CPC G06Q 10/083 (2013.01) [B64C 39/024 (2013.01); G06F 18/22 (2023.01); G06F 18/24 (2023.01); G06T 7/70 (2017.01); G06V 10/75 (2022.01); G06V 20/10 (2022.01); G06V 20/13 (2022.01); G06V 20/17 (2022.01); G06V 40/172 (2022.01); H04N 7/185 (2013.01); B64U 2101/60 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/30201 (2013.01)] | 12 Claims |
1. A computer implemented method of increasing reliability of face recognition in analysis of images captured by drone mounted imaging sensors, comprising:
recognizing a target person in at least one iteration comprising:
identifying at least one positioning property of the target person based on analysis of at least one image captured by at least one imaging sensor mounted on a drone operated to approach the target person, the at least one imaging sensor locally controlled at the drone,
instructing the drone to adjust its position to an optimal facial image capturing position selected based on the at least one positioning property,
receiving at least one facial image of the target person captured by the at least one imaging sensor while the drone is located at the optimal facial image capturing position,
receiving a face classification associated with a probability score from at least one machine learning model trained to recognize the target person which is applied to the at least one facial image, wherein the at least one machine learning model is executed by at least one remote system connected to the drone via at least one network,
calculating an updated aggregated probability score by accumulating the probability score received in a current iteration of the at least one iteration to an aggregated score calculated before said current iteration such that in each iteration said aggregated probability score is increased by an amount of said probability score received in the current iteration, and
initiating another iteration in case the aggregated probability score does not exceed a certain threshold; and
outputting the face classification for use by at least one face recognition based system,
wherein the operation of the drone is controlled locally at the drone.
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