Interactive Interface Design for Scalable Large Multivariate Volume - - PowerPoint PPT Presentation

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Interactive Interface Design for Scalable Large Multivariate Volume - - PowerPoint PPT Presentation

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Interactive Interface Design for Scalable Large Multivariate Volume Visualization Xiaoru Yuan Key Laboratory on Machine Perception, MOE School of EECS, Peking University Nov. 13 th 2011 Ultrascale Visualization Workshop November 13, 2011

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Ultrascale Visualization Workshop November 13, 2011 Seattle, WA

Interactive Interface Design for Scalable Large Multivariate Volume Visualization

Xiaoru Yuan

Key Laboratory on Machine Perception, MOE School of EECS, Peking University

  • Nov. 13th 2011
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Ultrascale Visualization Workshop November 13, 2011 Seattle, WA

Outline

  • Motivation
  • Multivariate Volume Transfer Function Design
  • Parallel coordinates & MDS
  • Scattering Points in Parallel coordinates
  • Parallel extension of the TF design
  • Scalable Pivot MDS
  • Adaptive Continuous Parallel Coordinates

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Ultrascale Visualization Workshop November 13, 2011 Seattle, WA

High Dimensional/Multivariate Data Set

  • Isabel Hurricane

QVAPOR QCLOUD Speed Pressure

…

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Transfer Functions

  • Transfer functions map the voxels values to colors and
  • pacities, generating insightful results.

1D TF (Intensity) 2D TF (Intensity vs. Gradient Magnitude)

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Transfer Functions

  • Multivariate TFs for multi-modal data

QVAPOR QCLOUD Speed Pressure

…

Pressure Temperature

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Methods of Visualizing Multi-dimensional Data

  • Scatterplot Matrix
  • Star Glyphs
  • Chernoff Faces
  • Multidimensional Scaling (MDS)
  • Parallel Coordinates
  • etc.

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Multidimensional Scaling

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Parallel Coordinates

  • To represent N dimensional data

– Set N vertical axes in parallel – Put data to intersects on corresponding axes – Connect intersects

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Data Exploration with PC

[Yuan et al. TVCG 2009]

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Multivariate Visualization with Parallel Coordinates

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[Jones et al. 2008]

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Line vs. Point Representation

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Line vs. Point Representation

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Line vs. Point Representation

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Data Exploration with SPPC

[Yuan et al. TVCG 2009]

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Data Exploration with SPPC

[Yuan et al. TVCG 2009]

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High Dimensional Transfer Function Design

  • Key issue in multivariate TF design:

Identifying features in multi-dimensional space

  • Multidimensional data visualization in InfoVis community

applied on TF design:

– Parallel coordinates plot (PCP), which keeps information on each dimension – Multidimensional scaling (MDS), which works better on multi- dimensional feature identification

PCP MDS

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Ultrascale Visualization Workshop November 13, 2011 Seattle, WA

High Dimensional Transfer Function Design

  • Integrate MDS into PCP to facilitate multivariate TF

design.

– Avoids context jumps between polyline and point regions when exploring data clusters – Provides multiple perspective views upon the data, supporting linked queries

[Guo, Xiao &Yuan, PacificVis 2011]

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Design Multivariate TFs with the Proposed System

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Volume Rendering with Sketch Feedbacks

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System Pipeline (Non-parallel version)

Reconstruction Pre-Processing Reconstruction Pre-Processing

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Transfer Function User Interface

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Transfer Function User Interface

  • User interactions

– Brushing on axes – Lasso on points – Magic wand on points

Lasso Tool Magic Wand Tool

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PCP and MDS Generation

  • Subroutines:

– Embedding MDS Plot into Continuous PCP – Generation of Weight-Adjustable MDS Plot – Adaptive Rendering of Continuous PCP

Pre-Processing

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MDS Plot

  • Pivot MDS [Brandes and Pich 2007]

– Low storage and low computational complexity

MDS works better for feature identification and selection

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MDS Plot

  • Hierarchical adaptive sampling can be exploited to

reduce the data amount to progressively reaching

  • ptimal
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MDS Plot

  • Metric adjustable MDS

– Allows user to define different impacts from the dimensions

  • n MDS layouts
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TF Construction

Reconstruction

  • Gaussian Mixture Model (GMM)

– Use several Gaussian blobs to fit the distribution of user selected clusters

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Hurricane Isabel

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Hurricane Isabel

Red part (hurricane eye): low pressure, medium temperature, lower QCLOUD, high wind speed

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Hurricane Isabel

Yellow part:

higher pressure

lower wind speed

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Hurricane Isabel

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System Pipeline

Reconstruction Pre-Processing

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System Pipeline – Parallel Environment

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Adaptive Continuous PCP

5% 10% 15%

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Adaptive Continuous PCP

  • The continuous PCP is a HDRI (High Dynamic Range

Image). Features may be hidden without proper mapping strategy.

  • A logarithm tone-mapping is utilized to enhance the small

features

Pseudo Color Linear Logarithm

Hidden Features

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Pivot MDS

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Pivot MDS Parallization

  • Computation of squared distance matrix Δ
  • Double centered sub-matrix C
  • Inner product CTC
  • Eigensolver

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Scalable Pivot MDS

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Performance –Parallel Multivariate Volume Rendering

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Performance –Parallel MDS Projection

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Performance –Parallel PCP Rendering

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Integrated System Interface

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VisIt Plug-in (ongoing)

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Related Publications

  • H. Guo, H. Xiao, and X. Yuan. “Multi-dimensional transfer function design based
  • n flexible dimension projection embedded in parallel coordinates”. In

Proceedings of IEEE Pacific Visualization Symposium 2011, pages 19–26, 2011.

  • H. Guo, H. Xiao, and X. Yuan. “Scalable Multivariate Volume Visualization and

Analysis based on Dimension Projection and Parallel Coordinates”. IEEE Transactions on Visualization and Computer Graphics. Under revision.

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Acknowledgement

  • Students

– Hanqi Guo, Xiao He

  • Collaborator

– CNIC CAS (parallel computing environment)

  • Funds

– NSFC 60903062, NSFC 61170204 – Beijing NSFC 4092021 – 863 Project 2010AA012400 – Chinese Ministry of Education Key Project No. 109001.

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http://vis.pku.edu.cn http://vis.pku.edu.cn/wiki Email: xiaoru.yuan@pku.edu.cn