Visual Navigation
Vortragende/r (Mitwirkende/r) |
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Umfang | 4 SWS |
Semester | Wintersemester 2022/23 |
Unterrichtssprache | Englisch |
Termine
- 21.10.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 21.10.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 28.10.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 28.10.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 04.11.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 04.11.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 11.11.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 11.11.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 18.11.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 18.11.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 25.11.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 25.11.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 02.12.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 02.12.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 09.12.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 09.12.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 16.12.2022 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 16.12.2022 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 13.01.2023 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 13.01.2023 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 20.01.2023 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 20.01.2023 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 27.01.2023 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 27.01.2023 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 03.02.2023 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 03.02.2023 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
- 10.02.2023 13:15-14:45 N 1179, Wilhelm-Nusselt-Hörsaal
- 10.02.2023 15:00-16:30 N 1179, Wilhelm-Nusselt-Hörsaal
Teilnahmekriterien
Lernziele
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.
Beschreibung
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.
Inhaltliche Voraussetzungen
Linear algebra, analysis.
Ideally, the student would have attended a computer vision class (such as (EI2223(alt)/EI7120(neu) ), but this is not mandatory.
Studien-, Prüfungsleistung
Written exam, February 2017, date and room TBD.