Mapping natural language to imagery: Placing objects intelligently

Humans are endowed with innate faculties, which allow for reasoning in noisy or uncertain environments, that far surpass the current abilities of computing systems. One such example is the notion of forming a ldquosketchrdquo of some real-world location or route from a series of linguistic descriptions of regions and surrounding landmarks. While mirroring this functionality might seem like a daunting computational task, it is possible, to a certain degree, to mimic many of the underlying humanistic processes. Out of these, the facet that we consider in this paper is iterative object placement from a set of language extracted spatial relations and dependencies.