Fachgebiet Augmented Vision



Because of the current situation with the corona virus pandemic, the lecture 2D Image Processing will be offered as an online course. There will be no lecturer in the rooms mentioned in the KIS-system. Instead, students should register to the course by sending an e-mail to sheela_raju.kurupathi(at)dfki.de  before 30th of April.

The content of the lecture will be updated on this page at the appointments defined in the KIS lecture and exercises appointments.


Lecture: Monday, 15:30-17:00
Exercise: Friday, 15:15 – 16:45


Prof. Dr. Didier Stricker

Fangwen Shu (Fangwen.Shu@dfki.de)



  • Color, HDR, image interpolation
  • Filters
  • Edges and corners
  • Feature tracking and optical flow
  • Detection and classification
  • Bayes Tracking (Kalman, EKF, and particle filters)

Slides and Online Course Material

The slides and videos will be continuously added here:




Homework assignments (6 throughout semester) will consist of a theoretical part (questions) and a practical part (using OpenCV and Python), to be solved in groups of 2 or maximum of 4 students.

Answers to questions and implementations must be handed in via email:

  • Homework submission is mandatory for being eligible to participate in the exam
  • Submission deadline, tutor and online exercise session will be given on each assignment

Tutorial sessions will be held shortly after submission deadline:

  • Discussion of last exercise
  • Presentation/prepartion of current exercise
  • Discussion of lecture
  • Friday, 15:15 – 16:45, online!

Exercise sheets

Exercices and material:

  • Exercise 1:  04.05.2020 (Exercise01) Submission Deadline: 14.05.2020
  • Exercise 2:  19.05.2020 (Exercise02) Submission Deadline: 29.05.2020
  • Exercise 3:  29.05.2020 (Exercise03) Submission Deadline: 12.06.2020
  • ... More to follow

Examination Date

There will be a written examination conducted in the end of the course. Exact dates will be provided below. 


Bibliography (textbooks)

  • David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach
  • Richard Szeliski, Computer Vision: Algorithms and Applications
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