Visualizing Routes with AI-Discovered Street-View Patterns

arXiv:2404.00431v1 Announce Type: cross
Abstract: Street-level visual appearances play an important role in studying social systems, such as understanding the built environment, driving routes, and associated social and economic factors. It has not been integrated into a typical geographical visualization interface (e.g., map services) for planning driving routes. In this paper, we study this new visualization task with several new contributions. First, we experiment with a set of AI techniques and propose a solution of using semantic latent vectors for …

abstract arxiv built environment cs.hc cs.lg driving economic environment map paper patterns planning role routes services social street study studying systems type understanding view visual visualization