US-20260124516-A1 - AUTOMATIC GOLF CLUB IDENTIFICATION

Abstract

A golf club identification apparatus includes a feature identification module that receives digital images of a golf club from a camera, automatically identifies features of the golf club in the digital images using a machine learning model, and generates feature confidence values for the identified features of the golf club. Each one of the feature confidence values represents a numerical likelihood that the identified feature associated with the feature confidence value corresponds to an actual feature of the golf club. The golf club identification apparatus also includes a confidence threshold module that compares each one of the feature confidence values to a corresponding one of predetermined confidence thresholds and automatically identifies the golf club as a predetermined golf club, of a plurality of predetermined golf clubs, having features associated with the identified features, when a minimum quantity of feature confidence values meets or exceeds the corresponding predetermined confidence thresholds.

Inventors

• Mark Greaney
• Matthew Johnson
• Brian Rahman
• Mikhail Todes
• Todd Beach

Assignees

• TAYLOR MADE GOLF COMPANY, INC.

Dates

Publication Date

20260507

Application Date

20251231

Claims (20)

1. 1 . A golf club identification apparatus, comprising: a feature identification module configured to receive digital images of a golf club from a camera, automatically identify features of the golf club in the digital images using a machine learning model, and generate feature confidence values for the identified features of the golf club, wherein each one of the feature confidence values represents a numerical likelihood that the identified feature associated with the feature confidence value corresponds to an actual feature of the golf club; and a confidence threshold module configured to: compare each one of the feature confidence values to a corresponding one of predetermined confidence thresholds; and automatically identify the golf club as a predetermined golf club, of a plurality of predetermined golf clubs, having features associated with the identified features, when a minimum quantity of feature confidence values meets or exceeds the corresponding predetermined confidence thresholds; wherein the feature identification module and the confidence threshold module each comprises at least one of logic hardware and executable code, the executable code being stored on one or more memory devices.
2. 2 . The golf club identification apparatus according to claim 1 , further comprising a user communication module, wherein: the confidence threshold module is configured to generate a club identification status based on the comparison between each one of the feature confidence values and the corresponding one of predetermined confidence thresholds; the club identification status comprises the feature confidence values for the identified features; and the user communication module is configured to communicate the club identification status to a user.
3. 3 . The golf club identification apparatus according to claim 2 , wherein: the club identification status comprises an annotated one or more of the digital images; and each one of the annotated one or more of the digital images comprises indicia, marking the identified features and identifying the feature confidence values associated with the identified features, superimposed over the golf club in the annotated one or more of the digital images.
4. 4 . The golf club identification apparatus according to claim 3 , wherein: the feature identification module is configured to continuously update the identified features of the golf club and continuously update the associated feature confidence values as the golf club is reoriented relative to the camera; the confidence threshold module is configured to continuously update the club identification status according to updates to the feature confidence values; and the user communication module is configured to continuously update the indicia according to updates to the identified features and the associated feature confidence values.
5. 5 . The golf club identification apparatus according to claim 4 , further comprising a club adjustment module configured to generate an adjustment request when a quantity of feature confidence values meeting or exceeding the corresponding predetermined confidence thresholds is less than the minimum quantity, wherein the adjustment request comprises a reorientation of the golf club predicted to increase the feature confidence value for at least one feature confidence value that is below its predetermined confidence threshold.
6. 6 . The golf club identification apparatus according to claim 2 , wherein: the confidence threshold module is further configured to send a copy of at least one of the digital images and the club identification status to the machine learning model; and the feature identification module is configured to train the machine learning model based on the copy of the at least one of the digital images and the club identification status.
7. 7 . The golf club identification apparatus according to claim 1 , wherein: at least a first digital image of the digital images captures the golf club in a first orientation; at least a second digital image of the digital images captures the golf club in a second orientation; and the feature confidence value, associated with at least one feature identified in the first digital image, is different than the feature confidence value, associated with the same at least one feature identified in the second digital image.
8. 8 . The golf club identification apparatus according to claim 1 , wherein: at least a first digital image of the digital images captures the golf club in a first orientation; at least a second digital image of the digital images captures the golf club in a second orientation; and at least one feature identified in the first digital image is different than at least one feature identified in the second digital image.
9. 9 . The golf club identification apparatus according to claim 1 , wherein a first predetermined confidence threshold, corresponding with a first feature confidence value associated with a first identified feature, is different than a second predetermined confidence threshold, corresponding with a second feature confidence value associated with a second identified feature.
10. 10 . The golf club identification apparatus according to claim 9 , wherein: the first identified feature is a model of a head of the golf club; the second identified feature is one of a position of at least one adjustable weight of the head of the golf club, a setting of an adjustable shaft-head connection of the golf club, a loft of the golf club, or a shaft characteristic of the golf club; and the first predetermined confidence threshold is higher than the second predetermined confidence threshold.
11. 11 . The golf club identification apparatus according to claim 1 , wherein the confidence threshold module is further configured to change at least a second one of the predetermined confidence thresholds when a first one of the feature confidence values meets or exceeds a corresponding first one of the predetermined confidence thresholds.
12. 12 . The golf club identification apparatus according to claim 1 , wherein: the confidence threshold module comprises memory; and the identification of the golf club, as the predetermined golf club, of the plurality of predetermined golf clubs, having features associated with the identified features, is stored in the memory.
13. 13 . A golf club identification system, comprising: a camera configured to capture digital images of a golf club; an electronic display; and a golf club identification apparatus operably coupled with the camera and the electronic display, the golf club identification apparatus comprising: a feature identification module configured to receive the digital images of the golf club from the camera, automatically identify features of the golf club in the digital images using a machine learning model, and generate feature confidence values for the identified features of the golf club, wherein each one of the feature confidence values represents a numerical likelihood that the identified feature associated with the feature confidence value corresponds to an actual feature of the golf club; and a confidence threshold module configured to: compare each one of the feature confidence values to a corresponding one of predetermined confidence thresholds; automatically identify the golf club, as a predetermined golf club, of a plurality of predetermined golf clubs, having features associated with the identified features, when a minimum quantity of feature confidence values meets or exceeds the corresponding predetermined confidence thresholds; generate a club identification status based on the comparison between each one of the feature confidence values to the corresponding one of predetermined confidence thresholds; and communicate the club identification status to the electronic display for displaying the club identification status to a user.
14. 14 . The golf club identification system according to claim 13 , further comprising a launch monitor configured to detect head presentation parameters of the golf club during a golf shot.
15. 15 . The golf club identification system according to claim 14 , wherein the launch monitor comprises the golf club identification apparatus.
16. 16 . The golf club identification system according to claim 15 , wherein: the launch monitor comprises the camera; and the launch monitor detects the head presentation parameters of the golf club during the golf shot based, at least in part, on the digital images captured by the camera.
17. 17 . The golf club identification system according to claim 15 , further comprising a fitting apparatus configured to identify optimal specifications or characteristics of a golf club based, at least in part, on the head presentation parameters of the golf club detected by the launch monitor and the identification of the golf club, as the predetermined golf club, of the plurality of predetermined golf clubs, having features associated with the identified features, wherein the fitting apparatus comprises the golf club identification apparatus.
18. 18 . A method of automatically identifying a golf club, the method comprising: capturing digital images of the golf club; identifying features of the golf club in the digital images via a machine learning model; generating feature confidence values for the identified features of the golf club via the machine learning model, wherein each one of the feature confidence values represents a numerical likelihood that the identified feature associated with the feature confidence value corresponds to an actual feature of the golf club; comparing each one of the feature confidence values to a corresponding one of predetermined confidence thresholds; and identifying the golf club, as a predetermined golf club, of a plurality of predetermined golf clubs, having features associated with the identified features, when a minimum quantity of feature confidence values meets or exceeds the corresponding predetermined confidence thresholds.
19. 19 . The method according to claim 18 , further comprising: generating an annotated one or more of the digital images based, at least partially, on the comparison between each one of the feature confidence values and the corresponding one of predetermined confidence thresholds, wherein each one of the annotated one or more of the digital images comprises indicia, marking the identified features and identifying the feature confidence values associated with the identified features, superimposed over the golf club in the annotated one or more of the digital images; and displaying the annotated one or more of the digital images to a user.
20. 20 . The method according to claim 19 , further comprising: reorienting the golf club and capturing at least one new digital image of the golf club when the golf club is reoriented, when the minimum quantity of feature confidence values does not meet or exceed the corresponding predetermined confidence thresholds; and updating at least one of the identified features of the golf club or the feature confidence values associated with the indicia, based on the at least one new digital image, to create updated indicia and adding the updated indicia to the at least one new digital image to create at least one new annotated digital image in response to reorienting the golf club.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation-in-part of U.S. patent application Ser. No. 19/287,177, filed Jul. 31, 2025, which is a continuation of U.S. patent application Ser. No. 18/401,320, filed Dec. 29, 2023, which claims the benefit of U.S. Provisional Patent Application No. 63/436,326, filed on Dec. 30, 2022, all of which are herein incorporated by reference in their entirety. FIELD The present disclosure relates generally to launch monitors for analyzing golf shot and golf swing characteristics, and more particularly relates to automatically identifying a golf club used with such launch monitors. BACKGROUND Launch monitors are electronic measurement devices used to capture and analyze the motion of a golf ball and/or golf club at impact during a golf shot. Conventional launch monitors can determine various parameters associated with the golf shot. These golf shot parameters can be useful for golfers looking to improve their game. For example, during a practice session, golfers can adjust their swing in response to the golf shot parameters determined by a launch monitor. Additionally, golf shot parameters can help fitters determine which golf clubs (e.g., golf club brand, golf club configuration, golf club characteristics, etc.) best enable a player being fitted to achieve optimal results when practicing or playing golf. More specifically, a golf club fitting can help determine which golf clubs promote better ball striking, shot shaping, distance, and distance control by determining and accounting for the swing dynamics of a golfer being fitted. Generally, golf club fittings can help a golfer being fitted select golf clubs that will optimize the golfer's performance, feel, and consistency when playing or practicing golf. Whether a launch monitor is used for practice, a fitting, or another use, documenting the golf club being swung to the determined golf shot parameters can be helpful. Currently, most launch monitor systems require the user to manually input the golf club being swung in order to associate the golf club with the determined shot parameters. Manually inputting a golf club can result in errors associated with manually misidentifying the golf club or incorrectly entering the golf club. Additionally, manually entering information on a golf club can be cumbersome, especially when multiple clubs are struck during a practice or fitting session, or when multiple characteristics (e.g., adjustable characteristics) of the golf club must be entered. BRIEF SUMMARY Apparatuses, methods, program products, and systems are disclosed for automatic identification of a golf club. Such subject matter of the present application has been developed in response to the present state of the art, and in particular, in response to the shortcomings of conventional techniques for identifying golf clubs. Accordingly, the subject matter of the present application has been developed to provide apparatuses, methods, program products, and systems that overcome at least some of the shortcomings of prior art techniques. Disclosed herein is a golf club identification apparatus. The golf club identification apparatus includes a feature identification module configured to receive digital images of a golf club from a camera, automatically identify features of the golf club in the digital images using a machine learning model, and generate feature confidence values for the identified features of the golf club. Each one of the feature confidence values represents a numerical likelihood that the identified feature associated with the feature confidence value corresponds to an actual feature of the golf club. The golf club identification apparatus also includes a confidence threshold module configured to compare each one of the feature confidence values to a corresponding one of predetermined confidence thresholds and automatically identify the golf club as a predetermined golf club, of a plurality of predetermined golf clubs, having features associated with the identified features, when a minimum quantity of feature confidence values meets or exceeds the corresponding predetermined confidence thresholds. The feature identification module and the confidence threshold module each includes at least one of logic hardware and executable code, the executable code being stored on one or more memory devices. The preceding subject matter of this paragraph characterizes example 1 of the present disclosure. The golf club identification apparatus further includes a user communication module. The confidence threshold module is configured to generate a club identification status based on the comparison between each one of the feature confidence values and the corresponding one of predetermined confidence thresholds. The club identification status includes the feature confidence values for the identified features. The user communication module is configured to communicate the club identification status to a user. T