Advances in Visibility Modelling in Urban Environments to Support Location Based Services
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
People describe and explore space with a strong emphasis on the visual senses, yet modelling the field of view has received little attention within the realm of Location Based Services (LBS), in part due to the lack of useful data. Advances in data capture, such as Light Detection and Ranging (LiDAR), provide new opportunities to build digital city models and expand the range of applications which use visibility analysis. This thesis capitalises on these advances with the development of a visibility model to support a number of innovative LBS functions in an urban region and particular focus is given to the visibility model‟s supporting role in the formation of referring expressions, the descriptive phrases used to identify objects in a scene, which are relevant when delivering spatial information to the user through a speech based interface. Speech interfaces are particularly useful to mobile users with restricted screen viewing opportunities, such as navigational support for motorists and a wider range of tasks including delivering information to urban pedestrians. As speech recognition accuracies improve so new interaction opportunities will allow users to relate to their surroundings and retrieve information on buildings in view through spoken descriptions. The papers presented in this thesis work towards this goal, by translating spatial information into a form which matches the user‟s perspective and can be delivered over a speech interface. The foundation is the development of a new visual exposure model for use in urban areas, able to calculate a number of metrics about Features of Interest (FOIs), including the façade area visible and the percentage on the skyline. The impact of urban vegetation as a semi-permeable visual barrier is also considered, and how visual exposure calculations may be adjusted to accommodate under canopy and through canopy views. The model may be used by pedestrian LBSs, or applied to vehicle navigation tasks to determine how much of a route ahead is in view for a car driver, identifying the sections with limited visibility or the best places for an overtaking manoeuvre. Delivering information via a speech interface requires FOI positions to be defined according to projective space relating to the user‟s viewpoint, rather than topological or metric space, and this is handled using a new egocentric model. Finally descriptions of the FOIs are considered, including a method to automatically collect façade colours by excluding foreground objects, and a model to determine the most appropriate description to direct the LBS user‟s attention to a FOI in view.