POITrack: improving map-based planning with implicit POI tracking

Abstract

Maps enable complex decision making, such as planning a day trip in a foreign city This kind of task often requires combining information from different parts of the map leading to a sequence of visual searches and map extent changes. Hereby, the user can easily get lost, not being able to find back to relevant points of interest (POI). In this paper, we present POITrack, a novel gaze-adaptive map which supports a user in finding previously inspected POIs faster by providing highlights. Our approach allows filtering inspected POIs based on their category and automatically adapting the current map extent. Not only could participants find visited locations faster with our system, but they also rated the interaction as more pleasing. Our findings can contribute to improving the interaction with high-density visual information, which requires revisiting of previously seen objects whose relevance for the task may not have been clear initially.