This paper presents a new visual tracking method that can achieve accurate estimation of affine transformation and precise spatial-color representation. The estimation of transformation provides more information than translation for better motion understanding and also helps maintain the precise representation; the precise representation enables tracking objects in highly-cluttered environment. The basis of the method is a kernel-based similarity measure called affine matching that describes the relationship between image regions with respect to affine transformation parameters. Based on the similarity measure, a mathematical solution is derived for estimating the transformation parameters for moving objects in videos. Various experiments have yielded positive results.


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    Title :

    Affine object tracking with kernel-based spatial-color representation


    Contributors:


    Publication date :

    2005-01-01


    Size :

    1686190 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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