On July 30th, 2024, due to an important database update, there will be service interruptions in the Student Self-Service and Workforce Management areas between 8 AM and 11 AM. Thank you for your understanding.

193.125 Fundamentals of Computer Vision
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, VU, 4.0h, 6.0EC
TUWELLectureTube

Properties

  • Semester hours: 4.0
  • Credits: 6.0
  • Type: VU Lecture and Exercise
  • LectureTube course
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to name, explain and contrast the most important theories, principles, concepts and algorithms of computer vision. Their knowledge and understanding corresponds to the state-of-the-art literature in the field of computer vision.

Subject of course

The lecture will cover advanced computer vision methods in depth:


• Texture, Scenes, und Context
• Local- and Multiscale Representations
• Interest Points, Corners
• Scene Emergent Features
• Scene Recognition, Bag of Words, SIFT
• Clustering, Pyramid Matching, Support Vector Machine
• Deep Learning, CNNs
• Perceptron, Linear Basis Function Models, RBF
• Neural Networks architectures und learning methods
• Error functions and methods for parameter optimization (e.g., pseudo-inverse,
gradient descent, Newton method)
• Duality, Sparsity, Support Vector Machine
• Unsupervised methods and Self-Organizing Maps (SOM)

Teaching methods

Lectures of the theoretical concepts by means of slides, and programming tasks.

Mode of examination

Immanent

Additional information

ECTS breakdown (estimate, recommendation):


28 hrs. lecture
54 hrs. preparation units, individual preparation and tests
68 hrs. solving exercises and hand-in meetings
---------------------------------------------
150 hrs. corresponds to 6 ECTS at 25 hrs. each.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed09:00 - 11:0015.03.2023 - 28.06.2023FAV Hörsaal 1 Helmut Veith - INF Lecture
Fri09:00 - 11:0023.06.2023FAV Hörsaal 1 Helmut Veith - INF Substitute date - Lecture
Fundamentals of Computer Vision - Single appointments
DayDateTimeLocationDescription
Wed15.03.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed22.03.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed19.04.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed26.04.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed03.05.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed10.05.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed17.05.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed24.05.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed31.05.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed14.06.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Wed21.06.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture
Fri23.06.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Substitute date - Lecture
Wed28.06.202309:00 - 11:00FAV Hörsaal 1 Helmut Veith - INF Lecture

Examination modalities

Submission of 5 exercises

Taking 1 test

Course registration

Begin End Deregistration end
15.02.2023 00:00 14.03.2023 23:59 14.03.2023 23:59

Curricula

Study CodeObligationSemesterPrecon.Info
033 532 Media Informatics and Visual Computing Mandatory5. SemesterSTEOP
Course requires the completion of the introductory and orientation phase
033 535 Computer Engineering Mandatory electiveSTEOP
Course requires the completion of the introductory and orientation phase
066 453 Biomedical Engineering Mandatory electiveSTEOP
Course requires the completion of the introductory and orientation phase

Literature

No lecture notes are available.

Previous knowledge

Mathematics: vector and matrix calculus, from linear algebra
Programming, object-oriented programming
Computer Vision knowledge, from module Introduction to Visual Computing (both parts) and its prerequisite modules.

Python knowledge advantageous, but not required.

Preceding courses

Miscellaneous

Language

English