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
Basic knowledge of linear algebra, analysis, probability theory, Python programming
Tuesday, 10:15-11:45, CP1-HSZ / Hörsaal 3
Friday, 10:15-11:45, CP1-HSZ / Hörsaal 3
Start: Tuesday, 8.10.
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, Endenicher Allee 19a, 2.025
Wednesday, 12:15-13:45, Endenicher Allee 19a, 2.025
Start: Monday, 14.10.
Written, details will be announced.