抄録
We propose a solution to the "map-to-text (M2T)" problem, which involves the generation of text descriptions of local map content based on scene understanding to facilitate fast succinct text-based map matching. Unlike previous local feature approaches that trade discriminativitv for viewpoint invariance, we develop a holistic view descriptor that is view-dependent and highly discriminative. Because the success of our holistic view descriptor depends on the assumption that the viewpoint is unique given a local map, we also address the issue of viewpoint planning that provides similar views for similar local maps.
