Lecturer: Mohammed Abbass

Objectives

While Computer Graphics focusses on image synthesis, Computer Vision is all about image analysis and image understanding. It finds many applications in domains such as 3D reconstruction, robotics, medical engineering, media technology, automatization, biometry, human-computer interaction, contact free measurement, remote sensing, quality control, etc. The associated lecture will give first insights into the basics of Computer Vision  and links to corresponding machine learning approaches. . At the end of the semester, participants of this class will be able to apply and implement computer vision methods independently. A basic understanding of programming concepts is required. Detailed knowledge of a programming language, however, is not necessary. This lab will provide a sufficient introduction into python, python modules, and hands-on computer vision techniques to prepare students for their team projects.

Subject

Introduction to Python, introduction to python modules (Scikit-image and OpenCV), introduction to this semester's project, team research project. 

Selected Readings

1. Computer Vision – A Modern Approach, Forsyth and Ponce, Addison Wesley
2. Multiple View Geometry in Computer Vision, Hartley and Zisserman, Cambridge Press
3. Computer Vision: Algorithms and Applications, Richard Szeliski, Springer
4. Image Processing: The Fundamentals, Maria Petrou and Costas Petrou, Wiley
5. Learning OpenCV: Computer Vision with the OpenCV Library, Gary Bradski, Adrian Kaehler, Mike Loukides, Robert Romano, O'Reilly 
6. Handbook of Mathematical Models in Computer Vision, Nikos Paragios and Yunmei Chen, Springer
7. Machine Vision. Theory, Algorithms, Practicalities: Theory, Algorithms, Practicalities: Theory, Algorithms, Practicalities, E. R. Davies, Academic Press
8. Computational Vision: Information Processing in Perception and Visual Behavior, Hanspeter A. Mallot, MIT Press
9. Three-Dimensional Computer Vision – A Geometric Approach, Olivier Faugeras, MIT Press

Criteria for Evaluation

Team project (project presentations and results)