course-details-portlet

TK8155

Advanced Visual Perception Systems

Credits 7.5
Level Doctoral degree level
Course start Autumn 2025
Duration 1 semester
Language of instruction English
Location Trondheim
Examination arrangement Aggregate score

About

About the course

Course content

The course is given every second year, next time in autumn 2025. The course builds on the basic knowledge gained from the robotic vision course TTK4255 with a focus on motion estimation, non-linear estimation methods and object recognition, the underlying theoretic foundation, and implementation skills. The course is given in English.

Learning outcome

Scientific Contents (a selection will be made with respect to interest and participation background):

* optimization, estimation, and uncertainty models for robotic vision systems

* motion estimation, optical flow, scene flow

* scene and place recognition

* dense, semi-dense, sparse matching

* shape priors and estimation

* pose estimation and tracking

* semantic scene understanding

* statistical models and uncertainties

* segmentation and fitting using probabilistic methods

* correspondence and pose consistency

* recognition by relations between templates

SKILLS:

* Proficiency in linear and non-linear estimation methods on image and video data, statistics, and probabilistic methods

* Proficiency in critical thinking and evaluation of disadvantages of different methods and approaches to make a qualified choice of methods for a given system

* Proficiency in designing motion estimation, and object recognition systems

GENERAL COMPETENCE:

* Skills in applying this knowledge and proficiency in new areas and completing advanced tasks and projects

* Skills in communicating extensive independent work, and mastering the technical terms of advanced visual perception techniques

* Ability to contribute to innovative thinking and innovation processes

Learning methods and activities

Study groups and optional problem sets. Project with report.

Required previous knowledge

TTK4115 Linear Systems Theory or similar.

Course materials

A collection of papers, which will be given at the beginning of the semester.

Subject areas

  • Engineering Cybernetics

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Engineering Cybernetics

Examination

Examination

Examination arrangement: Aggregate score
Grade: Passed / Not Passed

Ordinary examination - Autumn 2025

Report
Weighting 50/100 Exam system Inspera Assessment
Oral exam
Weighting 50/100 Examination aids Code D Duration 20 minutes

Ordinary examination - Spring 2026

Report
Weighting 50/100 Exam system Inspera Assessment
Oral exam
Weighting 50/100 Examination aids Code D Duration 20 minutes