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Object-oriented Visualization

Object-oriented Visualization. João Duarte Cunha Univ. de Lisboa - Faculdade de Ciências Socrates Programme Plzen, May 2001. Visualization. Overcoming spatial, temporal and physical barriers. Sensorial limitations.

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Object-oriented Visualization

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  1. Object-oriented Visualization João Duarte Cunha Univ. de Lisboa - Faculdade de Ciências Socrates Programme Plzen, May 2001 J D Cunha

  2. Visualization Overcoming spatial, temporal and physical barriers J D Cunha

  3. Sensorial limitations • Our senses are our “interface”: everything we got from the outside world comes through them • Our senses are quite limited • in the type of stimuli they can perceive • in their sensitivity J D Cunha

  4. Sensorial limitations • Because of those limitations, the world within our reach is: • limited in space • limited in time • limited in the type of objects and phenomena that we can perceive! J D Cunha

  5. Man’s inconformism • Man always struggled against his sensorial limitations! • Oral tradition in primitive societies was a away of overcoming the time barrier (and, combined with travelling, also the space barrier) • Painting and other art forms have a similar role! J D Cunha

  6. Man’s inconformism • The introduction of writing was an enormous step forward. • And the discovery of the press by Gutemberg in the 15th century amplified its impact by orders of magnitude. J D Cunha

  7. Man’s inconformism • And so we got the 19th century! J D Cunha

  8. Man’s inconformism • All these ways of overcoming the space and time barriers are human mediated • by ONE man in the case of writing and the plastic arts • by MANY men in the case of oral tradition, music, dance. J D Cunha

  9. Man’s inconformism • The senses involved are always vision and hearing! J D Cunha

  10. Man’s inconformism • Galileo’s telescope and other optical instruments pushed away the space barrier. And we know well how important this was for our understanding of the universe! J D Cunha

  11. Man’s inconformism • With the development of measuring instruments the struggle against the physical barrier proceeded step by step. • But slowly! J D Cunha

  12. Man’s inconformism • In the 19th century a new era begun! • Telegraphy (1856) introduced the “instanta-neous” transmission of the written word. We can say, at Earth scale at least, that with telegraphy space became independent of time! J D Cunha

  13. Man’s inconformism • The telephone (1876) and radio or wireless telephony (already in the 20th century) are new advances allowing for a limited form of direct (not human mediated) perception. • Photography (1839), sound recording (1877) and the cinema (1895) are other important landmarks. J D Cunha

  14. Man’s inconformism • But it was undoubtedly the television (1926) the most significant step in man’s struggle against the space barrier! J D Cunha

  15. "Sensing" information • From Visualization to "Perception" ! J D Cunha

  16. SEEING information • Knowledge is based on information and action is determined by knowledge. • Computers are essential to generate new information (simulation and data acquisition). • But they are, more than anything else, the ideal instrument to store, search, retrieve and process information. J D Cunha

  17. SEEING information • In their book "Readings in Information Visualization - Using vision to think", Card, Mackinlay e Shneiderman define visualization as The use of computer-supported, interactive, visual representations of data to amplify cognition J D Cunha

  18. SEEING information Look at the following table: 0,000 0,087 0,174 0,259 0,342 0,423 0,500 0,574 0,643 0,707 0,766 0,819 0,866 0,906 0,940 0,966 0,985 0,996 1,000 0,996 0,985 0,966 0,940 0,906 0,866 0,819 0,766 0,707 0,643 0,574 0,500 0,423 0,342 0,259 0,174 0,087 0,000 and at the graph in the following slide: J D Cunha

  19. SEEING information J D Cunha

  20. SEEING information • These two slides just point out what we already knew very well: our ability to get information is highly dependent on its form. • In general, a graph or image allow a much faster understanding than a list of numbers or a textual description. J D Cunha

  21. SEEING information • Visualization was used long before, but the Scientific Visualization and Information Visualization areas were born in the late 80’s. • The confluence of “push” and “pull” factors was determinant for that. J D Cunha

  22. SEEING information • “Push” factors • 30 years of experience in Computer Graphics • Availability of powerful graphical hardware • Developments in human-machine interfaces J D Cunha

  23. SEEING information • “Pull” factors • Ever greater amounts of data to store and analyze coming from: • Sophisticated simulations made possible by the available computing power • Very large and complex data bases J D Cunha

  24. SEEING information • Simplified reference model for visualization Data Mapping Rendering J D Cunha

  25. SEEING information Mapping Information is converted into geometry and/or graphical attributes. J D Cunha

  26. Scientific Visualization • Scientific Visualization or Visualization of Scientific Data is usually defined as concer-ned with visualization of data associated with a spatial grid, as opposed to Informa-tion Visualization which concentrates on more abstract kinds of data. J D Cunha

  27. The Visualization Toolkit - vtk • VTK is an object-oriented toolkit for 3D graphics(http://www.kitware.com/vtk.html) • Although tailored for the scientific visuali-zation field it can also be sucessfully used to illustrate the basics of 3D graphics and rendering. J D Cunha

  28. The Visualization Toolkit - vtk • The toolkit consists of a set of C++ classes providing the functionality to build 3D graphics applications, namely visualization applications, without the need for any low level programming. • Vtk is compatible with several graphical systems, namely OpenGL and X-Windows. J D Cunha

  29. The Visualization Toolkit - vtk • Vtk may be used from C++, Java or Tcl/Tk programmes. • In this talk Tcl/Tk will be used. J D Cunha

  30. The Visualization Toolkit - vtk • Vtk being object-oriented, we need only to create objects of the appropriate types and call the available methods. J D Cunha

  31. The Visualization Toolkit - vtk • Vtk object types can be grouped according to their functionality. • The most important object groups are: Sources, Mappers, Graphics and Filters. • We will now look in some detail at each group. J D Cunha

  32. The Visualization Toolkit - vtk • Sourcesare information provider objects. • Some sources are readers, that is, they get the information from files in appropriate formats. Examples: • vtkPLOT3DReader • vtkBYUReader • vtkPolyDataReader (one of vtk own formats) J D Cunha

  33. The Visualization Toolkit - vtk • Others generate data algorithmically. The typical example are the sources that create basic geometric shapes like • vtkSphereSource • vtkCylinderSource • vtkConeSource J D Cunha

  34. The Visualization Toolkit - vtk • Mappers, as suggested by the name itself, get the information provided by source objects, directly or through appropriate filters, and generate graphic primitives. • There are two types of mappers: • vtkDataSetMapper • vtkPolyDataMapper J D Cunha

  35. The Visualization Toolkit - vtk • A special type of mappers are the writers, which write out information in files with differente formats. Examples: • vtkBYUWriter • vtkTIFFWriter • vtkPolyDataWriter J D Cunha

  36. The Visualization Toolkit - vtk • Objects in the graphics group are respon-sible for the rendering portion of the visua-lization pipeline. J D Cunha

  37. The Visualization Toolkit - vtk • Objects in this group include: • vtkRenderer • vtkRenderWindow • vtkActor • vtkProperty • vtkTransform • vtkCamera • vtkLight J D Cunha

  38. The Visualization Toolkit - vtk • vtkRenderer is a virtual class. • But vtkOpenGLRenderer, which inherits from vtkRenderer, is a concrete class instan-tiated when the graphics systems is OpenGL. J D Cunha

  39. The Visualization Toolkit - vtk • Objects of type vtkRenderWindow repre-sent the application window. • The window will be a Windows window or an X window, according to the graphics system being used. J D Cunha

  40. The Visualization Toolkit - vtk • Each instance of vtkActor represents a scene “object”, combining the geometry (provided by the mapper) with the optical properties (colour, texture, etc) and con-crete values for the location, orientation and size. J D Cunha

  41. The Visualization Toolkit - vtk • Instances of vtkProperty are associated with actors to control its appearance. • Similarly, instances of vtkTransform are associated with actors to determine their location, orientation and size. J D Cunha

  42. The Visualization Toolkit - vtk • Instances of vtkCamera and vtkLight are associated with Renderer objects to specify how the scene is seen and illuminated. • If the user does not explicitely create objects of these two types, default ones are provided. J D Cunha

  43. The Visualization Toolkit - vtk • Filters are “transformation” objects and there are many types of filters available. • For example, the marching cubes and mar-ching squares algorithms are implemented as filters. The same is true for decimation, sampling, geometry extraction, threshol-ding, particle and many other algorithms. J D Cunha

  44. The visualization pipeline in vtk • The simplest pipeline includes a source, a mapper and an actor. • To be seen, actors must be associated with a renderer and the renderer associated to a window. J D Cunha

  45. vtkProperty Cubo_S Cubo_M Cubo_A vtkTransform r rw vtkCamera vtkLight The visualization pipeline in vtk J D Cunha

  46. Case study • We will now see and briefly discuss the application of vtk to meteorological data. • The data was provided by the Lisbon Meteorological Institute (IM) for use in a course of Computer Graphics for physics students. J D Cunha

  47. Case study • The data were collected with intervals of six hours between April 5 at 12h and April 6 at 12h. • Physical quantities measured are Tempera-ture, Humidity, Altitude and Wind velocity along the parallel and along the meridian. J D Cunha

  48. Case study • The grid is topologically and geometrically regular (cartesian grid), covering a region from -45º W to 45º E and from 80º N to 20º N, at 0.5º intervals. • This means a total of 108000 data points for each physical quantity. J D Cunha

  49. Case study • The data were measured at the so called “mid-atmosphere”, defined as the 500 hPa isobaric. • We will start by having a look at the data using WebWinds, a visualization program developped by the Jet Propulsion Lab (http://www.jpl.nasa.gov/directory) J D Cunha

  50. Case study • WebWinds is also object-oriented, but the objects are provided with a complete inter-face and a visual programming approach was adopted. J D Cunha

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