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Image Processing and Computer Graphics

Prof. Thomas Brox, Prof. Matthias Teschner

Image Processing and Computer Graphics have impact not only in computer science but also in other research areas, such as biology or medicine. Image processing is quite important in robotics and many industrial applications. Computer graphics dominates the movie theaters. This course gives a broad overview of these fields and introduces some basic techniques. It is highly recommended to take this course before attending other classes in computer vision or computer graphics. Consequently, if you think about specializing in these fields, you should take this course as early as possible. The exercises are intended to give you a better understanding of the most important techniques you learn in class. You are supposed to implement some selected methods in C/C++ and develop an intuition of their usage.

Due to the Corona pandemic, the complete course on Image Processing will be provided as online course. This includes both the lectures and the exercises. You can find the lectures below for download. They have been recorded before the pandemic. In addition there will Zoom meetings where we will go over the slides and where you can ask questions. It is highly recommended to watch the recordings before the corresponding meeting, as the online classes focus on questions. For the exercises there will be a discussion forum that you can use to interact with other students. The advisors of the exercises will also offer Zoom meetings to ask questions about the exercises.

For details on the Computer Graphics part, please refer to the site of Prof. Teschner

test exam including the solution is available.
Class:
(3 SWS)
10:00–11:30
Online meeting. See dates below.
Exercises:
(1 SWS)
10:00–11:30
Online meeting. See dates and exercise material below.
There is also a discussion forum, which will be available from June 14.
Contact Persons (Image Processing only) Jan Bechtold, Philipp Schröppel
Beginning: First video conference on June 14.

ECTS-Points: 6
Recommended Semester:   4-6 (Bachelor), 1-2 (Master)
Requirements: Fundamental mathematical knowledge and programming skills in C/C++

Exam: Written exam 15.9.2021 9:00-10:30.

Further Remarks: All course material is in English.

Object segmentation

Materials

Below you find all the slides, recordings, and exercise materials for this course. Note that the materials are being updated on the fly, so only the next upcoming classes will be up-to-date. Recordings are about 250MB each; some are much bigger due to videos. The German recordings are from few years ago and do not perfectly match the structure of the course anymore.

DateTopicSlidesRecordings Exercises

14.6. Class 1: Introduction and image basics Slides Class 1 English
15.6. Class 2: Noise, basic operators and filters Slides Class 2 English | German 21.7. | Material | Solution
22.6. Class 3: Energy minimization Slides Class 3 English | German
28.6. Class 4: Variational methods Slides Class 4 English | German
29.6. Class 5: Motion estimation Slides Class 5 English | German 05.7. | Material Solution
6.7. Class 6: Matching and local descriptors Slides Class 6 English | German 12.7. | Material Solution
13.7. Class 7: 3D reconstruction Slides Class 7 English | German
19.7. Class 8: Recognition and Deep Learning Slides Class 8 English | German
20.7. Class 9: Segmentation Slides Class 9 English | German
26.7. Last exercise session 26.7.

There is a forum for discussion, which will be available from June 14.