Towards a cognitive system that can recognize spatial regions based on context

Nicholas Hawes, G.S. Horn, M. Klenk, K. Lockwood, J.D. Kelleher

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Citations (Scopus)


In order to collaborate with people in the real world, cognitive systems must be able to represent and reason about spatial regions in human environments. Consider the command "go to the front of the classroom". The spatial region mentioned (the front of the classroom) is not perceivable using geometry alone. Instead it is defined by its functional use, implied by nearby objects and their configuration. In this paper, we define such areas as context-dependent spatial regions and present a cognitive system able to learn them by combining qualitative spatial representations, semantic labels, and analogy. The system is capable of generating a collection of qualitative spatial representations describing the configuration of the entities it perceives in the world. It can then be taught context-dependent spatial regions using anchor points defined on these representations. From this we then demonstrate how an existing computational model of analogy can be used to detect context-dependent spatial regions in previously unseen rooms. To evaluate this process we compare detected regions to annotations made on maps of real rooms by human volunteers.
Original languageEnglish
Title of host publicationProceedings of the National Conference on Artificial Intelligence
PublisherAssociation for the Advancement of Artificial Intelligence
Number of pages7
ISBN (Print)9781577355687
Publication statusPublished - 1 Jan 2012
Event26th AAAI Conference on Artificial Intelligence - Toronto, Canada
Duration: 22 Jul 201226 Jul 2012


Conference26th AAAI Conference on Artificial Intelligence


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