A method for identifying, locating, and mapping targets of interest using unmanned aerial vehicle (UAV) camera footage in GPS-denied environments. In one embodiment, the method comprises obtaining UAV visual data, passing the UAV visual data through a convolutional neural network (CNN) in order to detect targets of interest based on visual features disposed in the UAV visual data, wherein the detection by the CNN defines reference points and pixel coordinates for the UAV visual data, applying a geometric transformation to known and defined pixel coordinates to obtain real-world orthogonal positions; and projecting the detected targets of interest onto an orthogonal map based on the obtained real-world orthogonal positions, all without GPS data.


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    Title :

    Mapping Objects Using Unmanned Aerial Vehicle Data in GPS-Denied Environments


    Contributors:

    Publication date :

    2023-02-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL / B64C AEROPLANES , Flugzeuge / G06V