Throughout history, advances in transportation systems have had large economic and cultural impact. Mobility has changed the way people live and automobiles continue to evolve by becoming smarter and by leveraging cutting-edge technologies. Over the last three decades, we witnessed a tremendous growth of computer vision knowledge through research in academia and industry. More recently, in the last decade, we are finally seeing exciting applications of computer vision. Computer vision plays a fundamental role in the advanced driver assistance systems (ADAS), a field which is of particular interest to the evolution of transportation systems. For example, forward-facing driver assistance functions (such as road sign detection, lane departure warning, and autonomous emergency braking) are heavily relying on information received from a camera. The systems capture video data at high frame rate and process this information in order to warn the driver that the car is moving faster than the posted speed limit or to tell the driver of an unintentional lane drift. The goal of this chapter is to outline key components of ADAS, show how computer vision fits in the system, and describe its contribution to success of ADAS.


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    Titel :

    Embedded Vision in Advanced Driver Assistance Systems


    Weitere Titelangaben:

    Advs Comp. Vision, Pattern Recognition


    Beteiligte:
    Kisačanin, Branislav (Herausgeber:in) / Gelautz, Margrit (Herausgeber:in) / Nikolić, Zoran (Autor:in)


    Erscheinungsdatum :

    2014-11-27


    Format / Umfang :

    25 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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