Iconic indexing by 2-D strings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and brain: the resolution of the imagery debate
Image and brain: the resolution of the imagery debate
Spatial Cognition and Computation
Object-Oriented Representation of Depictions on the Basis of Cell Matrices
Text Understanding in LILOG, Integrating Computational Linguistics and Artificial Intelligence, Final Report on the IBM Germany LILOG-Project
Mental representation and processing of geographic knowledge: a computational approach
Mental representation and processing of geographic knowledge: a computational approach
Integrated spatial reasoning in geographic information systems: combining topology and direction
Integrated spatial reasoning in geographic information systems: combining topology and direction
A positron emission tomography study of visual and mental spatial exploration
Journal of Cognitive Neuroscience
Visual imagery facilitates visual perception: Psychophysical evidence
Journal of Cognitive Neuroscience
SC'10 Proceedings of the 7th international conference on Spatial cognition
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It is an ongoing and controversial debate in cognitive science which aspects of knowledge humans process visually and which ones they process spatially. Similarly, artificial intelligence (AI) and cognitive science research, in building computational cognitive systems, tended to use strictly spatial or strictly visual representations. The resulting systems, however, were suboptimal both with respect to computational efficiency and cognitive plausibility. In this paper, we propose that the problems in both research strands stem from a misconception of the visual and the spatial in mental spatial knowledge processing. Instead of viewing the visual and the spatial as two clearly separable categories, they should be conceptualized as the extremes of a continuous dimension of representation. Regarding psychology, a continuous dimension avoids the need to exclusively assign processes and representations to either one of the categories and, thus, facilitates a more unambiguous rating of processes and representations. Regarding AI and cognitive science, the concept of a continuous spatial / visual dimension provides the possibility of representation structures which can vary continuously along the spatial / visual dimension. As a first step in exploiting these potential advantages of the proposed conception we (a) introduce criteria allowing for a non-dichotomic judgment of processes and representations and (b) present an approach towards representation structures that can flexibly vary along the spatial / visual dimension.