Abstract: The method operates by estimating the differential movement of the scene picked up by a vertically-oriented camera. Estimation includes periodically and continuously updating a multiresolution representation of the pyramid of images type modeling a given picked-up image of the scene at different, successively-decreasing resolutions. For each new picked-up image, an iterative algorithm of the optical flow type is applied to said representation. The method also provides responding to the data produced by the optical-flow algorithm to obtain at least one texturing parameter representative of the level of microcontrasts in the picked-up scene and obtaining an approximation of the speed, to which parameters a battery of predetermined criteria are subsequently applied. If the battery of criteria is satisfied, then the system switches from the optical-flow algorithm to an algorithm of the corner detector type.

Abstract: The present invention relates to a system (1) of remotely controlled drones (10, 12) fitted with respective cameras (14) enabling a virtual shot from an assailant drone (12) at a target drone (10) to be validated by recognizing the target drone (10) in a video image (17) supplied by the camera (14) of the assailant drone (12) while firing a virtual shot. The recognition means comprise a beacon (15, 16) arranged on the target drone (10) and covered in two first strips (18) of a first color reflecting light at a first wavelength lying in the range 590 nm to 745 nm, situated on either side of at least one second strip (19, 20) of a second color reflecting light at a second wavelength, lying in a range 445 nm to 565 nm. It is thus possible to identify very reliably drones flying in an open space whether outdoors or indoors, in spite of the very great variety of interfering details present in the background images that are likely to be picked up by the camera.