Scientific visualization (2018/2019)



Course code
4S02714
Credits
6
Coordinator
Andrea Giachetti
Academic sector
INF/01 - INFORMATICS
Language of instruction
Italian
Teaching is organised as follows:
Activity Credits Period Academic staff Timetable
Teoria 4 I semestre Andrea Giachetti

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Laboratorio 2 I semestre Andrea Giachetti

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Learning outcomes

The course aims to provide the student with basic information on scientific and information visualization techniques.
Furthermore, it gives the student the tools needed to master algorithms and computational methods upon which many interactive computer graphics applications are based. The
focus is on understanding the theory (geometry, radiometry) and
the computational issues (algorithms, programming) that lie behind computer-generated images.
At the end of the course, the students will be able to:
-Use smartly visualization techniques and tools
-Understand the functionality of the graphics pipeline of computers
-Understand the basics of 3D modeling and rendering algorithms
-Design and implement simple graphics and visualization applications

Syllabus

1. Introduction to visualization
- Scientific and information visualization
- Graphics and data visualization
- The scientific visualization process

2. Fundamentals of graphics: Geometric modeling
-The Euclidean space
- Representations of objects
-Mesh, curves and surfaces (outline)
- Solid construction geometry (outline)
- Spatial partitioning (outline)

3. Rendering and lighting
- Introduction to rendering: ray casting
- Physical model: outline of radiometry, BRDF, rendering equation

4. Lighting models
- Phong model
- Types of lights

5. Rasterization pipeline
- Geometric transformations
- Clipping
- Removing hidden surfaces: list-priority, depth-buffer
- Scan conversion
- Shading: Flat, Phong and Gouraud
- The OpenGL pipeline
- Texture mapping

6. Other techniques for scientific visualization
- Isosurfaces
- Direct volume rendering

7. Laboratory (24h)
- Effective plots
- Images and volumes
- Paraview tutorial

Assessment methods and criteria

Written test (20/30) and evaluation of graphics programming skills (10/30)

To pass the exam students must demonstrate that:
- to have understood principles and methods of Scientific Visualization
- they have understood the basic algorithms related to modeling, lighting and rasterization pipeline
- they are able to describe these concepts in a clear and exhaustive way
- they are able to apply the acquired knowledge to solve application scenarios described by means of exercises, questions, and projects.

Written test:
The written test is composed of a few open questions and/or exercises testing the understanding of the different topics of the course.


Lab test:
The exam consists of the evaluation of exercises developed during the lab sessions.
For students who cannot attend the lab sessions, it will be assigned a project (typically a Visualization task to be realized with Paraview) to be completed, documented and discussed in an oral presentation.

Details and guidelines on the examination modalities are available in the e-learning area of the course.

STUDENT MODULE EVALUATION - 2017/2018