Comparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence
We propose a longest common subsequence (LCS) based approach to compute the distance among vector field ensembles. By measuring how many common blocks the ensemble pathlines passing through, the LCS distance defines the similarity among vector field ensembles by counting the number of sharing domain data blocks. Compared to the traditional methods (e.g. point-wise Euclidean distance or dynamic time warping distance), the proposed approach is robust to outlier, data missing, and sampling rate of pathline timestep. Taking the advantages of smaller and reusable intermediate output, visualization based on the proposed LCS approach revealing temporal trends in the data at low storage cost, and avoiding tracing pathlines repeatedly. Finally, we evaluate our method on both synthetic data and simulation data, which demonstrate the robustness of the proposed approach.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- National Natural Science Foundation of China (NSFC); USDOE Office of Science (SC)
- DOE Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1366297
- Resource Relation:
- Conference: 9th IEEE Pacific Visualization Symposium , 04/19/16 - 04/22/16, Taipei, TW
- Country of Publication:
- United States
- Language:
- English
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