Reliable understanding of the 3D driving environment is vital for obstacle detection and adaptive cruise control (ACC) applications. Laser or millimeter wave radars have shown good performance in measuring relative speed and distance in a highway driving environment. However the accuracy of these systems decreases in an urban traffic environment as more confusion occurs due to factors such as parked vehicles, guardrails, poles and motorcycles. A stereovision based sensing system provides an effective supplement to radar-based road scene analysis with its much wider field of view and more accurate lateral information. This paper presents an efficient solution using a stereovision based road scene analysis algorithm, which employs the "U-V-disparity" concept. This concept is used to classify a 3D road scene into relative surface planes and characterize the features of road pavement surfaces, roadside structures and obstacles. Real-time implementation of the disparity map calculation and the "U-V-disparity" classification is also presented.


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    Title :

    U-V-disparity: an efficient algorithm for stereovision based scene analysis


    Contributors:
    Hu, Z. (author) / Uchimura, K. (author)


    Publication date :

    2005-01-01


    Size :

    1206364 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    U-V-Disparity: An efficient algorithm for Stereovision Based Scene Analysis

    Hu, Z. / Uchimura, K. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2005



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    3D scene analysis by real-time stereovision

    Garibotto, G. / Cibei, C. | IEEE | 2005


    3D Scene Analysis by Real-Time Stereovision

    Garibotto, G. / Cibei, C. | British Library Conference Proceedings | 2005