Structuring Line Ensembles with Path-Integrated Fidelity and Structural Inconsistency Fields
Yumeng Xue, Patrick Paetzold, Bin Chen, Yunhai Wang, Christophe Hurter, Oliver Deussen
Figure 1: Weather observations: density-based selection compared with structural selection.
Abstract (Summary)
This work studies how to expose meaningful patterns in crowded collections of trajectories. It scores each trajectory against a tensor representation of its neighborhood, then maps disagreements into an image-space field. Excluding a trajectory from its own reference reduces bias. Users can query and remove subsets to reveal further patterns without replacing the original paths with a bundled approximation. Experiments use synthetic trajectories, weather observations, aircraft routes, and brain fibers to examine structural differences that density views can hide.
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Figures
Figure 2: Building the tensor representation at different neighborhood sizes.
Figure 3: Evaluating agreement along complete trajectories.
Figure 4: Synthetic input collections.
Figure 5: Comparing density, disagreement, and categorical views.
Figure 6: Runtime measurements as dataset size increases.
Figure 7: Separating dominant flight routes from unusual trajectories.
Figure 8: Comparing brain-fiber views and a selected coherent subset.