This contribution introduces a novel approach to cross-calibrate automotive vision and ranging sensors. The resulting sensor alignment allows the incorporation of multiple sensor data into a detection and tracking framework. Exemplarily, we show how a realtime vehicle detection system, intended for emergency breaking or ACC applications, benefits from the low level fusion of multibeam lidar and vision sensor measurements in discrimination performance and computational complexity.


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    Title :

    Sensorfusion Using Spatio-Temporal Aligned Video and Lidar for Improved Vehicle Detection


    Contributors:
    Mahlisch, M. (author) / Schweiger, R. (author) / Ritter, W. (author) / Dietmayer, K. (author)


    Publication date :

    2006-01-01


    Size :

    4838233 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Sensorfusion Using Spatio-Temporal Aligned Video and Lidar for Improved Vehicle Detection

    Mahlisch, M. / Schweiger, R. / Ritter, W. et al. | British Library Conference Proceedings | 2006


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