Course detail

Data Visualisation

FSI-SVDAcad. year: 2020/2021

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.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

doc. PaedDr. Dalibor Martišek, Ph.D.

Department

Institute of Mathematics (ÚM)

Learning outcomes of the course unit

Students will be able to visualise the common types of 3D data that are not suitable for tabulation.

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)

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.

Assesment methods and criteria linked to learning outcomes

Graded course-unit credit is awarded on condition of having worked out semester work

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

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

Specification of controlled education, way of implementation and compensation for absences

Missed lessons may be compensated for via a written test.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Chen, C, Hardle, W., Unwin, A.: Handbook of Data Visualization, Springer-Verlag. 2008 (EN)
Martišek, K.: Adaptive filters for 2-D and 3-D Digital Images Processing, FME BUT Brno, 2012 (EN)
Wilke, C.O: Fundamentals of Data Visualization, O’Reilly Media, 2019 (EN)

Recommended reading

Martišek, D.: Matematické principy grafických systémů, Littera, Brno 2002 (CS)

Classification of course in study plans

  • Programme M2A-P Master's

    branch M-MAI , 2 year of study, summer semester, compulsory

Type of course unit

 

Lecture

13 hod., optionally

Teacher / Lecturer

doc. PaedDr. Dalibor Martišek, Ph.D.

Syllabus

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

Computer-assisted exercise

26 hod., compulsory

Teacher / Lecturer

doc. PaedDr. Dalibor Martišek, Ph.D.

Syllabus

1) Curves defined by equation f(x,y)=0 – pixel algorithm
2) Surfaces defined by equation f(x,y,z)=0 – pixel algorithm
3 Curves defined by equation f(x,y)=0 – grid algorithm
4) Surfaces defined by equation f(x,y,z)=0 – marching cubes algorithm
6) Contour lines of surface, surface visualisation using the palette
7) 2D visualisation of 3D data grid
8) 3D visualisation of 3D data grid using marching cubes algorithm, 3D filters
9) 3D visualisation using volume methods – ray casting.
10) 2D and 3D reconstruction of confocal microscope outputs
11,12) 2D and 3D reconstruction of Visible Human Project data
13.14. Semester work processing.
Presence in the seminar is obligatory.