course-details-portlet

TDT4195 - Visual Computing Fundamentals

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Passed/Failed

Evaluation form Weighting Duration Examination aids Grade deviation
Home examination 50/100 4 hours
work 50/100 1 weeks

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

Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam (70%) and a coursework (30%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade.
If there is a re-sit examination, the examination form may change from written to oral.
In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken.

Course materials

To be announced at start of semester.

Credit reductions

Course code Reduction From To
SIF8043 7.5
Facts

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 3
Lab hours: 2
No.of specialization hours: 7

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Informatics
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Phone:

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD work 50/100
Room Building Number of candidates
Autumn ORD Home examination 50/100

Release 2020-12-16

Submission 2020-12-16

Release 09:00

Submission 13:00

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.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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