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.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)



    Erscheinungsdatum :

    2016-01-01


    Anmerkungen:

    Dagstuhl Reports, Volume 5, Issue 11; ISSN 2192-5283



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




    Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)

    Imiya, Atsushi / Leonardis, Ales / Pajdla, Tomas | BASE | 2016

    Freier Zugriff

    Vision for Autonomous Vehicles and Probes (Dagstuhl Seminar 15461)

    Imiya, Atsushi / Leonardis, Ales / Pajdla, Tomas | BASE | 2016

    Freier Zugriff

    The Mobile Revolution - Machine Intelligence for Autonomous Vehicles (Dagstuhl Seminar 15462)

    Burgard, Wolfram / Franke, Uwe / Enzweiler, Markus et al. | BASE | 2016

    Freier Zugriff

    Planning and Robotics (Dagstuhl Seminar 17031)

    Ghallab, Malik / Hawes, Nick / Magazzeni, Daniele et al. | BASE | 2017

    Freier Zugriff

    Planning and Robotics (Dagstuhl Seminar 17031)

    Ghallab, Malik / Hawes, Nick / Magazzeni, Daniele et al. | BASE | 2017

    Freier Zugriff