Granted Patent B2

US 12,493,828 · App. 18/236,003 · Granted Dec 9, 2025

Inventor: Yasushi Shigeta (Shiga, JP)

Assignee: ANGEL GROUP CO., LTD.

G06N20/00G06T1/0007G06V20/64G07F1/06G07F17/322G07F17/3239G07F17/3241G07F17/3248G07F17/3251G07F17/3293H04W4/80

Abstract

Claims (71)

1 . A chip recognizing and learning system associated with an amusement place having a gaming table, the chip recognizing and learning system comprising:

a camera configured to capture an image of multiple betting areas of the gaming table from above and at an angle so that the image includes a plurality of stacks of chips bet on the gaming table by a player, the multiple betting areas including a first betting area and a second betting area positioned between the first betting area and the camera; and

at least one processor configured to:

execute an artificial intelligence program to analyze the image of the chips in the plurality of stacks of chips on the gaming table to determine numbers and kinds of the chips;

use, as new teaching data for the artificial intelligence program to learn, one or more images associated with an error in the determination of the numbers or the kinds of chips associated with the one or more images to thereby increase teaching data learned by the artificial intelligence program, the new teaching data further including correct numbers and correct kinds of chips associated with the one or more images, wherein the error is determined based on a chip tray change amount and the numbers or kinds of chips determined based on the image of the chips; and

in response to the determined error:

select the image; and

provide the image to the artificial intelligence program.

2 . The chip recognizing and learning system according to claim 1 , wherein, in a case where it is determined that the numbers and kinds of chips are correct, the at least one processor is further configured to input one or more images used for the determination and the numbers and kinds of chips of the determination as teaching data to the artificial intelligence program to allow the artificial intelligence program to perform learning.

3 . The chip recognizing and learning system according to claim 1 , wherein the at least one processor is configured to:

use the image to determine numbers and kinds of chips in a chip tray included in the gaming table and to perform the determination of the numbers and kinds of chips bet by the player and an identification of positions of the chips bet by the player respectively for each of a plurality of players in a game performed on the gaming table from the image;

determine an actual total amount of the chips in the chip tray when retrieval of all losing chips bet by the players ends;

calculate a necessary total amount of the chips in the chip tray by adding an increased amount of the chip tray in the game calculated from the numbers and kinds of the chips bet by a losing one of the players to the total amount of the chips in the chip tray before settlement of each game on the basis of the identification that is based on the image;

compare the necessary total amount of the chips in the chip tray and the actual total amount of the chips in the chip tray with each other; and

determine that there is the error when there is a difference between the necessary total amount and the actual total amount.

4 . The chip recognizing and learning system according to claim 3 , wherein the at least one processor is configured to determine the actual total amount of the chips in the chip tray based on radio frequency identifications (RFIDs) provided in the chips.

5 . The chip recognizing and learning system according to claim 3 , wherein the at least one processor is configured to use, for the calculation of the necessary total amount, including determining the actual total amount of the chips in the chip tray from the image, an artificial intelligence that is different from the artificial intelligence program that is executed to determine the numbers and kinds of the chips bet by the player.

6 . The chip recognizing and learning system according to claim 3 , wherein the at least one processor is configured to record the image acquired from the camera after giving to the image an index, a time, or a tag specifying a retrieval scene or a payment scene of the chips by which a record of the game can be analyzed.

7 . The chip recognizing and learning system according to claim 1 , wherein the at least one processor is configured to determine the kinds, the numbers, and positions of the bet chips even when some of a plurality of chips put on the gaming table are partially or entirely hidden due to a blind spot of the camera.

8 . The chip recognizing and learning system according to claim 1 , wherein:

the plurality of chip stacks include a first chip stack positioned in the first betting area and a second chip stack positioned in the second betting area; and

the camera is positioned above a top chip of the first chip stack and above a top chip of the second chip stack.

9 . The chip recognizing and learning system according to claim 1 , wherein a first set of betting areas of the multiple betting areas correspond to a first player position at the gaming table, the first set of betting areas arranged on the gaming table in series between the first player position and a dealer position at the gaming table.

10 . The chip recognizing and learning system according to claim 1 , wherein the camera configured to capture the image from above and at the angle, is configured to capture the image so that the image includes a top surface of a top chip of at least one stack of the plurality of stacks.

11 . The chip recognizing and learning system according to claim 1 , wherein the at least one processor is further configured to, for each stack of the plurality of stacks, determine which betting area of the multiple betting areas includes the stack.

12 . The chip recognizing and learning system according to claim 1 , wherein:

the camera is distinct from the gaming table and mounted above the gaming table such that the camera is not mounted on gaming table; and

each first betting area and the second beating area corresponds to the same player.

13 . The chip recognizing and learning system according to claim 1 , wherein:

the camera is configured to capture multiple images of the multiple betting areas of the gaming table from above and at an angle; and

the at least one processor is configured to:

tag the image with a first tag indicating a payment scene associated with settlement of one or more chips associated with one or more winning wagers, wherein the image is captured prior to the settlement of the one or more chips associated with the one or more winning wagers;

determine a first amount associated with a chip tray of the gaming table prior to the settlement of the one or more chips associated with the one or more winning wagers;

after the settlement of the one or more chips associated with the one or more winning wagers, determine a second amount associated with the chip tray after the settlement of the one or more chips associated with the one or more winning wagers;

determine a first chip tray change amount based on the first amount and the second amount;

determine the error based on the first chip tray change amount and the numbers or kinds of chips determined based on the image of the chips; and

in response to the determined error:

select the image based on the first tag; and

provide the image to the artificial intelligence program.

14 . The chip recognizing and learning system according to claim 13 , wherein the chip tray change amount is based on:

a first amount associated with a chip tray of the gaming table prior to collection of one or more chips associated with one or more lost wagers, and

a second amount associated with the chip tray after the collection of the one or more chips associated with the one or more lost wagers.

15 . The chip recognizing and learning system according to claim 1 , wherein:

the camera is configured to capture multiple images of the multiple betting areas of the gaming table from above and at an angle; and

the at least one processor is configured to:

tag the image with a first tag indicating a retrieval scene associated with collection of one or more chips associated with one or more lost wagers, wherein the image is captured prior to the collection of the one or more chips associated with the one or more lost wagers;

determine a first amount associated with a chip tray of the gaming table prior to the collection of the one or more chips associated with the one or more lost wagers;

after the collection of the one or more chips associated with the one or more lost wagers, determine a second amount associated with the chip tray after the collection of the one or more chips associated with the one or more lost wagers;

determine a first chip tray change amount based on the first amount and the second amount;

determine the error based on the first chip tray change amount and the numbers or kinds of chips determined based on the image of the chips; and

in response to the determined error:

select the image based on the first tag; and

provide the image to the artificial intelligence program.

16 . The chip recognizing and learning system according to claim 15 , wherein the at least one processor is configured to:

tag a second image of the multiple images with a second tag indicating a payment scene associated with settlement of one or more chips associated with one or more winning wagers, wherein the second image is captured prior to the settlement of the one or more chips associated with the one or more winning wagers;

after the settlement of the one or more chips associated with the one or more winning wagers, determine a third amount associated with the chip tray after the settlement of the one or more chips associated with the one or more winning wagers;

determine a second chip tray change amount based on the second amount and the third amount;

determine another error based on the second chip tray change amount and based on the numbers or kinds of chips determined based on the image of the chips, the second image, or a combination thereof; and

in response to the determined another error:

select the second image based on the second tag; and

provide the second image to the artificial intelligence program.

17 . The chip recognizing and learning system according to claim 15 , wherein the chip tray is positioned between the camera and a dealer position at the gaming table.

18 . The chip recognizing and learning system according to claim 15 , wherein the at least one processor is configured to:

tag the image with a tag indicating a retrieval scene associated with the collection of one or more chips associated with one or more lost wagers, the image is captured prior to the collection of the one or more chips associated with the one or more lost wagers; and

select the image based on the tag.

19 . A chip recognizing and learning method in an amusement place having a gaming table, comprising:

executing an artificial intelligence program to analyze an image, obtained from a camera, of chips piled up on the gaming table to determine numbers and kinds of chips bet by a player, wherein the camera is configured to capture an image of multiple betting areas of the gaming table from above at an angle so that the image includes a plurality of stacks of the chips piled up on the gaming table, the multiple betting areas including a first betting area and a second betting area positioned between the first betting area and the camera;

using, as new teaching data for the artificial intelligence program to learn, one or more images associated with an error in the determination of the numbers or the kinds of chips associated with the one or more images to thereby increase teaching data learned by the artificial intelligence program, the new teaching data teaching data further including correct numbers and correct kinds of chips associated with the one or more images, wherein the error is determined based on a chip tray change amount and the numbers or kinds of chips determined based on the image of the chips; and

in response to the determined error:

selecting the image; and

providing the image to the artificial intelligence program.

Assignments (2)

Priority Claims (1)

Continuity (2)

References Cited (52)