DagRep.5.11.36.pdf
- Filesize: 1.02 MB
- 26 pages
Document
Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)
Authors and all authors of the abstracts in this report
-
Part of:
Issue:
Dagstuhl Reports, Volume 5, Issue 11
Volume: Dagstuhl Reports, Volume 5
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2016-03-11
Cite AsGet BibTex
André Bruhn, Atsushi Imiya, Ales Leonardis, and Tomas Pajdla. Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461). In Dagstuhl Reports, Volume 5, Issue 11, pp. 36-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
https://doi.org/10.4230/DagRep.5.11.36
https://doi.org/10.4230/DagRep.5.11.36
Abstract
The vision-based autonomous driving and navigation of vehicles has a long history. In 2013, Daimler succeeded autonomous driving on a public drive way. Today, the Curiosity mars rover is sending video views from Mars to Earth. Computer vision plays a key role in advanced driver assistance systems (ADAS) as well as in exploratory and service robotics. Continuing topics of interest in computer vision are scene and environmental understanding using single- and multiple-camera systems, which are fundamental techniques for autonomous driving, navigation in unknown environments and remote visual exploration. Therefore, we strictly focuses on mathematical, geometrical and computational aspects of autonomous vehicles and autonomous vehicular technology which make use of computer vision and pattern recognition as the central component for autonomous driving and navigation and remote exploration.
Keywords
- Vision-based autonomous driving and navigation
- Exploratory rovers
- Dynamic 3D scene understanding
- Simultaneous localization and mapping
- On-board algorithms
Metrics
- Access Statistics
-
Total Accesses (updated on a weekly basis)
0PDF Downloads