2 Search Results for "Bruhn, Andr�s"


Document
Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)

Authors: André Bruhn, Atsushi Imiya, Ales Leonardis, and Tomas Pajdla

Published in: Dagstuhl Reports, Volume 5, Issue 11 (2016)


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.

Cite as

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)


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@Article{bruhn_et_al:DagRep.5.11.36,
  author =	{Bruhn, Andr\'{e} and Imiya, Atsushi and Leonardis, Ales and Pajdla, Tomas},
  title =	{{Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)}},
  pages =	{36--61},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{5},
  number =	{11},
  editor =	{Bruhn, Andr\'{e} and Imiya, Atsushi and Leonardis, Ales and Pajdla, Tomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.5.11.36},
  URN =		{urn:nbn:de:0030-drops-57639},
  doi =		{10.4230/DagRep.5.11.36},
  annote =	{Keywords: Vision-based autonomous driving and navigation, Exploratory rovers, Dynamic 3D scene understanding, Simultaneous localization and mapping, On-board algorithms}
}
Document
Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471)

Authors: Andrés Bruhn, Thomas Pock, and Xue-Cheng Tai

Published in: Dagstuhl Reports, Volume 1, Issue 11 (2012)


Abstract
This report documents the program and the results of Dagstuhl Seminar 11471 Efficient Algorithms for Global Optimisation Methods in Computer Vision, taking place November 20-25 in 2011. The focus of the seminar was to discuss the design of efficient computer vision algorithms based on global optimisation methods in the context of the entire design pipeline. Since there is no such conference that deals with all aspects of the design process -- modelling, mathematical analysis, numerical solvers, and parallelisation -- the seminar aimed at bringing together researchers from computer science and mathematics covering all four fields.

Cite as

Andrés Bruhn, Thomas Pock, and Xue-Cheng Tai. Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471). In Dagstuhl Reports, Volume 1, Issue 11, pp. 66-90, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)


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@Article{bruhn_et_al:DagRep.1.11.66,
  author =	{Bruhn, Andr\'{e}s and Pock, Thomas and Tai, Xue-Cheng},
  title =	{{Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471)}},
  pages =	{66--90},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2012},
  volume =	{1},
  number =	{11},
  editor =	{Bruhn, Andr\'{e}s and Pock, Thomas and Tai, Xue-Cheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.1.11.66},
  URN =		{urn:nbn:de:0030-drops-33789},
  doi =		{10.4230/DagRep.1.11.66},
  annote =	{Keywords: Computer Vision, Modelling, Mathematical Foundations, Data Structures, Efficient Algorithms, Parallel Computing}
}
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