Experimental Setup for Neural Networks and Camera-Based Navigation of Mobile Systems
- The aim of this work is the application and evaluation of a method to visually detect markers at a distance of up to five meters and determine their real-world position. Combinations of cameras and lenses with different parameters were studied to determine the optimal configuration. Based on this configuration, camera images were taken after proper calibration. These images are then transformedThe aim of this work is the application and evaluation of a method to visually detect markers at a distance of up to five meters and determine their real-world position. Combinations of cameras and lenses with different parameters were studied to determine the optimal configuration. Based on this configuration, camera images were taken after proper calibration. These images are then transformed into a bird's eye view using a homography matrix. The homography matrix is calculated with four-point pairs as well as with coordinate transformations. The obtained images show the ground plane un distorted, making it possible to convert a pixel position into a real-world position with a conversion factor. The proposed approach helps to effectively create data sets for training neural networks for navigation purposes.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/5314 | Bibliografische Angaben |
Title (English): | Experimental Setup for Neural Networks and Camera-Based Navigation of Mobile Systems |
Conference: | International Scientific Conference Electronics (30. : 15-17 Sept. 2021 : Sozopol, Bulgaria) |
Author: | Stefan HenselStaff MemberORCiDGND, Marin B. Marinov, Adrian Seigel, Borislav Ganev |
Year of Publication: | 2021 |
Publisher: | IEEE |
Page Number: | 5 |
First Page: | 1 |
Last Page: | 5 |
Parent Title (English): | 2021 XXX International Scientific Conference Electronics |
ISBN: | 978-1-6654-4518-4 (Online) |
ISBN: | 978-1-6654-4519-1 (Print on Demand) |
DOI: | https://doi.org/10.1109/ET52713.2021.9579521 |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
Institutes: | Bibliografie |
Tag: | autonomous systems; camera-based navigation; neural networks; statistical methods, ROS; style | Formale Angaben |
Open Access: | Closed Access |
Licence (German): | Urheberrechtlich geschützt |