Temporal reasoning based on semi-intervals
Artificial Intelligence
A spatial knowledge structure for image information systems using symbolic projections
ACM '86 Proceedings of 1986 ACM Fall joint computer conference
Qualitative Representation of Spatial Knowledge
Qualitative Representation of Spatial Knowledge
Representing and Reasoning on Three-Dimensional Qualitative Orientation Point Objects
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Using Orientation Information for Qualitative Spatial Reasoning
Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
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The 2-D orientation model of Freksa and Zimmerman has been extended by us into a 3-D orientation model for fine information. When the information provided to the system is coarse or it is advisable to reduce the processing time of the reasoning process, it is necessary to define a coarse 3-D orientation model. Our orientation model has been coarse into three models, (a length coarse model, a height coarse model and a general coarse model) which have been explained in this paper. The management of different levels of granularity and the integration between the coarse and the fine 3-D orientation models has also been explained.