Title: Real-time visual off-road path detection
Authors: Krämer, Marc Steven
Kuhnert, Lars
Kuhnert, Klaus-Dieter
Citation: WSCG 2018: full papers proceedings: 26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS Association, p. 78-87.
Issue Date: 2018
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: wscg.zcu.cz/WSCG2018/!!_CSRN-2801.pdf
ISBN: 978-80-86943-40-4
ISSN: 2464–4617 (print)
2464–4625 (CD-ROM)
Keywords: detekce silnic;terénní autonomní navigace;segmentace obrazu;klasifikace terénu;mobilní roboty
Keywords in different language: road detection;off-road autonomous navigation;image segmentation;terrain classification;mobile robots
Abstract: In this paper, we propose a fast and real-time capable system for visual off-road path detection. We equipped our robot AMOR with a single monocular camera and explored unstructured environments like woods. In these areas, it is almost harder to identify and classify drivable and non-drivable parts in an image. In urban regions, roads can be detected by lane markers or delimitations whereas the boundaries of a forest path blend into the environment almost seamlessly. In our work, we developed a software system that is based on mostly simple and low computationally intensive algorithms. We developed and tested the functions with a large dataset of camera images and also generated a manually Ground Truth for the evaluation.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG 2018: Full Papers Proceedings

Files in This Item:
File Description SizeFormat 
Kramer.pdfPlný text12,17 MBAdobe PDFView/Open

Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/34627

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.