Dynamic environment interpretation is of special interest for intelligent vehicle systems. It is expected to provide lane information, target depth, and the image positions of targets within given depth ranges. Typical segmentation algorithms cannot solve the problems satisfactorily, especially under the high-speed requirements of a real-time environment. Furthermore, the variation of image positions and sizes of targets creates difficulties for tracking. In this paper, we propose a sensor-fusion method that can make use of coarse target depth information to segment target locations in video images. Coarse depth ranges can be provided by radar systems or by a vision-based algorithm introduced in the paper. The new segmentation method offers more accuracy and robustness while decreasing the computational load.


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    Title :

    Depth-based target segmentation for intelligent vehicles: fusion of radar and binocular stereo


    Contributors:
    Fang, Y. (author) / Masaki, I. (author) / Horn, B. (author)


    Publication date :

    2002-09-01


    Size :

    311931 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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    Fang, Y. / Masaki, I. / Horn, B. | British Library Online Contents | 2002



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