Spatial prepositions, functional relations, and lexical specification
Representation and processing of spatial expressions
Representation and recognition in vision
Representation and recognition in vision
Language and Spatial Cognition
Language and Spatial Cognition
An Influence Model for Reference Object Selection in Spatially Locative Phrases
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Automatic Classification of Containment and Support Spatial Relations in English and Dutch
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Quantifying spatial prepositions: an experimental study
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Connectionist modeling of linguistic quantifiers
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
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There is much empirical evidence showing that factors other than the relative positions of objects in Euclidean space are important in the comprehension of a wide range of spatial prepositions in English and other languages. We first the overview the functional geometric framework [11] which puts “what” and “where” information together to underpin the situation specific meaning of spatial terms. We then outline an implementation of this framework. The computational model for the processing of visual scenes and the identification of the appropriate spatial preposition consists of three main modules: (1) Vision Processing, (2) Elman Network, (3) Dual-Route Network. Mirroring data from experiments with human participants, we show that the model is both able to predict what will happen to objects in a scene, and use these judgements to influence the appropriateness of over/under/above/below to describe where objects are located in the scene. Extensions of the model to other prepositions and quantifiers are discussed.