This paper presents a robust real time obstacle and pedestrian detection algorithm, which is capable of handling the challenges of stationary as well as moving objects, utilizing a single car mounted monochrome camera. First, the system detects obstacles above the ground plane by obtaining a "virtual stereo system" through the usage of inverse perspective mapping. A fast digital image stabilization algorithm is used to compensate erroneous detections whenever the flat ground plane assumption is an inaccurate model of the road surface. Finally, a low level pedestrian segmentation algorithm is developed to extract bounding boxes of potential pedestrians. Furthermore a novel approach called the Pedestrian Detection Strip is used to improve the calculation time by a factor of six compared to previous attempts. Experiments have been carried out by applying the proposed algorithm on prerecorded sequences as well as within a test vehicle and thus in a closed loop environment. The experimental results indicate a promising detection performance. Obstacles and pedestrians up to 50 meters away from the vehicle have been detected reliably at 64 frames per second on a 3GHz PC.


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    Titel :

    A Real Time Object Detection Approach Applied to Reliable Pedestrian Detection


    Beteiligte:


    Erscheinungsdatum :

    2007-06-01


    Format / Umfang :

    1044138 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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