Jens Grubert‎ > ‎Courses‎ > ‎

Computer Vision

During my studies I attended several Computer Vision related courses. Below are details about some of them. I also worked on a project on contour detection with subpixel accuracy.

3D Computer Vision

The extraction of 3D information from 2D images is the core task of 3D computer vision. Prof. Klaus D. Toennies introduced various methods for depth computation. 

The topics were:

  • Direct Depth Computation
  • Depth From Triangulation (Active Vision)
  • Camera Calibration
  • Stereo Vision (Area-Based and Feature-Based)
  • Motion and Depth
  • Computing Projected Motion
  • Surface Normals and Gradient Fields
  • Shading and Depth
  • Shape From Shading
  • Photometric Stereo

During the course my fellow sudent Thomas Seidel and I implemented a stereo vision algorithm based on belief propagation. Therefore we made use of markov random fields (MRF) as described by Felzenszwalb and Huttenlocher. So, the correspondence problem turned into a energy minimization problem which is solved with the use of the MRF.

Here are some of our results (left: input image | right: depth map)
Introduction to Signal Oriented Image Processing

During the winter term 2005 / 2006 I also got insight into the hardware oriented part of image processing. The topics included:

  • Image Acquisition Systems
  • Color Image Characteristics
  • Pattern Matching and Classification
  • Photogrammetric 3D Survey

Prof. Klaus D. Toennies introduced basic terms and algorithms in the area of image processing. I attended the course during the summer term 2005.

Image Acquisition and Image Coding


  • Fundamentals
    • Perceptual fundamentals
    • TV-Systems (Rasterscanning, Color Processing, Transmission)
    • Quantisation
  • Lossless Image Coding
    • Direct Coding
    • Fano-Shannon Coding
    • Huffman-Coding
    • Arithmetic Coding
    • Run Length Coding
    • Blockcoding
    • READ-Code
    • Encryption techniques
  • Lossy Image Coding
    • Digital Pulse-Code-Modulation
    • Interframe Prediction
    • Fouriertransformation (Discrete, Fast)
    • Walsh/Hadarmard Transformation
    • Haar Transformation
    • Discrete Sine / Cosine Transformation
    • Wavelet Transformation
    • Karhunen-Loeve-Transformation
    • Slant-Transformation
    • Radial-Basis-Functions
  • Semantic Image Coding
    • Binary Image Coding
    • Object Oriented Coding
    • Freeman-Code
    • Shape Coding
    • Contour Coding
    • Fractal Description
    • Sprites
    • Hybrid Approaches
  • Standards
    • JPEG
    • H.261/H.263
    • MPEG


Fundamentals of Image Processing

Here's a list of the course topics:

  • Digital Images
  • Disturbing Signal Influences
  • Fourier-Transformation
  • Wavelet- and Cosine-Transformation
  • Anti-Aliasing and Restauration
  • Image Compression
  • Pixel-Based Image Enhancements
  • Area-Based Image Enhancements
  • Segmentation
    • Region-Based
    • Feature-Based
    • Model-Based
  • Morphological Operators
  • Features and Classification