Publication | Closed Access
Improving topological segmentation of three-dimensional vector fields
13
Citations
12
References
2003
Year
Unknown Venue
EngineeringGeometryOutflow SeparatricesComputer-aided DesignComputational TopologyImage AnalysisData SciencePattern RecognitionSignificant InflowComputational GeometryGeometry ProcessingGeometric ModelingMachine VisionComputer EngineeringComputer ScienceTopological SegmentationMedical Image ComputingComputer VisionComputational ScienceNatural SciencesBioimage AnalysisSeed StreamlinesImage Segmentation
We present three enhancements to accelerate the extraction of separatrices of three-dimensional vector fields, using intelligently selected streamlines. These enhancements reduce the number of needed sample streamlines and their propagation length. Inflow/outflow matching supports the simultaneous extraction of topologically significant inflow and outflow separatrices in a single pass. An adaptive sampling approach is introduced and used to seed streamlines in a more meaningful and efficient manner. Cell-locking is a new concept that isolates regions of a data set that do not contain separatrices. This concept makes streamline propagation more efficient as streamlines are not propagated through cells that do not influence or contain separatrices. These enhancements enable us to perform separatrix construction for three-dimensional vector field data requiring less overall computation.
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