It is hard to keep vertical photography for Unmanned Aerial Vehicles (UAV) and there is large deflection and rotation in the UAV image, which lead to accuracy of point cloud data produced by UAV image is not high. In this paper an algorithm on UAV point cloud optimization based on Patch-based Least Squares Image Matching is proposed. By optimizing the point cloud data with Patch-based Least Squares Image Matching, and test data with images in campus of Northwestern University. The experimental results show that UAV point cloud optimization based on Patch-based Least Squares Image Matching can conspicuously improve the accuracy of the UAV image matching.


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    Title :

    An Improved Algorithm on Point Cloud Optimization for Unmanned Aerial Vehicles



    Published in:

    Publication date :

    2014-02-06


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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