Road detection is an important problem with application to driver assistance systems and autonomous, self-guided vehicles. The focus of this paper is on the problem of feature extraction and classification for front-view road detection. Specifically, we propose using Support Vector Machines (SVM) for road detection and effective approach for self-supervised online learning. The proposed road detection algorithm is capable of automatically updating the training data for online training which reduces the possibility of misclassifying road and non-road classes and improves the adaptability of the road detection algorithm. The algorithm presented here can also be seen as a novel framework for self-supervised online learning in the application of classification-based road detection algorithm on intelligent vehicle.


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    Title :

    Road detection using support vector machine based on online learning and evaluation


    Contributors:


    Publication date :

    2010-06-01


    Size :

    933147 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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