Learn about 3D reconstruction from images as well as computer vision methods needed for mobile robotics.
All the lectures will be online. The first lecture will happen as a streaming event, further lectures will be pre-recorded videos which can be accessed at any time. There will be Q&A sessions as live stream for direct interaction. To get access information to the online lectures students need to be registered. The information can then be found in the Teach Center.
The practical is organized as programming assignments which can be carried out from home. The practical is organized as group work in groups of 2. This is important such that you do have the possibility to discuss the topics of the practical with a peer. Assignment handouts will be held as streaming events. There will be also online Q&A sessions with a student assistent.
The course is organized as a lecture and practical. It is advised to take both of them at the same time. To pass the lecture an exam has to be taken. Exam dates will be published in TUG-Online. The practical part is organized as programming assignments and carried out in groups of 2.
The practical consists of programming assignments. The practical will be done as group work in groups of 2 students. There will be 3 assignments to be completed through the semester. The assignments need to be programmed in C/C++ with the help of the OpenCV computer vision library. The first assignment will be about camera calibration. The second assignment will be about feature matching and 2 view geometry estimation. The third assignment will be depth estimation using deep learning.
There will not be weekly meetings for the practical. There will however be tutor hours on selected dates.
The assignments will be available in the teach center and will also be handed out and discussed in the lecture slots.
Grades for the lecture can be obtained by taking a written exam. Exam dates will be published in TUG-Online. The grades for the practical (INP.32989UF) are independent of the lecture and will be determined based on the submitted programming assignments.
(slides will gradually appear here)
(website updated on 24.02.2021)