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 conferenceObject |
URI: | wscg.zcu.cz/WSCG2018/!!_CSRN-2801.pdf http://hdl.handle.net/11025/34627 |
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 | Size | Format | |
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Kramer.pdf | Plný text | 12,17 MB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/34627
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