Fachgebiet Augmented Vision


Exams will be written (no oral exams).

Room and Time

Lecture: 48-210, Monday, 15:30-17:00

Exercise: 48-379, Friday, 15:15 – 16:45



Prof. Dr. Didier Stricker 
Kripasindhu Sarkar


  • Color, HDR
  • Filters
  • Edges and Corners
  • Feature tracking and optical flow
  • Object detection
  • Neural networks


The slides will be continuously added here:

  • 13.05.2019: Introduction to OpenCV
  • 20.05.2019: Blobs + Descriptors
  • 27.05.2019: Optical Flow 
  • 03.06.2019: Object recognition and SVM
  • 17.06.2019: Face detection and Recognition (Adaboost)
  • 24.06.2019: Introduction to PyTorch and CNN
  • 01.07.2019: Tracking: intro to bayes filtering
  • 08.07.2019: Tracking: bayes filtering, KF
  • 15.07.2019: Tracking: EKF



Homework assignments (4-5 throughout semester) will consist of a theoretical part (questions) and a practical part (using OpenCV), to be solved in groups of 2 students.

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

  • Homework submission is mandatory for being eligible to participate in the oral exam
  • Submission deadline, tutor and 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, 15:30-17:00, room 48-379

Exercise sheets

    Exercices and material:

    • Exercise 1:  17.05.2019
    • ... More to follow

    Examination Date

    There will be oral examinations conducted in the end of the course. Exact dates will be provided below. 

    Students have to register for the exam by sending an email to Mrs. Keonna Cunningham (Keonna.Cunningham@dfki.de)

    Bibliography (textbooks)

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