Visual spatial information is projected from the retina to the brain in a highly topographic fashion, so that 2-D visual space is represented in a simple retinotopic map. Auditory spatial information, by contrast, has to be computed from binaural time and intensity differences as well as from monaural spectral cues produced by the head and ears. Evaluation of these cues in the central nervous system leads to the generation of neurons that are sensitive to the location of a sound source in space ("spatial tuning") and, in some animal species, to auditory space maps where spatial location is encoded as a 2-D map just like in the visual system. The brain structures thought to be involved in the multimodal integration of visual and auditory spatial integration are the superior colliculus in the midbrain and the inferior parietal lobe in the cerebral cortex. It has been suggested for the owl that the visual system participates in setting up the auditory space map in the superior.

Sejnowski Computational Neurobiology Lab The Salk: Institute San Diego, CA 92138 Visual spatial information is projected from the retina to the brain in a highly topographic fashion, so that 2-D visual space is represented in a simple retinotopic map. Auditory spatial information, by contrast, has to be computed from binaural time and intensity differences as well as from monaural spectral cues produced by the head and ears. Evaluation of these cues in the central nervous system leads to the generation of neurons that are sensitive to the location of a sound source in space ("spatial tuning") and, in some animal species, to auditory space maps where spatial location is encoded as a 2-D map just like in the visual system. The brain structures thought to be involved in the multimodal integration of visual and auditory spatial integration are the superior colliculus in the midbrain and the inferior parietal lobe in the cerebral cortex. It has been suggested for the owl that the visual system participates in setting up the auditory space map in the superior.

The acquisition of spatial knowledge by exploration of an environment has been the subject ofseveral recent experimental studies.

In this paper we give a new randomized incremental algorithm for the construction of planar Voronoi diagrams and Delaunay triangulations. The new algorithm is more "on-line" than earlier similar methods, takes expected timeO(nℝgn) and spaceO(n), and is eminently practical to implement. The analysis of the algorithm is also interesting in its own right and can serve as a model for many similar questions in both two and three dimensions. Finally we demonstrate how this approach for constructing Voronoi diagrams obviates the need for building a separate point-location structure for nearest-neighbor queries.

Artificial Intelligence 51 (1991) 417-471, Spatial reasoning is ubiquitous in human problem solving. Significantly, many aspects of it appear to be qualitative. This paper describes a general framework for qualitative spatial reasoning and demonstrates how it can be used to understand complex mechanical systems, such as clocks. The framework is organized around three ideas.

A fundamental goal of computer vision is the development of systems capable of carrying out scene interpretation while taking into account all the available knowledge. In this article, we focus on how the interpretation task can be aided by the expected scene information (such as map knowledge), which, in most cases, would not be in registration with the perceived scene. The system is implemented as a two-panel, six-level blackboard and uses the Dempster-Shafer formalism to accomplish inexact reasoning in a hierarchical space. Inexact reasoning involves exploiting, at different levels of abstraction, any internal geometric consistencies in the data and between the data and the expected scene.

In this article, principles involving the intrinsic, deictic, and extrinsic use of spatial prepositions are examined from linguistic, psychological, and AI approaches. First, I define some important terms. Second, those prepositions which permit intrinsic, deictic, and extrinsic use are specified. Finally, I introduce the natural language dialog system CITYTOUR, which can cope with the intrinsic, deictic, and extrinsic use of spatial prepositions, and compare it with the approaches dealt with in the previous sections as well as to some other AI systems.

A guest editorial describing the special issue on spatial reasoning: "We conceive of space as a completely empty, infinite, three-dimensional, isotropic, disembodied receptacle distinct from the earth or any object that might be located on the earth, one that is capable of housing not only things but also such incorporeal mathematical entities as points and infinite straight lines. Such a strange idea -especially if it were taken to describe something that exists in this world-was unthinkable before the seventeenth century; yet not even Galileo fully accepted the idea of such a world as real. For him, a "straight line" was still bound to the earth's surface. The transformation that led to the reification of geometry, though basically one of attitude and perception rather than of empirical observation, profoundly affected the course of science."

A guest editorial describing the special issue on spatial reasoning: "We conceive of space as a completely empty, infinite, three-dimensional, isotropic, disembodied receptacle distinct from the earth or any object that might be located on the earth, one that is capable of housing not only things but also such incorporeal mathematical entities as points and infinite straight lines. Such a strange idea -especially if it were taken to describe something that exists in this world-was unthinkable before the seventeenth century; yet not even Galileo fully accepted the idea of such a world as real. For him, a "straight line" was still bound to the earth's surface. Not until Newton was the task of "geometrization of the world" ... completed. The transformation that led to the reification of geometry, though basically one of attitude and perception rather than of empirical observation, profoundly affected the course of science."

Moravec has interests in computer animation and three dimensional graphics. He has produced illustrations and films presenting progress in the other work and published in the areas of mobile robots, computer vision, robots and the future, orbital skyhooks, switching networks, and three dimensional Keith M. Andress, coauthor of "Evidence Accumulation and Flow of Control in graphics a Hierarchical Spatial Reasoning System, " is a research associate in the Robot Vision Lab at Purdue University His research interests are in formalisms for Gudula Retz-Schmidt received her accumulation of evidence, expert systems, and computer vision. He can be Master degree (Dipl.-Inform) Practitioners Should Know about the Law. Part Two" is an attorney practicing Benjamin J. Kuipers, coauthor of William Swartout, editor of "Summary with Nutter, McClennen & Fish, "Navigation and Mapping in Large-Report on DARPA Santa Cruz One International Place, Boston, Massachusetts Scale Space" is an associate professor Workshop on Planning" is a senior 02210-2699. His research Framework for Representing and Reasoning research interests include qualitative interests include explanation of about Three-Dimensional reasoning about physical mechanisms expert systems, natural language generation, Objects for Vision" is group leader of and qualitative representations and expert system architectures, the Sensory Intelligence Group in the learning strategies for spatial knowledge.