A real-time adaptive segmentation method based on new distance features is proposed for the binary centroid tracker. These novel features are the distances between the predicted center pixel of a target object, measured by a tracking filter, and each pixel in the extraction of a moving target. The proposed method restricts clutters with target-like intensity from entering a tracking window and has low computational complexity for real-time applications compared with other complex feature-based methods. Comparative experiments show that the proposed method is superior to other segmentation methods based on intensity features in target detection and tracking.


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    Title :

    Robust centroid target tracker based on new distance features in cluttered image sequences


    Contributors:
    Cho, Jae-Soo (author) / Kim, Do-Jong (author) / Park, Dong-Jo (author)

    Published in:

    Publication date :

    2000


    Size :

    10 Seiten, 29 Quellen



    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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