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Course detail

Data Visualisation

Course unit code: FSI-SVD
Academic year: 2016/2017
Type of course unit: compulsory
Level of course unit: Master's (2nd cycle)
Year of study: 2
Semester: summer
Number of ECTS credits:
Learning outcomes of the course unit:
Students will be able to visualise the common types of 3D data that are not suitable for tabulation.
Mode of delivery:
90 % face-to-face, 10 % distance learning
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.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
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.
Recommended or required reading:
Martišek, D.: Matematické principy grafických systémů, Littera, Brno 2002
Martišek, D.: Matematické principy grafických systémů, Littera, Brno 2002
Martišek, K.: Adaptive filters for 2-D and 3-D Digital Images Processing, FME BUT Brno, 2012
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
Language of instruction:
Czech
Work placements:
Not applicable.
Course curriculum:
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.

Type of course unit:

Lecture: 13 hours, 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
seminars in computer labs: 26 hours, 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.

The study programmes with the given course