We propose a novel monocular vision-based framework for both satellite recognition and pose estimation, using homeomorphic manifold analysis. We use a unified conceptual manifold to represent continuous pose variation of all satellites in the visual input space, learn nonlinear function mapping from conceptual manifold representation to visual inputs, and decompose discrete category variation in the mapping coefficient space. Experimental results on a simulated image data set show the effectiveness and robustness of our approach.


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    Title :

    Satellite recognition and pose estimation using homeomorphic manifold analysis


    Contributors:


    Publication date :

    2015-01-01


    Size :

    716687 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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