Siehe TUMonline

After attending the course, the students will be able to apply the basic principles of visual navigation and sensor fusion, and to develop their own algorithms for the navigation and guidance of autonomous vehicles.

Elements of computer vision and image processing: image formation and characteristics; feature detection, description, tracking and matching. Introduction to camera models. 2D/3D projective geometry. Single- and dual-view geometry. Camera motion estimation and mapping of sensed environment. Elements of probabilistic estimation. Simultaneous localization and mapping techniques.

Linear algebra, analysis. Ideally, the student would have attended a computer vision class (such as (EI2223(alt)/EI7120(neu) ), but this is not mandatory.

Written exam, February 2017, date and room TBD.