Visualisatie BMT. Introduction, visualization, visualization pipeline. Arjan Kok Huub van de Wetering

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1 Visualisatie BMT Introduction, visualization, visualization pipeline Arjan Kok Huub van de Wetering 1

2 Lecture overview Goal Summary Study material What is visualization Examples Visualization pipeline 2

3 Goal Provide theoretical and practical knowledge in: Data visualization Data representation Computer graphics Data processing in Java Visualization in MayaVi 3

4 Summary (1) Introduction What is visualization Related disciplines Fields of applications The visualization pipeline Definition Data enrichment, mapping, rendering 4

5 Summary (2) Basic data representation Datasets Sampling Interpolation Graphics rendering Rendering process Color Lighting, shading 5

6 Summary (3) Algorithms Scalar algorithms Vector algorithms Tensor algorithms Modeling algorithms Volume visualization Ray tracing, ray sampling Volume interpolation 6

7 Study material Theory Book Slides Practice MayaVi (visualization tool) Jaspis (java programming tool) Assignments 7

8 Book The Visualization Toolkit An Object-Oriented Approach to 3D Graphics W. Schroeder, K. Martin, B. Lorensen Prentice Hall Book contains a lot more than the course does (course will address specific parts/chapters) Book contains software (VTK) we shall not (directly) use 8

Lorensen Prentice Hall Book contains a lot more than the course does

9 Slides Slides used in lectures will be available at: 9

10 Visualization 10

11 What do we visualize? 11

12 Visualization The purpose of computing is insight, not numbers - Richard Hamming 12

13 Visualization - insight in data 13

14 From data to pictures Attributes of Visualization Making abstract data visible (complex, many) Forming a mental image of something abstract Using the abilities of human vision and interaction DATA VISUALIZATION PICTURES E a: b: 43.3 C:

Using the abilities of human vision and interaction DATA VISUALIZATION

15 Scientific visualization The use of computer imaging techniques as a tool for comprehending data obtained by simulation or physical measurements The techniques that allow scientists and engineers to extract knowledge from the results of simulations and computations 15

measurements The techniques that allow scientists and engineers to

16 Goals in visualization Exploration of data and information Enhancing understanding of concepts and processes Gaining new (unexpected) insight Making invisible visible Effective presentation of significant features Quality control of simulations and measurements Increasing scientific production 16

Making invisible visible Effective presentation of significant features

17 Visualization challenges Getting usable data Parsable Visualizable Defining your goal What is the focus of attention or primary features Who is the audience What is the message Choosing meaningful/compelling visual representations 17

attention or primary features Who is the audience What is

18 Graphs

19 Complex data We are interested in more complex data Multi-dimensional Complex geometry Computed or collected Simulations MRI, CT,.. Microscopic to galactic data collections 19

20 Some examples 20

21 Related disciplines USER INTERFACE STUDIES IMAGE PROCESSING PERCEPTUAL PSYCHOLOGY COMPUTER AIDED DESIGN V I S U A L I Z A T I O N GEOMETRIC MODELING COMPUTER GRAPHICS SIGNAL PROCESSING 21

22 Imaging, graphics, visualization Imaging The study of 2D images (transformations, enhancement, information extraction) Graphics Creating images using a computer (2D drawing techniques, 3D rendering techniques) Visualization Exploring, transforming, and viewing data as images 22

23 Imaging, graphics, visualization Visualization uses computer graphics and imaging as tools for the higher level goal of getting insight into data Graphics and imaging are particular forms of visualization 23

24 Imaging, graphics, visualization Data dimensionality Data transformation Imaging Graphics Visualization 2D 2D, 3D nd image 2D/3D object any data image image image 24

25 Applications 25

26 Applications Biochemistry Molecular modeling/dynamics Industrial research on molecular structures Drug design DATA VISUALIZATION PICTURES molecule structures 26

27 Molecular visualization 27

28 Molecular visualization 28

29 Applications Mathematics Understanding complex concepts (functions, surfaces, fields,..) DATA VISUALIZATION PICTURES functions f(x,y,z) function plot 29

30 Mathematics z = F(x,y) = e-rcos(10r) nested implicit functions saddle quadric surface F(x,y,z) = 0 30

31 Applications Medicine Diagnosis Treatment planning Education Research DATA VISUALIZATION PICTURES 2D/3D scan data surfaces/ slices 31

32 Medicine 32

33 Examples Geosciences Weather forecast Topography Geology DATA VISUALIZATION PICTURES surface/ volume data surfaces/ height plots 33

34 Geosciences Rain during summer 2004 Ocean surface height during the El Nino event 34

35 Applications Space sciences Astronomy Astrophysics Remote sensing 35

36 Space sciences Orion Nebula as seen from a virtual spacecraft 36

37 Applications Engineering and physics Computational fluid dynamics Fluid flow simulation Surface modeling Finite element simulations Physical processes (strength, elasticity, flow,..) 37

38 Computational fluid dynamics velocity of a turbulent jet flow air pressure on a plane wing internal waves inside the ocean 38

39 Finite element methods pressure on a plane wing 2D flow past a cylinder 39

40 Applications Architecture Simulations of: Indoor lighting Sound Heath Air 40

41 Architecture Simulation of light in a theatre 41

42 Applications Visualization is applicable in any research or engineering field DATA VISUALIZATION PICTURES E a: b: 43.3 C:

43 Visualization pipeline Describes the steps to transform raw data into displayable images Goal of these steps is to convert the information to a format amenable to understanding by the human perceptual system while maintaining the integrity of information 43

44 Visualization pipeline Raw Data Data Enrichment/Enhancement Derived Data Visualization Mapping Abstract Visualization Object Rendering Displayable Image 44

45 Getting the data Measured data Simulation data Data formats Data compression HDF, NetCDF, XDR, Dicom,. RLE, Fractal methods,. my own format Visualization internal data (ready for the pipeline) 45

46 Step 1: Data enrichment Data enrichment Interpolation Filtering and smoothing Selection Merging Format conversion 2D and 3D conversions (rotation, translation) data object(s) data enrichment (filter object) data object(s) 46

47 Step 2: Mapping Mapping Generating displayable data (2D and 3D objects) whose shape, dimensions and color represent the enriched data Abstract visualization objects The 2D and 3D objects resulting from the mapping stage (graphical primitives) data object(s) mapping (mapper object) abstract visualization objects 47

48 Step 3: Rendering Rendering Produces an image (view) of the 2D/3D abstract visualization objects Several rendering parameters (lighting, shadows, reflections, etc) abstract visualization objects rendering image(s) 48

49 Step 3: Rendering Rendering Special rendering techniques such as volume rendering for non-opaque data data object(s) volume rendering image(s) 49

50 Example 50

51 Example pipeline reader outline filter data mapper lines mapper surfaces mapper surface polydata data render str. pnts geometry filter data polydata image 51

52 Visualization and interaction Raw Data u s e r i n p u t Data Enrichment/Enhancement Derived Data Visualization Mapping Abstract Visualization Object Rendering Displayable Image 52

53 Visualization and research process Visualization plays a large role in forming the link between hypothesis and experiment, and between insight and new hypothesis 53

54 Visualization and research process 54

55 Visualization pipeline (revisited) Raw Data Data Enrichment/Enhancement Derived Data Visualization Mapping Abstract Visualization Object Rendering Displayable Image 55

The Visualization Pipeline

The Visualization Pipeline Conceptual perspective Implementation considerations Algorithms used in the visualization Structure of the visualization applications Contents The focus is on presenting the