Argonne National Laboratory

Comparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence

TitleComparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence
Publication TypeJournal Article
Year of Publication2016
AuthorsLiu, R, Guo, H, Zhang, J, Yuan, X
JournalProceedings of IEEE Pacific Visualization Symposium 2016
Pagination 96-103
AbstractWe propose a longest common subsequence (LCSS)-based approach to compute the distance among vector field ensembles. By measuring how many common blocks the ensemble pathlines pass through, the LCSS distance defines the similarity among vector field ensembles by counting the number of shared domain data blocks. Compared with traditional methods (e.g., pointwise Euclidean distance or dynamic time warping distance), the proposed (c) approach is robust to outliers, missing data, and the sampling rate of the pathline timesteps. Taking advantage of smaller and reusable intermediate output, visualization based on the proposed LCSS approach reveals temporal trends in the data at low storage cost and avoids tracing pathlines repeatedly. We evaluate our method on both synthetic data and simulation data, demonstrating the robustness of the proposed approach.  
PDFhttp://www.mcs.anl.gov/papers/P5499-1215.pdf