A Quick Guide to Visualization - PowerPoint Presentation

Slide1

A Quick Guide to Visualization

Yingcai XiaoSlide2

Computation with and without Visual Assistance

67 x 89 = ? Slide3

Visualized Data Analysis

67

x 89

---------

603

+ 536

---------

5963

Slide4

Visualization

Representing

information (data)

as

computer graphics.Slide5

Scientific, Engineering and Information Visualization

Scientific Visualization: Scientific Data

Engineering Visualization: Measurement Data

Information Visualization: Abstract DataSlide6

Data Structures & Algorithms

Data Structures:

How to store and retrieve data.

For visualization: input data (to be visualized) and output data (graphics).

Algorithms:

How to process data efficiently.

For visualization: converting input data into graphical data and display/print them.

Slide7

Scientific Visualization

Started from CFD (Computational Fluid Dynamics) in the 80s.

Formalized as a research discipline in 1989. (NSF Report on Scientific Visualization).Slide8

Scientific Data

Commonly in the form of a grid: data values are known on the grid nodes.Slide9

Scientific Visualization: Fundamentals

Visualizing data variation through out the volume of interest.Slide10

Scientific Visualization: Fundamentals

Local Trilinear InterpolationSlide11

Mapping data values to colors with a color map.

Scientific Visualization: Techniques: Color MappingSlide12

A color map.

Scientific Visualization: Techniques: Color MappingSlide13

Revealing data values inside the volume of interest.

Scientific Visualization: Techniques: Cut-AwaySlide14

Revealing data values on cutting planes.

Scientific Visualization: Techniques: SlicingSlide15

Iso-surface: a surface of constant data values.

Scientific Visualization: Techniques: Iso-surfacingSlide16

Scientific Visualization: Techniques: Iso-surfacingSlide17

Scientific Visualization: Techniques: Iso-surfacingSlide18

Iso-line: a line of constant data values.

Scientific Visualization: Techniques: Iso-LinesSlide19

Data Types

Scientific VisualizationSlide20

Scientific Visualization: Data Types

Scalar: one value per data point

Vector: 3 values per data point

3 Scalars

Tensor: 9 values per data point

9 Scalars

3 VectorsSlide21

3 scalar values, (v

x

, v

y

, v

z

) => direction and length

Vector VisualizationSlide22

Vector Visualization: Directed Lines

3 scalar values, (v

x

, v

y

, v

z

) => direction and lengthSlide23

Vector Visualization: GlyphSlide24

Vector Visualization: GlyphSlide25

Vector Visualization: Warping

Warping: deformation of geometry according to a vector. Slide26

Vector Visualization: Displacement Plots

Displacement Plots: represent data values as the displacement of a surface in the direction perpendicular to the surface. Slide27

Vector Visualization: Streamlines

Streamlines: outlines of fluid flowSlide28

Vector Visualization: Streamtubes

Stream-tubes: streamline + isosurface + color mappingSlide29

Tensor Visualization: Tensor Ellipsoid

Three eigenvectors

:

V

1



V

2



V

3

Slide30

Tensor Visualization: Tensor EllipsoidSlide31

Scientific Visualization: Mature

W.

Shroeder

, K. Martin, & B.

Lorensen

The Visualization Toolkit - An Object-oriented Approach to 3D Graphics, 2nd ed.

www.kitware.comSlide32

Engineering VisualizationSlide33

Engineering Visualization

Intelligent Monitoring

Traffic

Assembly Line

Slide34

Intelligent Monitoring

Data capturing

Data analysis

Data representation

Slide35

Intelligent Monitoring

Data capturing

sensors, video cameras, tracking devices

Data analysis

video image processing is a challenge

Data representation

color coding (e.g. GIS – Geographical Information Systems, google map)

Slide36

Intelligent Monitoring

video image processing :

computer vision :

OpenCV

http://opencv.willowgarage.com/wiki/

http://sourceforge.net/projects/opencvlibrary/

ITK:

http://www.itk.org/

Slide37

Engineering Visualization

Measurement Data:

Scattered

Sparse

Slide38

Scattered Data: sample points distributed unevenly and non-uniformly throughout the volume of interest.

Slide39

Engineering Visualization: Two-Step Approach

T. Foley & A. D. Lane

Visualization of Irregular Multivariate Data

Proceedings of the First IEEE Conference on Visualization, San Francisco, CA, 1990Slide40

Scattered Data

Interpolation

Modeling

Intermediate Grid

Rendering

Grid-based

Rendered Volume

__________ ____________ __ ___ _______Slide41

Information Visualization

Data abstractNot

interpolatable

Domain dependent

Visual Analytics (IA: Intelligence Amplification)

http://en.wikipedia.org/wiki/Information_visualization

http://ieeevis.org/

http://www.tableauconference.com/

Slide42

Information Visualization

GapMinder

Hans

Rosling’s

TED Talk:

https://www.youtube.com/watch?v=RUwS1uAdUcI

http://www.gapminder.org

http://www.gapminder.org/data/

http://www.gapminder.org/downloads/

http://www.gapminder.org/labs

Slide43

Information Visualization

Parallel CoordinatesVisualizing high dimensional data using parallel

vertical axes. Each axis represents one dimension. Each data point is drawn as a polyline connecting its attribute values on the axes.

Basic concepts:

http://en.wikipedia.org/wiki/Parallel_coordinates

https://eagereyes.org/techniques/parallel-coordinatesSlide44

Visualization in Art

New Media ArtArt work generated by computers

Interactive

Audience participation

Examples: http://

www.kangeunsu.com

/Slide45

Visualization Programming Tools

For Scientific VisualizationVisualization Toolkit (VTK)

http://www.vtk.org/

VTK Documentation

http://www.vtk.org/documentation/

VTK Online Visualization

http://www.kitware.com/solutions/dataanalytics/webvisualization.htmlSlide46

Visualization Programming Tools

For Engineering VisualizationInterpolation Overview

https://en.wikipedia.org/wiki/Interpolation

Least squares in VTK

http://www.vtk.org/Wiki/VTK/Examples/Cxx/Math/LeastSquares

Solve Linear Systems in VTK

http://www.vtk.org/doc/release/5.0/html/a01710.html#e7Slide47

Visualization Programming Tools

For Information VisualizationGoogle Visualization APIhttps://developers.google.com/chart/interactive/docs/reference

Google Charts

https://google-developers.appspot.com/chart/interactive/docs/gallery

Other Google APIs

https://developers.google.com/products/Slide48

Visualization Programming Tools

For Information VisualizationVTK Chart APIhttp://www.vtk.org/features-2d-plots-and-charts/

JavaScript charts for web & mobile

http://www.fusioncharts.com/

.NET Windows Presentation Foundation (WPF)

http://wpftutorial.net/Slide49

Parallel Coordinates Tools

Free software: http://www.xdat.org Source code with demo:https://syntagmatic.github.io/parallel-coordinates/

http://mbostock.github.io/protovis/ex/cars.html

3D PC:

http://innovis.cpsc.ucalgary.ca/Research/3DParallelCoordinates

http://www.ncbi.nlm.nih.gov/pubmed/16680710

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1532141&tag=1

 Slide50

Data Source

Google Public Data Directory: http://www.google.com/publicdata/directoryData in GapMinder World: http://www.gapminder.org/data/

Ask Dr. Xiao for the following data

CT Scan Image Data

Scattered Data

Social Visualization Data

Genomic DataSlide51

Visualization Overview

Visualization

Data Structures

Algorithms

Background

Term projects

Scientific

3D Girds

Marching Cubes/Voxel,

Local Interpolations

VTK

3D Printing

Cloud

GPU

Engineering

Scattered

Global Interpolations

Linear Algebra

Matrix Inversion

VTK

O

ld and new interpolation methods

GPU

Cloud

Abstract

(Information)

Not

interpolatable

Stored

in tables.

GapMi

n

der

Parallel Coordinates (2D,3D)

WebGL

.NET WPF

Google API

XDAT

VTK

Social Vis

Genomic Vis

Online Vis

DB VisSlide52

Summary

Visualization: Information/Data to GraphicsCurrent Techniques for Scientific Visualization

Examples of Engineering Visualization

Examples of

Information Visualization

Visualization in Art

Visualization Programming Tools