Welcome to the homepage of the lecture Image Processing and Computer Vision Winter term 2012 / 2013 

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Image Processing and Computer Vision
Lectures (4h) with theoretical and programming assignments (2h); NEWS: The results of the second written exam are now online. NEWS:
Opportunity for exam inspection: Type of Lectures – Prerequisites – Tutorials – Registration – Written Exam – Contents – Material for the Programming Assignments – Literature Broad introduction to mathematically wellfounded areas of image processing and computer vision. These fields are important in numerous applications including medical image analysis, computeraided quality control, robotics, computer graphics, multimedia and artificial intelligence. The classes qualify for starting a bachelor's thesis in our group. The lectures are continued in the summer term by the course "Differential Equations in Image Processing and Computer Vision" which leads to current research topics. Both courses are necessary in order to pursue a master's thesis in our group. This course is suitable for students of visual computing, mathematics, computer science, bioinformatics, computer and communications technology, and physics. It counts e.g. as a visual computing core course within the visual computing programme, an applied mathematics course within mathematics, or a core course (Stammvorlesung) in computer science. It is based on mathematical knowledge from the first two semesters. For the programming assignments, some elementary knowledge of C is required. The lectures are given in English. The tutorials include homework assignments (theory and programming) as well as classroom assignments. The programming assignments give an intuition about the way how image processing and computer vision algorithms work, while the theoretical assigments provide additional mathematical insights. Classroom assignments are supposed to be easier and should guide you gently to the main themes.
For the homework assignments you can obtain up to 24 points per week.
Actively participating in the classroom assignments gives you 12 more
points per week, regardless of the correctness of your solutions.
To qualify for both exams you need 2/3 of all possible points.
For 13 weeks, this comes down to 13 x 24 = 312 points.
Working in groups of up to 3 people is permitted, but all persons must be
in the same tutorial group. If you have questions concerning the tutorials, please do not hesitate to contact Pascal Peter. The tutorials are conducted by Leif Bergerhoff, Mohamed Omran, Sarah Schaeffer and Martin Schmidt.
Seven groups are scheduled for Tuesday and Wednesday afternoon:
If you have difficulties with the programming assignments, feel free to participate in
The tutors can be reached via the mail addresses: Registration is closed. It was open from Tue, Oct. 16, 2012, 3 pm until Fri, Oct. 19, 2012, 3 pm. You can now check which group you are finally in.
The results of the first written exam can be found
here, and the corresponding
distribution of points and grades
here.
The results of the second written exam can be found
here, and the corresponding
distribution of points and grades
here. You can pick up certificates from Gabriele Voss in Building E2.4, Room 111.
Course material is available on this webpage in order to
support the classroom teaching and the tutorials, not to replace
them. Additional organisational information, examples and explanations
that may be relevant for your understanding and the exam are provided
in the lectures and tutorials. It is solely your responsibility
 not ours  to make sure that you receive this infomation.
PART II: IMAGE PROCESSING
PART III: COMPUTER VISION AND IMAGE UNDERSTANDING
The following selftest problem sheet
contains 6 problems, which are intended to be similar in style
and difficulty to a 180minutes written exam.
Here you can download material for the programming assignments.
There is no specific text book for this class, but many of our image processing topics are covered in one of the following books:
Computer vision books include
These and further books can be found in the mathematics and computer
science library.


MIA Group 