Data Visualisation

Additional Info

  • ECTS credits: 4
  • Semester: 2
  • University: Brno University of Technology
  • Prerequisites:

    Students are expected to be familiar with basic programming techniques and their implementation in Borland Delphi, and with basic 2D and 3D graphic algorithms (colour systems, projection, curves and surfaces construction)

  • Objectives:

    Students will be made familiar with basic methods of 3D data reconstruction and conditions for their use.

  • Topics:

    1) Curves defined by equation f(x,y)=0, surfaces defined by equation f(x,y,z)=0 – pixel algorithm.

    2) Curves defined by equation f(x,y)=0 – grid algorithm.

    3) Surfaces defined by equation f(x,y,z)=0 – marching cubes algorithm.

    4) Contour lines of surface.

    5) Surface visualisation using the palette.

    6) 2D visualisation of 3D data grid.

    7) 3D visualisation of 3D data grid using marching cubes algorithm.

    8) 3D filters.

    9) 3D visualisation using volume methods – ray casting.

    10) 2D reconstruction of confocal microscope outputs.

    11) 3D reconstruction of confocal microscope outputs.

    12) 2D reconstruction of Visible Human Project data.

    13) 3D reconstruction of Visible Human Project data.

  • Books:

    Martišek, K.: Adaptive filters for 2-D and 3-D Digital Images Processing, FME BUT Brno, 2012

  • More information:

    The course is lectured in winter semester in the fourth year of mathematical engineering study. It familiarises students with basic principles of basic algorithm of computer modelling of 2D and 3D data, namely of scalar fields. Lecture summary: Construction of implicit curves and surfaces, contour lines and iso-surfaces. Algorithms, which construct surfaces – marching cubes and volume algorithms - ray casting, ray tracing.

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