Magic Lens Interface

In this paper we present a novel mobile buddy finder, that combines the advantages of a mobile camera device (such as a smartphone) with traditional large-scale paper maps. We applied a Magic Lens approach that uses a mobile camera-display-unit (such as a smartphone) as a lens to provide a dynamic overlay on a traditional paper map. Paper maps are still superior in some aspects to their digital counterparts. They provide high-resolution, large-scale information with zero power consumption. Using a mobile camera-display-unit as a lens over a city map, a user can easily browse the position of her buddies without cumbersome scrolling, panning or zooming of a digital map on a small screen. We explain the main concept of this idea and present first results with a fully implemented prototype.

A user study was conducted to compare the performance of three methods for map navigation with mobile devices. These methods are joystick navigation, the dynamic peephole method without visual context, and the magic lens paradigm using external visual context. The joystick method is the familiar scrolling and panning of a virtual map keeping the device itself static. In the dynamic peephole method the device is moved and the map is fixed with respect to an external frame of reference, but no visual information is present outside the device's display. The magic lens method augments an external content with graphical overlays, hence providing visual context outside the device display. Here too motion of the device serves to steer navigation. We compare these methods in a study measuring user performance, motion patterns, and subjective preference via questionnaires. The study demonstrates the advantage of dynamic peephole and magic lens interaction over joystick interaction in terms of search time and degree of exploration of the search space.

Providing indoor navigation within ab uilding is usually associated with large investments in infrastructure. We present and evaluate an approach to provide indoor navigation with minimal infrastructure investments. In our approach people use amobile camera device likeamobile phone as amagic lens. When the device is sweeped overam ap of the building, the wayi sa ugmented on the camera image of the map. We showthat people using our system use more maps and makeless errors. The main advantage of our approach is that no tracking of the user is needed-t he navigation is solely based on the user'smobile phone and paper maps. 1I ntroduction Everyone can remember asituation when he entered an unfamiliar building looking for a certain person. Probably the room number is known, butthe unstandardized building plans are difficult to read. The signs pointing to certain departments are difficult to interpret, and manypeople fall back to social navigation and ask someone. But if the building is big, it is improbable that the person asked knows the way. In the scenario we propose the first action upon entering the building would be to takeone'smobile phoneand point it to the next building map. It would be possible to select the person one is looking for from alist or ap oster with the employees' photos. The wayt ot he selected person would then be displayed on the camera image of the buildings' map. If maps are provided at all decision points within the building, the correct wayw ould always be available. To evaluate our approach we implemented aprototype of the system on an OQO 1 and tested the prototype with users of different familarity levels with the building.