Landmark-based navigation systems have proven benefits relative to traditional turn-by-turn systems that use street names and distances. However, one obstacle to the implementation of landmark-based navigation systems is the complex challenge of selecting salient local landmarks at each decision point for each user. In this paper, we present Pharos, a novel system that extends turn-by-turn navigation instructions using a single global landmark (e.g. the Eiffel Tower, the Burj Khalifa, municipal TV towers) rather than multiple, hard-to-select local landmarks. We first show that our approach is feasible in a large number of cities around the world through the use of computer vision to select global landmarks. We then present the results of a study demonstrating that by including global landmarks in navigation instructions, users navigate more confidently and build a more accurate mental map of the navigated area than using turn-by-turn instructions.
We present an analysis of how runners navigate the environment when running. Results from 153 questionnaire, and 8 interview participants found navigation was often not pre-planned, had no clear route and changed organically as running was undertaken. From this we present the design of RunNav, a novel navigation system that uses Foursquare to provide support for the navigation practices runners employ. We illustrate its basic design, and plans for its future development and evaluation. Map applications for smartwatches present new challenges in cartography, a domain in which large display sizes have significant advantages. In this paper, we introduce StripeMaps, a system that adapts the mobile web design technique of linearization for displaying maps on the small screens of smartwatches. Just as web designers simplify multiple column desktop websites into a single column for easier navigation on mobile devices, StripeMaps transforms any two-dimensional route map into a one-dimensional "stripe". Through a user study, we show that this simplification allows StripeMaps to outperform both traditional mobile map interfaces and turn-by-turn directions for pedestrian navigation using smartwatches. In addition to introducing StripeMaps, this paper also has a secondary contribution. It contains the first empirical comparison of different approaches for pedestrian smartwatch navigation and illuminates their pros and cons. Deep Map is a research framework that aims at building the prototype of an intelligent next generation spatial information system. Deep Map realizes the vision of a future tourist guidance system that works as a mobile guide and as a web-based planning tool. This long term research project addresses several challenging research aspects covering intelligent integration of information from different data sources and services including geographical information systems, multi-media databases, and interactive internet data sources such as reservation systems. On the basis of this complex information system the European Media Laboratory plans to build user interfaces that allow intuitive and easy access to information. Such a user interface including visual and natural language processing will be included into a mobile device that navigates the user through a city. Also virtual tours in a 3D-reconstructed city will be possible. In this paper, we present the current system that already covers a number of these aspects and demonstrates how tourists may be guided in the future.