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Systems, methods, apparatuses, and devices for identifying, tracking, and managing unmanned aerial vehicles

  • US 10,229,329 B2
  • Filed: 11/08/2016
  • Issued: 03/12/2019
  • Est. Priority Date: 11/08/2016
  • Status: Active Grant
First Claim
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1. A method for identifying unmanned aerial vehicles (UAVs) in a particular air space via the use of one or more video sensors, comprising the steps of:

  • receiving a video frame from a video feed of the particular air space, the video frame comprising a plurality of pixels, wherein the video feed was captured by a particular video sensor proximate to the particular air space;

    identifying at least one region of interest (ROI) in the video frame, the at least one ROI comprising an image of an object that may be a UAV flying within the particular air space, wherein the at least one ROI comprises a subset of the plurality of pixels, and wherein the at least one ROI includes a first ROI inter-frame position and a first ROI velocity;

    performing a scene learning process with respect to the at least one ROI to determine whether the at least one ROI is part of a learned scene represented by the video frame, the scene learning process comprising the steps of;

    comparing the first ROI inter-frame position and the first ROI velocity of the at least one ROI to a plurality of stored ROI inter-frame positions and a plurality of stored ROI velocities of a plurality of stored ROIs to determine if the at least one ROI substantially matches any of the plurality of stored ROIs, wherein the plurality of stored ROIs are associated with substantially reoccurring objects in the particular air space; and

    upon determination that the at least one ROI does not substantially match any of the plurality of stored ROIs, performing an object classification process with respect to the at least one ROI to determine whether the object in the image is a UAV, the object classification process comprising the steps of;

    extracting image data from the image of the at least one ROI;

    comparing the extracted image data to prior image data of objects known to be UAVs to determine a probability that the object in the image is a UAV; and

    upon determination that the probability that the object in the image is a UAV exceeds a predetermined threshold, denoting the object in the image as a UAV.

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