This paper aims at employing scene classification in real-time to the two-class problem of separating city and rural scenes in images constructed from an infrared sensor that is mounted at the front of a vehicle. The 'Bag of Words' algorithm for image representation has been evaluated and compared to two low-level methods 'Edge Direction Histograms', and 'Invariant Moments'. A method for fast scene classification using the Bag of Words algorithm is proposed using a grey patch based algorithm for image element representation and a modified floating search for visual word selection. It is also shown empirically that floating search for visual word selection outperforms the currently popular k-means clustering for small vocabulary sizes.


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    Title :

    Real-time road scene classification using infrared images


    Contributors:


    Publication date :

    2010


    Size :

    6 Seiten, 17 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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