This paper considers pedestrian detection, specialized for a near infrared imaging system at night. The main objective is the detection of a distant pedestrian, beyond an illuminated area in a low-beam mode, using a monocular on-board camera. In this method, the region of interest (ROI) is first selected by extracting bright regions, and shape information from a whole human body, is later used for verification. Motion information is not used, due to difficulties in cancellation of ego-motion. The ROI selector is implemented by a modified boosted cascade, in combination with dynamic perspective constraints. After filtering out typical non-pedestrian objects, the remaining ROIs are verified using a support vector machine (SVM). The verified ROIs are tracked with a simple alpha-beta tracker, in combination with final validation, based on a classification score from the SVM. The effectiveness of the proposed modules has been confirmed using several typical night time scenarios.


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    Titel :

    Pedestrian Detection for a Near Infrared Imaging System


    Beteiligte:


    Erscheinungsdatum :

    01.10.2008


    Format / Umfang :

    1851897 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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