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    Ground-Image Plane Mapping for Lane marks detection

    Access Status
    Fulltext not available
    Authors
    Lim, King Hann
    Gopalai, Alpha Agape
    Date
    2012
    Type
    Conference Paper
    
    Metadata
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    Citation
    Lim, King Hann and Gopalai, Alpha Agape. 2012. Ground-Image Plane Mapping for Lane marks detection, in Proceedings of the 12th International Conference on Intelligent Systems Design and Applications (ISDA), Nov 27-29 2012, pp. 622-627. Kochi, India: IEEE.
    Source Title
    IEEE
    Source Conference
    Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference
    DOI
    10.1109/ISDA.2012.6416609
    ISSN
    2164-7143
    School
    Sarawak Malaysia
    URI
    http://hdl.handle.net/20.500.11937/16927
    Collection
    • Curtin Research Publications
    Abstract

    Autonomous vehicles are equipped with optical sensors and micro-processing units to perform intelligent visual analysis of its surroundings. Due to the high speed of moving vehicle, the captured information has to be processed in a short duration to avoid possible collision. In this paper, aground-image plane mapping technique is proposed to quickly locate detected object if the object’s position is known in the real world. A three dimensional (3D) world coordinate is mathematically derived to an image plane using pinhole camera model. Several 3D perspective parameters such as vehicle’s steering angle and its velocity, sensor’s height and tilting angle are encompassed in the ground plane measurement. The optical sensor’s intrinsic parameters such as focal length, principal point, pixel’s height and width are also inserted for the mathematical model derivation. The importance of this ground to image plane mapping enables a rapid search of an object in a moving scene to achieve fast object identification during sensor acquisition. Experimental results have been carried on the application of lane marks detection with 93.82% correct mapping, using approximately 20% less processing time.

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