J. Gayko

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Publications (3)0 Total impact

  • Conference Proceeding: About robust hypotheses generation and object validation in traffic scenes
    M. Schneider, J. Gayko, C. Goerick
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    ABSTRACT: Environmental perception is an important element of advanced driver assistance systems. The perception mainly consists of the steps sensing and data interpretation. Both of these steps are affected by errors due to noise and misinterpretations. Therefore, we present a system design addressing the problem of robust processing under limited resources in a hierarchical system architecture that can use state of the art data-fusion and object-recognition methods.
    Intelligent Vehicles Symposium, 2007 IEEE; 07/2007
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    Article: Scene Analysis And Organization Of Behavior In Driver Assistance Systems
    W. von Seelen, C. Curio, J. Gayko, T. Kalinke
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    ABSTRACT: To reduce the number of traffic accidents and to increase the drivers comfort, the thought of designing driver assistance systems rose in the past years. Fully or partly autonomously guided vehicles, particularly for road traffic, pose high demands on the development of reliable algorithms. Principal problems are caused by having a moving observer in predominantly natural environments. At the Institut fur Neuroinformatik methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. In this paper we present a solution for a driver assistance system. We concentrate on the aspects of video-based scene analysis and organization of behavior.
    08/2001;
  • Conference Proceeding: Scene analysis and organization of behavior in driver assistance systems
    W. von Seelen, C. Curio, J. Gayko, U. Handmann, T. Kalinke
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    ABSTRACT: To reduce the number of traffic accidents and to increase the drivers comfort, the thought of designing driver assistance systems arose in the past years. Fully or partly autonomously guided vehicles, particularly for road traffic, pose high demands on the development of reliable algorithms. Principal problems are caused by having a moving observer in predominantly natural environments. At the Institut fur Neuroinformatik methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a solution for a driver assistance system. We concentrate on the aspects of video-based scene analysis and organization of behavior
    Image Processing, 2000. Proceedings. 2000 International Conference on; 02/2000
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