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Documents authored by Leonardis, Ales

Document
DOI: 10.4230/DagRep.5.11.36
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
DOI: 10.4230/DagRep.1.3.67
Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)

Authors: Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, and Jan Peters

Published in: Dagstuhl Reports, Volume 1, Issue 3 (2011)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 11131 ``Exploration and Curiosity in Robot Learning and Inference''. This seminar was concerned with answering the question: how should a robot choose its actions and experiences so as to maximise the effectiveness of its learning?}. The seminar brought together workers from three fields: machine learning, robotics and computational neuroscience. The seminar gave an overview of active research, and identified open research problems. In particular the seminar identified the difficulties in moving from theoretically well grounded notions of curiosity to practical robot implementations.
Cite as

Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, and Jan Peters. Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131). In Dagstuhl Reports, Volume 1, Issue 3, pp. 67-95, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@Article{wyatt_et_al:DagRep.1.3.67,
  author =	{Wyatt, Jeremy L. and Dayan, Peter and Leonardis, Ales and Peters, Jan},
  title =	{{Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)}},
  pages =	{67--95},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2011},
  volume =	{1},
  number =	{3},
  editor =	{Wyatt, Jeremy L. and Dayan, Peter and Leonardis, Ales and Peters, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.1.3.67},
  URN =		{urn:nbn:de:0030-drops-31943},
  doi =		{10.4230/DagRep.1.3.67},
  annote =	{Keywords: Artificial Intelligence, Robotics, Learning, Exploration, Curiosity}
}
Document
DOI: 10.4230/DagSemProc.04251.1
04251 – Imaging Beyond the Pinhole Camera

Authors: Kostas Daniilidis, Reinhard Klette, and Ales Leonardis

Published in: Dagstuhl Seminar Proceedings, Volume 4251, Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision (2005)

Abstract
From 13.06.04 to 18.06.04, the Dagstuhl Seminar 04251 ``Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Kostas Daniilidis, Reinhard Klette, and Ales Leonardis. 04251 – Imaging Beyond the Pinhole Camera. In Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision. Dagstuhl Seminar Proceedings, Volume 4251, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{daniilidis_et_al:DagSemProc.04251.1,
  author =	{Daniilidis, Kostas and Klette, Reinhard and Leonardis, Ales},
  title =	{{04251 – Imaging Beyond the Pinhole Camera}},
  booktitle =	{Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4251},
  editor =	{Konstantinos Daniilidis and Reinhard Klette and Ales Leonardis},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.04251.1},
  URN =		{urn:nbn:de:0030-drops-3222},
  doi =		{10.4230/DagSemProc.04251.1},
  annote =	{Keywords: Panoramic imaging, omnidirectional cameras, laser range finder, data fusion, sensor geometry, calibration, motion analysis, tracking}
}
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