Course - Visual Computing Fundamentals - TDT4195
TDT4195 - Visual Computing Fundamentals
About
Examination arrangement
Examination arrangement: Aggregate score
Grade: Passed / Not Passed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Assignment | 50/100 | |||
| School exam | 50/100 | 3 hours | D |
Course content
Half of the course is concerned with image syntesis (computer graphics) and half of the course is on image analysis (image processing). Graphics: graphical primitives, rasterization, anti-aliasing, clipping, geometric transformations, viewing transformations, hierarchical scene modelling, culling and hidden surface elimination, colour representation, illumination models and algorithms. C/C++ OpenGL labs. Image processing: introduction to and examples of image processing and simple image analysis applications. Intro to deep learning based image interpretation and understanding (fully-connected neural networks and CNNs). Filtering and image enhancement in both the spatial domain as well as in the frequency / Fourier domain. Various image segmentation methods and mathematical morphology. Labs with assignments and Python (alternatively MATLAB). For more information see also: https://www.idi.ntnu.no/grupper/vis/teaching/ as well as Blackboard.
Learning outcome
Knowledge: The candidate will acquire knowledge of basic image synthesis and image analysis principles and algorithms. Skills: The candidate will acquire skills in graphics and image processing programming with commonly used tools. General competence: The candidate will gain competence in realising the potential of basic graphics and image processing techniques, an overview of visual computing, the ability to construct sizeable visual computing applications as well as to absorb further visual computing knowledge.
Learning methods and activities
Lectures and exercises. The lectures will be in English. The exam will be in English.
Further on evaluation
The course involves up to 6 assignments in graphics and image processing, that jointly count for 50% of the grade. A written examination makes up the other 50%. The final result is A-F. If there is a re-sit examination, the examination form may change from written to oral.
Recommended previous knowledge
TDT4120 Algorithms and Datastructures and TMA4115 Calculus 3 or equivalent.
Course materials
To be announced at start of semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| SIF8043 | 7.5 |
Version: 1
Credits:
7.5 SP
Study level: Third-year courses, level III
Term no.: 1
Teaching semester: AUTUMN 2022
Language of instruction: English
Location: Trondheim
- Informatics
- Technological subjects
Department with academic responsibility
Department of Computer Science
Examination
Examination arrangement: Aggregate score
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD School exam 50/100 D 2022-12-03 15:00 INSPERA
-
Room Building Number of candidates SL111 orange sone Sluppenvegen 14 59 SL111 lyseblå sone Sluppenvegen 14 63 SL430 Sluppenvegen 14 2 SL425 Sluppenvegen 14 1 SL238 Sluppenvegen 14 1 - Autumn ORD Assignment 50/100
-
Room Building Number of candidates - Summer UTS School exam 50/100 D INSPERA
-
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"