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

A system for identifying unmanned aerial vehicles (UAVs) in a particular air space, comprising:

• a video sensor, wherein the video sensor is proximate to the particular air space and is configured to collect and transmit a video frame from a video feed of the particular air space, the video frame comprising a plurality of pixels;
• and
• a processor operatively coupled to the video sensor;
• wherein the processor is operative to:
• identify 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;
• perform 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, perform 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.