US 12,469,291 B2
Neural-network-based prediction of the stopping moment for text recognition in a video stream
Kseniya Stanislavovna Kryuchkova, Moscow (RU); Aleksandr Vladimirovich Sheshkus, Belgorodskaya oblast (RU); and Konstantin Bulatovich Bulatov, Moscow (RU)
Assigned to Smart Engines Service, LLC, Moscow (RU)
Filed by Smart Engines Service, LLC, Moscow (RU)
Filed on Jan. 26, 2023, as Appl. No. 18/101,894.
Claims priority of application No. RU2022115947 (RU), filed on Jun. 14, 2022.
Prior Publication US 2023/0419667 A1, Dec. 28, 2023
Int. Cl. G06V 20/40 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 10/94 (2022.01); G06V 20/62 (2022.01)
CPC G06V 20/49 (2022.01) [G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 10/94 (2022.01); G06V 20/63 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising using at least one hardware processor to, for each of one or more fields in a plurality of frames from a video stream for which a recognition process is being performed:
perform text recognition on the field to produce a current text-recognition result;
combine the current text-recognition result with a preceding text-recognition result for the field from one or more prior frames;
calculate an error between the combined text-recognition result and the preceding text-recognition result;
add the calculated error to an accumulated feature set; and,
when the accumulated feature set has reached a predefined size, wherein the predefined size is greater than one,
apply a predictive model to the accumulated feature set of the predefined size to classify the accumulated feature set into one of a plurality of classes, wherein the plurality of classes comprises a first class that indicates continuation of the recognition process, and a second class that indicates stopping of the recognition process,
when the one class is the first class, continue the recognition process for the field, and,
when the one class is the second class, stop the recognition process for the field.