Statistical visualization and analysis of large data using a value-based spatial distribution

Ko Chih Wang, Kewei Lu, Tzu Hsuan Wei, Naeem Shareef, Han Wei Shen

研究成果: 書貢獻/報告類型會議論文篇章

26 引文 斯高帕斯(Scopus)

摘要

The size of large-scale scientific datasets created from simulations and computed on modern supercomputers continues to grow at a fast pace. A daunting challenge is to analyze and visualize these intractable datasets on commodity hardware. A recent and promising area of research is to replace the dataset with a distribution based proxy representation that summarizes scalar information into a much reduced memory footprint. Proposed representations subdivide the dataset into local blocks, where each block holds important statistical information, such as a histogram. A key drawback is that a distribution representing the scalar values in a block lacks spatial information. This manifests itself as large errors in visualization algorithms. We present a novel statistically-based representation by augmenting the block-wise distribution based representation with location information, called a value-based spatial distribution. Information from both spatial and scalar spaces are combined using Bayes' rule to accurately estimate the data value at a given spatial location. The representation is compact using the Gaussian Mixture Model. We show that our approach is able to preserve important features in the data and alleviate uncertainty.

原文英語
主出版物標題2017 IEEE Pacific Visualization Symposium, PacificVis 2017 - Proceedings
編輯Yingcai Wu, Daniel Weiskopf, Tim Dwyer
發行者IEEE Computer Society
頁面161-170
頁數10
ISBN(電子)9781509057382
DOIs
出版狀態已發佈 - 2017 9月 11
對外發佈
事件10th IEEE Pacific Visualization Symposium, PacificVis 2017 - Seoul, 大韓民國
持續時間: 2017 4月 182017 4月 21

出版系列

名字IEEE Pacific Visualization Symposium
ISSN(列印)2165-8765
ISSN(電子)2165-8773

會議

會議10th IEEE Pacific Visualization Symposium, PacificVis 2017
國家/地區大韓民國
城市Seoul
期間2017/04/182017/04/21

ASJC Scopus subject areas

  • 電腦繪圖與電腦輔助設計
  • 電腦視覺和模式識別
  • 硬體和架構
  • 軟體

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