Positive of all exercises followed by oral examination. Weight for finalgrade: Labs:Lecture 60:40.
Workload for exams
Gaining knowledge in the theory of machine vision as it is relevant for the application oriented use in robotics and automation technology. Knowledge of the methods from the sub-fields to solve problem cases in the area of robotics and automation technology.
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.