After successful completion of the course, students are able to solve first problems in the fields of in machine vision: basic computer vision methods, edge detection, region description, feature extraction, object tracking, depth image acquisition, methods of 2D and 3D object recognition, Gestalt theory, depth image processing, cognitive vision; Focus in robotics on cognitive robots, situated vision for robotics, and robot systems.
Emphasis is on the following topics in machine vision: basic computer vision methods, edge detection, region description, feature extraction, object tracking, depth image acquisition, methods of 2D and 3D object recognition, Gestalt theory, depth image processing, cognitive vision; Focus in robotics on cognitive robots, situated vision for robotics, and robot systems.
Positive of all exercises followed by oral examination. Weight for final grade: Labs:Lecture 60:40.
Due to the current situation, the oral exams will be conducted remotely using GoToMeeting until further notice.
Matlab is mandatory; Background in Robotics is recommended, e.g., 376.040 Fachvertiefung Bildverarbeitung und Robotik. Python is helpful.