Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero-Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence - Special issue on knowledge representation
Efficient algorithms for qualitative reasoning about time
Artificial Intelligence
Scaling Theorems for Zero Crossings of Bandlimited Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Processing disjunctions in temporal constraint networks
Artificial Intelligence
Pattern matching algorithms
Maintaining knowledge about temporal intervals
Communications of the ACM
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Temporal Constraints: A Survey
Constraints
Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Constraint Processing
Scaling Theorems for Zero-Crossings
Scaling Theorems for Zero-Crossings
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
A survey on tree edit distance and related problems
Theoretical Computer Science
Deriving and Mining Spatiotemporal Event Schemas in In-Situ Sensor Data
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Path consistency on triangulated constraint graphs
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Ordering events for dynamic geospatial domains
COSIT'05 Proceedings of the 2005 international conference on Spatial Information Theory
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This paper introduces a novel framework for deriving and mining high–level spatiotemporal process models in in-situ sensor measurements. The proposed framework is comprised of two complementary components, namely, hierarchical event schemas and spatiotemporal episodes. Event schemas are used in this work as the basic building model of spatiotemporal processes while episodes are used for organizing events in space and time in a consistent manner. The construction of event schemas is carried out using scale-space analysis from which the interval tree, a hierarchical decomposition of the data, is derived. Episodes are constructed from event schemas using by formulating the problem as a constraint network, in which spatial and temporal constraints are imposed. Consistency is achieved using a path–consistency algorithm. Once created, possible episodes can be derived from the network using a shortest–path search.