Location Based Services for Human Self-Localization
Human self-localisation is an important part of everyday life. In order to determine one’s own position and orientation, the allocentric representation, usually in the form of a map, has to be aligned with one’s own egocentric representation of the real world. This requires objects (anchor points) that are present in both representations. We present two novel approaches that aim to simplify the process of alignment and thus the self-localisation. The Viewshed approach is based on visibility analysis and the Image Recognition approach identifies objects and highlights them on the map. On the basis of an empirical experiment with 30 participants in the city of Vienna, Austria, the two approaches were compared with each other as well as with a standard approach using a 2D map representation. The goal is to assess and compare aspects like efficiency, user experience, and cognitive workload. Results show that the Image Recognition method provided the best support and was also most popular among users. The Viewshed method performed well below expectations.