Tentative: Linear filters, Edges, Derivatives, Hough Transform, Segmentation, Graph Cuts, Mean Shift, Active Contours, Level Sets, MRFs, Expectation Maximization, Background Subtraction, Temporal Filtering, Active Appearance Models, Shapes, Optical Flow, 2D Tracking, Cameras, 2D/3D Features, Stereo, 3D Reconstruction, 3D Pose Estimation, Articulated Pose Estimation, Deformable Meshes, RGBD Vision
The course will be hybrid. The lectures will be recorded and recorded lectures and slides will be shared. The link for the slides and recordings will be provided in the first lecture. If you cannot attend the first lecture, you will get it per email after the registration for the exercises. The exercises will be on-line and not recorded. The slides and recordings are available at: Slides.
Basic knowledge of linear algebra, analysis, probability theory, Python programming
Monday, 10:15-11:45, HSZ / HS 1
Friday, 10:15-11:45, Meckenheimer Allee 176 / HS IV
Start: Monday, 11.10.
Theory and programming. At least 50% of the exercise points are required to qualify for exam. The programming exercises are implemented in Python and OpenCV. The focus of the exercises is on implementing algorithms presented in the lecture. If you are not comfortable with OpenCV, we recommend to have a look at the OpenCV Tutorials. The first exercise sheet, which is an introduction to OpenCV, will be released on the date of the first lecture.
Monday, 14:15-15:45 (zoom)
Wednesday, 12:15-13:45 (zoom)
Start: Monday, 18.10.
Registration period: 1.12.-11.1.
Exam: Thursday, 17.2., 12:30-14:30, Wolfgang-Paul-Hörsaal, Kreuzbergweg 28
2nd Exam: Monday, 28.3., 11:15-13:15, CP1-HSZ / Hörsaal 2