Person in charge: | (-) |
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Credits | Dept. |
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7.5 (6.0 ECTS) | CS |
Person in charge: | (-) |
Others: | (-) |
The overall aim of this subject is for students to be familiar with the fundamentals of realistic visualisation and data. More specifically, upon finishing the subject, students should be familiar with the following:
- Existing illumination models, their limitations and applications.
- Using graphic libraries to enhance realism.
- The main applications used in science for visualising data, and the algorithms associated with them.
- The features of current graphic cards.
Estimated time (hours):
T | P | L | Alt | Ext. L | Stu | A. time |
Theory | Problems | Laboratory | Other activities | External Laboratory | Study | Additional time |
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
---|---|---|---|---|---|---|---|---|---|---|
9,0 | 0 | 10,0 | 0 | 10,0 | 9,0 | 0 | 38,0 | |||
The visualisation process and graphic cards. Algorithms for simulating transparencies, shadows, and reflections between objects. Image enhancement techniques: antialiasing. Advanced 2D-texture techniques.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
---|---|---|---|---|---|---|---|---|---|---|
9,0 | 0 | 6,0 | 0 | 9,0 | 9,0 | 0 | 33,0 | |||
Basic concepts. Shadows, reflections and transparencies. Techniques for speeding up calculations. Use of textures. Image enhancement techniques: antialiasing. Use of APIs for ray-tracing calculations. Applications.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
---|---|---|---|---|---|---|---|---|---|---|
9,0 | 0 | 9,0 | 0 | 6,0 | 9,0 | 0 | 33,0 | |||
Definition of data/scientific visualisation. Applications. Volume modelling. Classification and segmentation functions. Extraction of surfaces: Marching Cubes algorithm. Direct visualisation of volumes. 3D textures.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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9,0 | 0 | 3,0 | 0 | 3,0 | 9,0 | 0 | 24,0 | |||
Functional diagram. Vertex and pixel shaders. Examples of use.
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Total per kind | T | P | L | Alt | Ext. L | Stu | A. time | Total |
42,0 | 0 | 28,0 | 0 | 28,0 | 42,0 | 0 | 140,0 | |
Avaluation additional hours | 7,0 | |||||||
Total work hours for student | 147,0 |
The teaching methodology will be based based on weekly theory classes (3 hours) and lab classes (2 hours). Course concepts will be introduced in the theory classes and be consolidated and developed in the lab sessions.
The teacher will provide guidelines for the lab session exercises and furnish the concepts (e.g. the functions of various APIs) needed to carry out the lab work. Students must complete the design and programming of various applications related to the course contents. For this purpose, students will be provided with partially-programmed skeleton applications. The guidelines will be provided in advance. There will be three exercises: realistic visualisation using OpenGL functions (students may choose between the various options available); realistic visualisation using ray tracing; visualisation of volume models or scientific data. The exercises will be carried out by pairs of students.
* The final concepts exam (Nota_conceptes) will comprise short questions and/or exercises in which students must demonstrate their mastery of the concepts taught during the course.
* The lab exam (Nota_lab) will comprise questions concerning both practical work and the software used.
These exams will be held on the dates indicated by faculty members.
A grade will also be awarded for practical work (Nota_pract). The grade will be based on continuous assessment of the course's practical assignments. Exercises that are not submitted by the relevant deadline will be given a zero grade.
The course grade is based on the foregoing grades, and in accordance with the following formula:
Nota_curs = 0.5 Nota_conceptes + 0.2 Nota_lab + 0.3 Nota_pract.
VIG course.
To round off the training, students are recommended to take courses on computational geometry and geometric modelling.