guides in museums and similar spaces typically require the visitor to locate a track number at each exhibit and enter it on a keypad. These guides, however, provide no information on the amount of content available. Current mobile devices provide rich output capabilities, and indoor location tracking technology can simplify the selection of content in modern audio guides. In this paper, we compare the keypad-based interface to a map-based interface with and without automatic localization. Through a field study in a local museum with 84 participants, we found that the usability of all versions is rated high, with the keypad interface coming out ahead. Nevertheless, visitors favored the overview of the map and thumbnails to find the right exhibit, while numbers were considered helpful indicators in the real world. Those who used the self-localizing guide preferred it over manually adjusting the map.