US 12,094,288 B2
System and method for synthetic image training of a machine learning model associated with a casino table game monitoring system
Bryan M. Kelly, Rancho Santa Margarita, CA (US); Terrin Eager, Campbell, CA (US); and Martin S. Lyons, Henderson, NV (US)
Assigned to LNW Gaming, Inc., Las Vegas, NV (US)
Filed by LNW Gaming, Inc., Las Vegas, NV (US)
Filed on Oct. 20, 2023, as Appl. No. 18/491,257.
Application 18/491,257 is a continuation of application No. 17/514,062, filed on Oct. 29, 2021, granted, now 11,798,353.
Application 17/514,062 is a continuation of application No. 16/884,539, filed on May 27, 2020, granted, now 11,205,319.
Claims priority of provisional application 62/864,634, filed on Jun. 21, 2019.
Prior Publication US 2024/0046739 A1, Feb. 8, 2024
Int. Cl. G07F 17/32 (2006.01); G06N 3/08 (2023.01)
CPC G07F 17/322 (2013.01) [G06N 3/08 (2013.01); G07F 17/3223 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, from a casino table game monitoring system, specification data related to a physical object positioned relative to a physical gaming table;
generating, by a processor based on the specification data, synthetic image data based on a virtual scene that depicts a virtual object relative to a virtual gaming table, wherein the virtual object is modeled in the virtual scene using the specification data, and wherein the virtual gaming table is modeled in the virtual scene according to known dimensions of the physical gaming table;
training, by the processor, a machine learning model using the synthetic image data; and
deploying, by the processor via a communications network, the machine learning model to the casino table game monitoring system to monitor the physical object relative to the physical gaming table.