We present a novel tracking algorithm for an autonomous vehicle equipped with a single camera. Given only monocular visual data, our algorithm utilizes projective geometry to compute concise features of the environment. Using these features, road markings are identified by a multi-class classifier. The classification results are then used with a Rao-Blackwellized particle filter to track the vehicle as it moves back and forth across the road. The resulting position tracker is part of a complete, simulated autonomous driving system. The realistic driving video game Need for Speed: Hot Pursuit was used as a vehicle simulation platform, and the autonomous system is shown to perform competitively against the game's automated opponents.


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    Title :

    Rapid tracking for autonomous driving with monocular video


    Contributors:


    Publication date :

    2013-12-01


    Size :

    311151 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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