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PE-TESV

Towards Better Pattern Enhancement in Temporal Evolving Set Visualization

Zihao Zhu, Yue Shen, Sujia Zhu, Gefei Zhang, Ronghua Liang, Guodao Sun

This GitHub repo presents the results of our paper, which is accepted by ChinaVis2022.

This paper is now published at Journal of Visualization, link.

Each figure shows the orginal result of timeline visualization (left) and the result of pattern enhancement strategies (right).

Abstract

Temporal evolving set data are time-varying and growing ubiquitous in person re-identification, parameter choice, and streaming data analysis. We construct a workflow to analyze and explore the inconspicuous pattern between multiple nonadjacent sets in temporal evolving set data. We propose a progressive timeline layout algorithm based on a mathematical optimization model to place the set element after data update, our layout algorithm can calculate the coordinates of elements in a short time and preserve the distance ratio between elements. To relax the visual clutter when visualizing sets’ relationships, we design two types of pattern enhancement strategies and their combinations: optimization-based pattern enhancement strategy and design-based pattern enhancement strategy. We conduct a comprehensive evaluation to verify and compare our pattern enhancement strategies including a quantitative experiment, two case studies, and an informal user study. The results show that our pattern enhancement strategies can effectively help users identify inconspicuous patterns. Our workflow and strategies show broad application prospects and we hope it could be a fundamental component in data projection pattern mining and streaming data analysis.

Citation

@article{zhu2022towards,
  title = {{Towards Better Pattern Enhancement in Temporal Evolving Set Visualization}},
  journal = {Journal of Visualization},
  pages = {611-629},
  volume = {26},
  issue = {3},
  year = {2023},
  doi = {https://doi.org/10.1007/s12650-022-00896-x},
  author = {Zihao Zhu and Yue Shen and Sujia Zhu and Gefei Zhang and Ronghua Liang and Guodao Sun},
  keywords = {Temporal evolving set data, Pattern enhancement strategy, Progressive timeline layout algorithm}
}

Table of Content

Columns

These results are the comparison of results that applied our pattern enhancement strategies in different columns.

Element Movement

Column one and three

em_1_3

Column one and five

em_1_5

Element Alignment

Column one and three

ea_1_3

Column one and five

ea_1_5

Element Reorder

Column one and three

er_1_3

Column one and five

er_1_5

Curve Link

Column one and three

cl_1_3

Column one and five

cl_1_5

Element Movement + Curve Link

Column one and three

em_cl_1_3

Column one and five

em_cl_1_5

Element Alignment + Curve Link

Column one and three

ea_cl_1_3

Column one and five

ea_cl_1_5

Element Reorder + Curve Link

Column one and three

er_cl_1_3

Column one and five

er_cl_1_5

Case1

Case $\mathrm{I}$ utilizes different projection methods and paramenters in a ReID dataset, the points in the timeline represent the outliers in each projection result.

Element Movement

em

Element Alignment

ea

Element Reorder

er

Curve Link

cl

Bubble Link

bl

Flow Link

fl

Element Bundling

eb

Element Movement + Curve Link

em_cl

Element Movement + Bubble Link

em_bl

Element Movement + Flow Link

em_fl

Element Movement + Element Bundling

em_eb

Element Alignment + Curve Link

ea_cl

Element Alignment + Bubble Link

ea_bl

Element Alignment + Flow Link

ea_fl

Element Alignment + Element Bundling

ea_eb

Element Reorder + Curve Link

er_cl

Element Reorder + Bubble Link

er_bl

Element Reorder + Flow Link

er_fl

Element Reorder + Element Bundling

er_eb

Case2

Case $\mathrm{II}$ utilizes the Park dataset from VAST challenge 2015, which records the locations of tourists in an amusement park. We choose the location information of tourists within ninety minutes, and filter the twenty-five tourists with the most location information.

The results of pattern enhancement strategies are shown as followings. Each circle denotes a tourist. We examine our strategies in the fourth and sixth column.

Element Movement

em

Element Alignment

ea

Element Reorder

er

Curve Link

cl

Bubble Link

bl

Flow Link

fl

Element Bundling

eb

Element Movement + Curve Link

em_cl

Element Movement + Bubble Link

em_bl

Element Movement + Flow Link

em_fl

Element Movement + Element Bundling

em_eb

Element Alignment + Curve Link

ea_cl

Element Alignment + Bubble Link

ea_bl

Element Alignment + Flow Link

ea_fl

Element Alignment + Element Bundling

ea_eb

Element Reorder + Curve Link

er_cl

Element Reorder + Bubble Link

er_bl

Element Reorder + Flow Link

er_fl

Element Reorder + Element Bundling

er_eb

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