US 12,283,081 B1
Method for training a system for automated detection of the stroboscopic effect
Abraham Greenboim, La Jolla, CA (US); and Osama Mustafa, London (GB)
Assigned to IOT Technologies LLC, La Jolla, CA (US)
Filed by IoT Technologies LLC, La Jolla, CA (US)
Filed on Jul. 10, 2024, as Appl. No. 18/769,249.
Int. Cl. G06V 10/75 (2022.01); G03B 15/03 (2021.01); G06N 3/04 (2023.01); G06T 7/246 (2017.01); G06T 7/80 (2017.01)
CPC G06V 10/751 (2022.01) [G03B 15/03 (2013.01); G06N 3/04 (2013.01); G06T 7/251 (2017.01); G06T 7/80 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/20201 (2013.01)] 9 Claims
OG exemplary drawing
 
1. A stroboscopic device, comprising:
a camera for acquiring video frames;
a light source; and
at least one hardware processor; and
software that is configured to, when executed by the at least one hardware processor,
generating synthetic video frames of an object,
providing real video frames of the object and the synthetic video frames to a discriminator configured to detect the difference between the real video frames from the synthetic video frames,
using feedback from the discriminator to generate further synthetic video frames,
providing real video frames of the object and the further synthetic video frames to the discriminator and repeating until a convergence point is achieved where the discriminator can't reliably tell the real video frames from the synthetically generated video frames,
generating a data set comprising synthetic video frames and real vide frames of the object,
using the data set to train a model,
acquire a sequence of video frames via the camera,
for a first and second frame in the sequence of video frames, compute the dense optical flow field between the two frames, wherein the optical flow field contains a flow vector for each pixel in each of the first and second frames, indicating the motion of that pixel from the first frame to the second frame,
calculate the average magnitude (Average Optical Flow or AOF) of all flow vectors for each pixel in the first and second frames,
compare the AOF to a threshold, and store a result based on the comparison,
repeat the process for all frames in the sequence of video frames,
determine whether a stroboscopic effect has been achieved based on the store results,
control the activation of the light source until the results indicate that the stroboscopic effect has been achieved, and
obtain a further sequence of video frames after the stroboscopic effect is achieved,
identify the object in the further sequence of video frames using the model, and
automatically detect movement or vibration of the identified object using the model.