JPWO2021248050A5 - - Google Patents

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 63/034,667, filed June 4, 2020, entitled "Autonomous Activity Monitoring and Lottery System and Method," and the contents thereof Incorporated herein by reference in its entirety.

FIELD OF THE INVENTION This disclosure relates to digital media production. More particularly, the present disclosure relates to autonomous golf competition systems and methods.

BACKGROUND OF THE INVENTION Various forms of video recording and production exist today. For example, producing a movie video is a highly labor-intensive task, with directors shooting multiple shots from multiple viewing angles, and post-production taking months to produce the final video. Such video recording is very expensive and requires a lot of human resources. In sports, video streaming technology is used to capture real-life events, and does so by having a cinematographer move the camera in the direction of the play. This makes it possible to perform real-time recording in which camera cuts are made for different aspects of the play. Although the length of time has been greatly compressed, there is still a need to manually record and follow the field of play to capture the desired footage. In another aspect, for live sports video, the video is streamed in near real time using a dedicated high speed network configured to broadcast televised sporting events. However, each of these systems includes automated means for processing and communicating video footage without requiring a director or videographer to capture the relevant footage, and for producing and viewing video in an efficient manner. There is a lack of an automated way to communicate with people.

Overview One aspect of the present disclosure is to provide a system for automatically recording sporting events.

According to one aspect, a system for operating a performance-based competition includes a remote media system (RMS) located at a golf course having a golf hole, the system comprising: a remote media system (RMS) located at a golf course having a golf hole; an RMS including a first AI-enabled camera configured to record video of the golfer; and a competition-based network media processor and service (CNMS) communicatively coupled to the RMS and located remotely to the RMS. ), the network communication interface configured to initiate a recording event request including an input for activating video recording, the recording event request being communicated to the RMS; and a network media processor configured to receive the enabled camera activation request and confirm the recording request, and a mobile configured to send a session request to the CNMS to activate video recording. a digital media-enabled destination including an application, the request comprising a digital media-enabled destination including a unique identifier for the digital media-enabled destination, a golf hole location, and a user profile identifier; A system configured to receive input from a user indicating consent to participate, the CNMS further configured to detect successful attempts associated with a competition.

In another aspect, a method for automatically managing a skill-based competition is provided, the method comprising: detecting the presence of a golfer at a golf hole on a golf course; , receiving an activation request at a competition-based network media processor and service (CNMS), the activation request including a user profile identifier of the golfer; and receiving the user profile identifier and the location of the golf hole. to verify golfers, send activation requests and activate recordings of golfers and competitions using AI-enabled cameras at golf holes, and to identify winning events in competitions. and detecting.

In another aspect, an AI-enabled golf course is provided, the AI-enabled golf course includes: a first golf hole having a green, a tee box, a hole with a pin disposed in the hole; a remote media system (RMS) located at the course, including a first AI-enabled camera configured to record video of a golfer detected at a golf hole, and communicatively coupled to the RMS; a competition-based network media processor and service (CNMS) located remotely to the computer, the CNMS configured to initiate a recording event request that includes an input for activating video recording; an RMS comprising: a network communication interface, wherein the recording event request is communicated to the RMS; and a network media processor configured to receive the AI-enabled camera activation request and confirm the recording request. and a digital media-enabled destination including a mobile application configured to send a session request to a CNMS to activate video recording, the request including a unique identifier of the digital media-enabled destination and a location of the golf hole. and a user profile identifier, the CNMS is configured to receive input from the user indicating consent to participate in the competition, and the CNMS is configured to receive input from the user indicating consent to participate in the competition. Further configured to detect a successful attempt.

BRIEF DESCRIPTION OF THE DRAWINGS Other aspects of the present disclosure will be better understood and readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings. .

1 illustrates an autonomous media processing system according to an aspect of the present disclosure. FIG. 1 is a block diagram illustrating a remote media capture system according to one aspect of the present disclosure. FIG. FIG. 2 is a block diagram illustrating an AI-enabled camera for use with a remote media capture system according to an aspect of the present disclosure. FIG. 2 is a block diagram illustrating network media processing and management services in accordance with one aspect of the present disclosure. FIG. 2 is a block diagram illustrating network media processing and management services in accordance with one aspect of the present disclosure. FIG. 2 is a block diagram illustrating network media processing and management services in accordance with one aspect of the present disclosure. 2 is a graphical user interface for a media-enabled mobile application according to an aspect of the present disclosure. 2 is a graphical user interface for a media-enabled mobile application according to an aspect of the present disclosure. 2 is a graphical user interface for a media-enabled mobile application according to an aspect of the present disclosure. 2 is a graphical user interface for a media-enabled mobile application according to an aspect of the present disclosure. 1 is a diagram of an AI-enabled golf course according to one aspect of the present disclosure. FIG. 1 is a block diagram illustrating an AI-enabled golf hole according to one aspect of the present disclosure. FIG. FIG. 3 illustrates a method for activating recording using an autonomous media processing system according to an aspect of the present disclosure. FIG. 3 illustrates a method for activating recording using an autonomous media processing system according to an aspect of the present disclosure. FIG. 3 illustrates a method for autonomous media post-processing in accordance with an aspect of the present disclosure. FIG. 3 illustrates a method for autonomous media post-processing in accordance with an aspect of the present disclosure. FIG. 3 illustrates a method of using a media-enabled mobile application according to an aspect of the present disclosure. FIG. 3 illustrates a method of using a media-enabled mobile application according to an aspect of the present disclosure. FIG. 3 illustrates a method of using a media-enabled mobile application according to an aspect of the present disclosure. FIG. 3 illustrates a method of using a media-enabled mobile application according to an aspect of the present disclosure. FIG. 3 illustrates a method of using a media-enabled mobile application according to an aspect of the present disclosure. FIG. 2 is a block diagram illustrating a multi-view AI compatible golf hole according to one aspect of the present disclosure. FIG. 2 illustrates a graphical user interface of a golf competition mobile application in accordance with one aspect of the present disclosure. FIG. 2 is a block diagram of a method for providing autonomous golf competitions within a mobile application according to one aspect of the present disclosure. FIG. 2 is a block diagram of a method for providing autonomous golf competitions within a mobile application according to one aspect of the present disclosure. FIG. 2 is a block diagram of a method for providing autonomous golf competitions within a mobile application according to one aspect of the present disclosure. FIG. 2 is a block diagram of a method for providing autonomous golf competitions within a mobile application according to one aspect of the present disclosure. 1 is a block diagram illustrating a network media processing and management service incorporating an autonomous golf competition service in accordance with one aspect of the present disclosure. FIG. FIG. 2 is a block diagram illustrating a network media processing and management service incorporating an autonomous golf competition service in accordance with one aspect of the present disclosure. 1 is a block diagram illustrating a network media processing and management service incorporating an autonomous golf competition service in accordance with one aspect of the present disclosure. FIG. 1 is a block diagram of an autonomous golf competition method according to one aspect of the present disclosure. FIG. 1 is a block diagram of an autonomous golf competition method according to one aspect of the present disclosure. FIG. 1 is a block diagram of an autonomous golf competition method according to one aspect of the present disclosure. FIG.

DETAILED DESCRIPTION OF THE DISCLOSURE The following description, taken in conjunction with the drawings, is provided to assist in understanding the teachings disclosed herein. The following description focuses on particular implementations and embodiments of the teachings. This focus is provided to help explain the teachings and is not to be construed as a limitation on the scope or applicability of the teachings. However, other teachings can certainly be utilized in this application. The teachings may also be utilized in several different types of architectures, such as distributed computing architectures, client/server architectures, or middleware server architectures and associated components, in other applications.

Devices or programs that are in communication with each other need not be in continuous communication with each other, unless specified otherwise. Additionally, devices or programs that communicate with each other may communicate directly or indirectly through one or more intermediaries.

The embodiments described below partially describe distributed computing solutions that manage all or a portion of communication interactions between network elements. In this regard, communication interactions may include sending information, requesting information, receiving information, receiving requests for information, or any combination thereof. Thus, communication interactions may be unidirectional, bidirectional, multidirectional, or any combination thereof. In some situations, communication interactions may be relatively complex and include two or more network elements. For example, a communication interaction may be a "conversation" or a series of related communications between a client and a server, with each network element sending and receiving information to and from the other. Communication interactions between network elements are not necessarily limited to only one particular form. A network element may be a node, hardware, software, firmware, middleware, another component of a computing system, or any combination thereof.

In the description that follows, a flowcharted technique or algorithm may be described as a series of sequential actions. Unless expressly stated to the contrary, the order of the operations and the parties performing the operations may be changed at will without departing from the scope of the teachings. Actions can be added, removed, or modified in several ways. Similarly, actions may be reordered or looped. Further, although processes, methods, algorithms, etc. may be described in a sequential order, such processes, methods, algorithms, or any combination thereof may be operable to be performed in an alternative order. obtain. Furthermore, some actions within a process, method, or algorithm may be performed simultaneously (e.g., actions performed in parallel), at least during some point in time, in whole, in part, or It is also possible to perform any combination of the following. As used herein, the terms "comprises", "comprising", "includes", "including", "has", "having" ”, or any other variations thereof, are intended to include non-exclusive inclusion. For example, a process, method, article, or device that includes a list of features is not necessarily limited to only those features and includes features not explicitly listed or unique to such process, method, article, or device. Other features may be included. Further, unless explicitly stated to the contrary, "or" refers to an inclusive disjunction and not to an exclusive disjunction. For example, condition A or B is one of the following: A is true (or exists), B is false (or does not exist), A is false (or does not exist), and B is true. (or exists), and both A and B are true (or exist).

Also, the use of "a" or "an" is used to describe elements and components described herein. This is done merely for convenience and to give a general sense of the scope of the invention. This description should be read to include one or at least one, and the singular also includes the plural and vice versa, unless it is obvious that it is meant otherwise. except. For example, when a single device is described herein, two or more devices may be used in place of a single device. Similarly, if more than one device is described herein, a single device may be used in place of that one device.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety, unless a specific section is cited. In case of conflict, the present specification, including definitions, will control. Furthermore, the materials, methods, and examples are illustrative only and not intended to be limiting.

Unless otherwise described herein, many details regarding specific materials, processing operations, and circuits are conventional and may be found in textbooks and other sources within the computing, electronics, and software arts. can.

For purposes of this disclosure, media processing systems and services include computing, classifying, processing, transmitting, and receiving information, intelligence, or data in any form for business, scientific, control, entertainment, or other purposes. , any means or set of means operable to retrieve, originate, switch, store, display, present, detect, record, play, handle, or utilize. For example, a media processing system may include a mobile device, a digital camera, a personal computer, a PDA, a consumer electronic device, a smartphone, a set-top box, a digital media subscriber module, one or more cloud or network services and storage, a cable modem, It may be a fiber optic-enabled communication device, media gateway, network server or storage device, switch router, wireless router, or other network communication device, or any other suitable device, size, shape, performance, functionality. , and prices may vary.

A processor disclosed herein may include one or more processing resources or controllers such as memory, central processing unit (CPU), hardware, local memory, or software control logic. Additional components include one or more memory devices including internal and external storage devices, one or more wireless and wired communication interfaces, displays, keypads, touch screens, touch pads, voice recognition, facial or AI-enabled image recognition. , one or more cameras or camera inputs, audio inputs, power sources, or various combinations. A processor can be embedded within the media processing system, provided separately from the media processing system, or in combination. A processor may also be implemented as digital logic stored solely within services such as APIs, network services such as Amazon Cloud services, or a combination thereof. Other forms of processors that may be deployed within the scope of this disclosure are described herein by way of example.

Various software aspects that can be used within the media processing system include a Linux operating system with Python programmed applications, OpenCV image processing libraries, AWS Greengrass ML model development and execution, OpenCV image processing libraries and Python May include video editing software using programming. AWS for video storage
Various cloud services can be used for video storage, transmission, and access, including S3 and AWS Glacier, and AWS Cloud for content delivery and distribution. Cloud services for processing and editing videos may include Python and OpenCV running on AWS EC2 servers. Cloud services for converting videos from one format to another may include AWS Elemental MediaConvert.

Embodiments of the autonomous media processing systems and processors disclosed herein also employ artificial intelligence (AI) or AI logic, commonly described as AI logic, machine learning, and neural networks. AI or AI logic includes several categories of techniques that allow systems and processors to mimic human abilities. AI techniques or logic include machine learning, spoken language processing, expert systems, and robotics. Machine learning is a subset of AI that allows computers to improve tasks through experience. Machine learning includes traditional statistics-based techniques such as regression analysis, as well as newer techniques such as deep learning. Deep learning uses large amounts of historical data to train multilevel neural networks to draw conclusions about new data. Throughout this specification, the description also uses AI logic that deploys deep learning in the form of neural networks to identify classes of objects, object positions and segments within video images. Deep learning is also used to identify distinct activities or subactivities within video images and video segments that include multiple video frames. In some forms, statistics-based machine learning is used to characterize motion or orientation of objects within video images and segments.

AI or AI logic disclosed herein may also include, but is not limited to, cloud services for generating neural networks to create AI logic and AI gesture recognition logic, including Keras/TensorFlow development. AWS SageMaker for building, training, tuning, and evaluating machine learning models, including frameworks, and Sagemaker NEO for preparing models for deployment to one or more AI logic locations.

Various embodiments of autonomous media processing systems and methods will now be described more fully. Each of these exemplary embodiments is provided so that this disclosure will be thorough, and will fully convey the scope of the concepts, features, and advantages of the invention to those skilled in the art. To this end, numerous specific details are set forth, such as examples of specific components and methods associated with the system, in order to provide a thorough understanding of each of the aspects related to this disclosure. However, as will be apparent to those skilled in the art, it is not necessary to use all the specific details set forth herein, and the example embodiments may be embodied in many different forms, such as: It should not be interpreted or construed to limit the scope of this disclosure.

Various embodiments disclose the capture, processing, distribution, and use of video, audio, and content used to create media or digital media. Embodiments disclosed herein include autonomous and AI-enabled systems, devices, methods, applications, software, hardware, and locations for capturing, processing, distributing, and consuming digital media. As disclosed herein, digital media can refer to any media that is encoded in a machine-readable format. Digital media can be created, viewed, distributed, modified, listened to, and stored on digital electronic devices. Digital media refers to any information that can include text, audio, video, and graphics that is broadcast through a screen or speakers and transmitted over the Internet or digital communication media. Examples of digital media include software, digital images, digital video, video games, web pages and websites, social media, digital data and databases, digital audio such as MP3, electronic documents, and electronic books. As disclosed herein, media and digital media are used throughout this specification and unless explicitly specified as different, they should be referred to as above.

Referring now to FIG. 1, an autonomous media processing system is disclosed. An autonomous media processing system (AMPS), shown generally at 100, includes a remote media system (RMS) 102, a network media processing and management service (NMS) 104, and a media-enabled destination 106. AMPS 100 further includes AI logic 108, which may include remote AI logic 110 that is accessible to RMS 102. AI logic 108 also includes network AI logic 112 that is accessible to NMS 104 . Some or all of the AI logic 108 may be stored in either or both remote AI logic 110 or network AI logic 112.

According to one aspect, the AI logic 108 includes learned logic generated based on previous recordings of image data that can be used to generate AI logic specific to the field of use being deployed. Can be done. By way of example, AMPS 100 can be used with one or more golf courses to create AI logic and generate AI golf logic as AI logic 108 . Accordingly, AI golf logic may include AI logic having elements of AI logic designed to be used in golf. For example, AI golf logic may include objects that can be used to identify a particular player, clothing, equipment, other items associated with the golf course or its environment. For example, AI golf logic can include: a person, a person or golfer holding a golf club, a shirt, the color of the shirt, a hat, the color of the hat, a golf glove, golf shoes, a golf cart, a person in a golf cart, a golf ball, a golf tee. , golf clubs, irons, drivers, utility clubs, putters, wedges, 1-iron, 2-iron, 3-iron, 4-iron, 5-iron, 6-iron, 7-iron, 8-iron, 9-iron , wedges, pitching wedges, gap wedges, sand wedges, golf ball logos, men, women, children, youth, left-handed golfers, right-handed golfers, shirts, logos, caddies, marshals, Callaway, Taylor-Made, Titleist, Mizuno, etc. equipment brands. Various other objects may be identified within the AI logic 108 as needed or desired.

According to another aspect, AI logic 108 may include golf courses, golf holes, and objects used in the surrounding environment. For example, the AI logic 108 can determine the tee box, tee box color, golf cart, tree, fairway, cart path, green, hole, pin, sand bunker, water hazard, grass hazard, out of bounds, rough, first of the green, etc. cut, second cut of the green, birds, insects, animals, distance from the tee to the pin, distance from the tee to the front of the green, distance from the tee to the middle of the green, distance from the tee to the back of the green , Red Stakes, White Stakes, Blue Stakes, Yellow Stakes, Red Line, White Line, Yellow Line, Elevation Change, Clouds, Rain, Snow, Fog, Haze, Mud, Wind, Green Topology, Hole Cut, Maintenance Personnel, lawn mowers, leaf blowers, rakes, sand rakes, or various other objects that can be identified and added and used by the AI logic 108 for use in processing video or images captured on the golf course. can include.

In addition to object identification, AI logic 108 may also be configured to identify gestures generated within the video. Gesture logic, or gesture recognition, can be identified using AI logic 108 by processing a series of image frames and comparing the image frames to AI logic 108 with gesture logic. Although gesture logic is described as AI logic 108, it can be appreciated that gesture logic can be provided alone or in combination with other objects within AI logic 108. Examples of gesture logic are not limited to golf gestures, but can include various image frames defined as gestures. For example, gesture logic for golf may include a pre-shot gesture routine, a shot or swing gesture, and a post-shot gesture.

According to one aspect, the swing gesture includes identifying a golfer on a tee box, a practice swing, a golfer talking to another golfer, a golfer looking at the distance to the pin, a golfer setting a ball on a tee, Golfer walking behind the ball, golfer lining up for a swing, golfer addressing the ball, pulling up a golf cart, golfer walking, golfer carrying a bag, golfer on cart pushing bag , a golfer on a cart pulling a bag, a golfer walking with a caddy, a golfer reviewing a scorecard, or a variety of other pre-shot gestures that can be learned and added to the AI logic 108.

Additional gesture logic that may be included within the AI logic 108 may include gestures related to the golfer's shot, including, but not limited to, backswing, downswing, contact with the ball, and missed ball. to hit the ball, to top the ball, to duff the ball, to top the ball, to shank the ball, to hook the ball, to slice the ball, to pop the ball, Pulling the ball, pushing the ball, hitting the ball straight, hitting the ball low, hitting the ball high, the ball landing on the green, the ball landing on the sand, the ball landing on the water, Ball landing in the rough, ball landing out of bounds, ball hitting a tree, ball hitting a pin, ball hitting a cart path, ball hitting a golfer/person, putting, putting too hard, putting too weak, putting to the left, putting to the right putting, hitting the ball over the green, hitting the ball short of the green, hitting the ball left of the green, hitting the ball short of the green, hitting the ball right of the green, or AI. Includes various other shot gestures that may be learned and added to logic 108.

According to further aspects, the AI logic 108 may also include golf logic with identifiable post-shot gestures. Post-shot gestures include, but are not limited to, hitting the club, throwing the club, the golfer high-fiving, the golfer clenching his fist, the golfer raising his arms in the air, the golfer pumping his fist, the golfer running, golfer jumping, golfer looking down, golfer shouting, golfer teeing up, golfer walking straight ahead, golfer clapping, golfer laughing, or various others that can be learned and added to the AI logic 108. may include a post-shot gesture.

According to further aspects, AI logic 108 with object and gesture recognition can be used to identify kinematic aspects of a golfer's swing. AI logic 108 may be used to identify the type of golf swing a golfer may have made while hitting a golf ball using object recognition logic and gesture recognition logic. For example, objects in AI logic 108 may be used to identify a golf club, arms, legs, hips, golf club, tee box, or other objects associated with a golfer. Gesture logic in AI Logic 108 is used with object logic to determine club path, arms, legs, hips, wrists, golf club, golf ball movement, ball launch angle, ball velocity, ball smash factor, ball Side spin, the apex of the ball being hit, and various other gestural activities of the golfer, club, and ball can be identified. The resulting analysis can then be used as a teaching opportunity to assist a golfer or teaching professional in analyzing the golfer's swing. Although not shown, each object, gesture, or combination identified using AI logic 108 can identify the object, gesture, kinematics, or combination thereof for subsequent media and video processing. As may be provided, metadata or labels may be provided with the video captured by AMPS 100.

Although it has been described that the AI logic 108 having golf logic is used, golf activities, football activities, soccer activities, baseball activities, basketball activities, ski activities, snowboard activities, bicycle activities, fishing activities, boat activities, general sports activities, or understand that various other activities, logic, and gestures may be used by the AMPS 100, including but not limited to various other types of non-sporting activities that are predetermined to occur at a geographic location. Can be done. AI logic 108 may include objects that are important or related to the activity. For example, AI logic 108 can be used to detect football activity, can be used on a football field to detect objects for football player numbers and names, and videos can be used to detect football player numbers and names. Player numbers can be used and processed to assist in unique video identification. Depending on the activity or environment in which AMPS 100 is being used, various other objects for football or other activities may be provided by AI logic 108.

As mentioned above, AMPS 100 may be configured to use AI capable of machine learning and object/gesture identification based on image datasets. An image dataset is a previously identified set of objects, activities, gestures, etc. that the AI can automatically identify from an image or video. The image dataset may include a list of known objects and/or movements and may be used to identify a threshold number of known objects based on images captured by the AMPS 100, and the image dataset may be defined. Further instances of known objects within the data set can be automatically identified by the AMPS 100 without the need for manual/human identification afterward. It will be appreciated that the AMPS 100 and AI logic described throughout this specification are configured to autonomously and automatically detect aspects of the video. AMPS 100 can also support other forms of input, such as audio input, sensor input, data input, voice input, radar input, or various other forms of support AI logic that can be used to detect input to AMPS 100. May include AI logic. RMS 102 can include various forms of input that can be used to initialize, record, process, and distribute captured video using AI logic 108. For example, RMS 102 may be used to identify a particular sporting event, such as golf, and to initiate recording of a video of a particular golfer. RMS 102 may access AI logic 108, such as remote AI logic 110 created specifically for golf. Once a golfer is identified using AI logic 108, video can be recorded for that particular golfer and processed using RMS 102 and NMS 104. Once the golfer has finished playing a hole, AMPS 100 may begin final generation of the golfer's video using NMS 104 and communicate the digital media to a media-enabled destination 106, such as the golfer's mobile device or smartphone. According to one aspect, the final generated video shows the golfer, their name, the name of the course they are playing, the hole number, the course logo, and the path of where the ball traveled during the video. Golfer statistics for the shot may be included, including overlaying graphical ball traces. In this way, no human intervention is required to record, generate, and distribute video footage, thereby increasing the efficiency of video generation, while providing graphics- and format-enhanced final generated video related to the creation of Time and cost can be reduced.

According to further aspects, media-enabled destinations 106 may include various types of devices that can display digital media received from or being streamed from NMS 104. For example, the media-enabled destination 106 can be configured on a mobile device (not explicitly shown in the figure), such as a smartphone or other mobile device, that can receive a link to a video stored by the NMS 104 and select the link to play the video. (not shown). Media-enabled destination 106 can also download and store digital media at the destination. For example, media-enabled destinations 106 may include web-based services such as social media service providers such as Instagram, Facebook, Snapchat, Twitter, etc. that can play digital media generated by NMS 104. In one form, a link to the video can be created by the NMS 104 and communicated to the social media service. In other forms, video requests from services such as YouTube, Disney+, ESPN+, Fox Sports, and other streaming services may enable video storage. In some forms, the video may need to be formatted before being delivered to media-enabled destination 106. According to further aspects, NMS 104 may be capable of providing digital media channels that may be accessed by media-enabled destinations 106. For example, NMS 104 may create a particular sports channel, such as a golf channel, ski channel, fishing channel, or other sports channel that has a particular type of digital media created using AMPS 100. Accordingly, NMS 104 may provide various forms of digital media and output digital media to one or more media-enabled destinations 106, depending on the end use of the digital media created by AMPS 100.

Referring now to FIG. 2, a block diagram illustrating a remote media capture system (RMS) is disclosed. A remote media capture system (RMS), shown generally at 200, includes a processor and memory 202 , which can include an NVIDIA Jetson AGX Xavier for processing and controlling a local video camera. The specifications of Jetson AGX Xavier are available at https://developer.as of the filing date of this application. nvidia. com/embedded/jetson-agx-xavier-developer-kit. Multiple computers may be used. In the case of a golf hole, one computer may be placed at each end of the hole. It will be appreciated that alternative computer systems may be used for particular processing needs and performance may vary over time. Processor 202 may include a dual-core NVIDIA Denver 2 64-bit CPU and a quad-core ARM® Cortex®-A57 MPCore, and memory 202 may include 8GB 128-bit LPDDR4 memory, 32GB eMMC It can also include storage. Other processors and memory may be used as needed, and performance may vary over time. System 200 may also include an AI-enabled graphics processor 216, which may include a 256-core NVIDIA Pascal™ GPU architecture with 256 NVIDIA CUDA cores. Other graphics processors may be used as performance and needs change over time. The operating software of RMS 200 may include the Linux operating system, Python as an application programming language, and the OpenCV image processing library. RMS 200 further includes AI logic 218, which may include machine learning deployment and execution software, such as Amazon Web Services Greengrass ML software or other endpoint AI processing software or modules.

According to further aspects, RMS 200 can include one or more remote cameras 204 in communication with processor 202. As discussed below, remote camera 204 may be connected to the processor and memory using a network interface (not explicitly shown). RMS 200 may further include a power supply module 220 configured to power processor 202 and other components of RMS 200. Power module 220 may be in the form of a battery or composite solar cell, and may be a wired connection to an AC or DC power source. Power module 220 may be provided to convert the power source to one or more power levels as needed or desired by RMS 200.

According to another aspect, remote camera 204 can be connected using a Power Over Ethernet (PoE) interface to provide power and communication to remote camera 204. Other forms of connection may also be used including, but not limited to, optical fiber, coaxial cable, twisted pair, single strand, custom cable, or various combinations thereof. RMS 200 may further include a communications module 214 connected to processor 202 and, optionally, a modem, such as a cellular modem, wired modem, or other form of modem. In one aspect, a cellular modem, such as a Peplink MAX BR1 Mini, can be attached to each computer (at each end of the golf hole). The specifications of Peplink MAX BR1 Mini are available at https://download. peplink. com/resources/pepwave_max_br1_mini_lte_datasheet. It is written in pdf. For example, communication module 214 can be configured with a wired or wireless network to which the Internet or cloud-based services can be connected. Communication module 214 can be used to determine a location or address for communicating via a modem and can further receive data or instructions for processor 202. The communication module 214 having a cellular or hardwired modem can be configured to communicate or transmit data over a network such as the Internet or a cloud, and the cellular modem supports 3G, 4G, 5G, or other communication standards. can be used to communicate. In other forms, the communication module 214 can be a wired modem that can communicate using a broadband connection such as Ethernet, or via a fiber optic connection, or various combinations thereof. can.

According to one aspect, the RMS 200 includes one or more remote cameras as AI-enabled remote cameras that can process image data using AI logic to detect specific objects within the video being recorded. A camera 204 may further be included. RMS 200 may also include sensor inputs 206 and audio inputs 208 that may be controlled or accessed by processor 202 to add additional media to video being recorded using remote camera 204.

RMS 200 also includes a digital media storage module 210 for storing raw or compressed video, data files, operational files, control log metadata, sensor data, radar data, session data, and other forms of data or information. and a data storage module 222 for storing files. RMS 200 further includes a media processing engine 212 configured to process media received by RMS 200 as described below. RMS 200 further includes an AI-enabled graphics processing engine 216 that is accessible to processor 202 and AI logic 218 that can be used to process video, audio, and sensor input to RMS 200.

In use, RMS 200 can be used to capture and process media content that can be processed and sent to a destination using communication module 214. Some or all of the processing may be performed locally using RMS 200. However, in other configurations, processing may be divided among various parts of RMS 200, such as remote camera 204, media processing engine 212, processor 202, and AI-enabled graphics processing engine 216 and AI logic 218. Processing may also include, but is not limited to, video processing, sensor data processing, audio processing, data or metadata processing, graphics processing, AI processing, compression processing, or use to output digital media using communication module 214. Various combinations of processing may be included, including, but not limited to, various other forms of processing that may be performed.

According to one aspect, RMS 200 can be used to process and compress media so that communications module 214 can communicate the media to a destination in an efficient manner. For example, some cellular networks have limited capacity for uploading media, including large video formats or files. Accordingly, RMS 200 and communication module 214 can determine communication upload speeds and bandwidth capabilities and compress media files to ensure that bandwidth demands are maintained. Various video formats and media file sizes, such as 8K and 4K videos, may be too large to communicate over cellular networks. Therefore, larger video formats and resolutions can be converted to smaller formats if needed. For example, 4K video is H. 264 format and can be uploaded as HD, UHD, or other digital media file formats.

According to further aspects, RMS 200 can be used in a golf environment to detect golfers and record and communicate the golfer's activities in the form of processed video or digital media. During use of RMS 200 in a golf environment, processor 202 automatically captures golfer video data using remote camera 204 and automatically processes the video using AI-enabled processing engine 216 to provide autonomous The video may be configured to create a digitally processed video. For example, an AI-enabled processing engine 216 may be used to detect a golfer using image data from a video and neural network within AI logic 218 created to detect a person within a video or image frame. can. Once a golfer is identified, RMS 200 can capture and process video of that particular golfer. In other forms, AI logic 218 may also include golf logic and gesture recognition logic (not explicitly shown) functionality for processing video data using RMS 200. For example, AI logic 218 can detect a golfer holding a golf club and can further detect when the golf club hits a ball. In this way, the time intervals when the golfer hit the golf ball can be identified and the recorded video can be segmented and processed accordingly.

According to further aspects, RMS 200 may use AI logic 218 to process video, audio, or sensor input. For example, AI logic 218 can include object identification functionality that can be used to detect various types of objects. Once an object in the video is identified, the AI-enabled graphics processing engine 216 can be used to identify the portion of the video that has the identified object and create a video segment that has only that particular object. As an example, RMS 200 may be deployed on a golf course and AI logic 218 may be used to identify golfers with specific clothing, such as the color red. A video of a golfer wearing red can be segmented until the golfer is no longer in the video. According to further aspects, AI logic 218 may include golf logic that can identify golf objects, such as golf clubs, and golfers wearing a particular color, such as blue, in images of a video. RMS 200 may then process the video with those two objects in the video to create segments for those AI detected attributes.

According to further aspects, RMS 200 may also process other sensory information used with video to create media content that can be combined and communicated using communication module 214. For example, audio input 208 can output a time-stamped digital audio file that is synchronized with a time-stamped video file received from remote camera 204. For example, a microphone may be connected to audio input 208 and provide audio that may be used to detect the sound of a ball being hit or to detect voice or other audio from a player on a golf hole. can be entered. RMS 200 can then combine the video and audio files to output media content with enhanced media appeal. In a further aspect, RMS 200 can combine sensor input data with recorded video to create a superior digital media experience. In other forms, the sensor input(s) can be stored in a sensor data file that can be communicated with the video for further processing by a network service, as described below. For example, sensor data, such as weather sensor data, can be acquired and used in combination with recorded video. Sensor inputs 206 may include sensors including wind speed sensing mechanisms, thermometers, humidity, or other weather-related course conditions.

According to another aspect, sensor input 206 and radar sensor input or radar unit input can detect various aspects of objects moving within the field of view of one or more remote cameras 204. For example, the sensor input 206 as a radar unit input for golf may be used to provide information about the golf swing, ball speed, ball height, ball curve, or other data that can be added to the output digital media using the RMS 200. Various other forms of radar data input can be detected, or the digital media can be communicated to another service that can further process and combine the detected sensed radar data. The camera and radar combination can also be used to sense various aspects of the golf swing. For example, using a remote camera 204 configured as an AI-enabled camera, small differences in angle between two golf balls, as measured by the camera using optical zoom and pixel density in the recorded video. can be identified. This is a case where the phase difference is used in combination with, for example, a 20 GHz radar or a radar with a wavelength of about 0.6 inches. Camera and radar inputs can share information about where objects are located and what types of objects can be identified using AI logic 218. For example, an RMS 200 and an AI-enabled camera can be used to identify objects using AI logic 218 and radar inputs that have the same timestamp or recorded interval. RMS 200 may be used to provide movement characteristics of moving objects within a video frame using both AI-enabled graphics processing engine 216 and radar sensor unit data input to sensor input 206. In this way, an intelligent radar detection system that utilizes radar, image processing, and AI logic can be deployed for efficient digital media processing and video enhancement.

According to another aspect, RMS 200 may use only one or more of remote cameras 204 to detect AI objects in images captured using remote cameras 204. For example, some or all of the AI logic 218 can be stored within the remote camera 204 to identify videos with one or more objects associated with the remote camera 204 and record subsequent videos to the RMS 200. Can communicate. Cameras that include AI logic 218 may require a reduced amount of video to be recorded and communicated to processor 202 for subsequent video processing. Various forms of AI logic 218 may be used within remote camera 204 as described herein.

According to another aspect, RMS 200 may use no or only some of the AI processing locally within RMS 200, and may use remote network or cloud-based AI processing from RMS 200. Processing may also be used. For example, RMS 200 may locally initiate video recording using remote camera 204. The recorded video can then be communicated by RMS 200 to a remote processing system (eg, NMS 104, NMS 400, or other cloud service) to perform AI processing of the captured video. In this way, RMS 200 only needs to communicate media with a particular format size using communications module 204 for subsequent media processing, and then the media files are transferred to the Internet using communications module 204. Or can be uploaded to the cloud.

According to further aspects, RMS 200 may process video locally near the geographical location of installed remote cameras 204 to provide automatic monitoring and processing of desired activities. RMS 200 may use automatic detection and video recording/processing local to the installed field of view of remote camera 204, and the processed video may be transmitted to a destination using communication module 214. . For example, processed video may be received and transmitted to end users via an intermediate server or other communication device (not explicitly shown). RMS 200 can process the video to add various graphical elements to the captured video. For example, media processing engine 212 may be used to add information about golf holes, such as golf course names, hole numbers, logo information, sensor data information, weather information, or various other forms of graphical data. . According to one aspect, a golf ball can be detected within a video frame, and media processing engine 212 adds additional color graphics to indicate a trace or direction of the golf ball hit, user information, course information, etc. can be shown. Other elements may also be added using RMS 200 as described herein.

According to further aspects, a portion or all of RMS 200 can be incorporated into a mobile device having one or more integrated cameras. For example, a 108MPf/1.8 main camera, a 12MPf/2.2 ultrawide camera, and two 10MP telephoto cameras (one with f/2.4 aperture and 3x optical zoom, the other f/4.9 A mobile phone such as the Samsung Galaxy S21 Ultra, which has four rear cameras including a large aperture and a huge 10x optical zoom, can be used as the RMS200.

In another form, some or all of the RMS200 can be used with an Apple iPhone, including a three-camera system with an ultra-wide f/2.4 camera, a wide f/1.6 camera, and a telephoto f/2 camera. It can be incorporated into mobile phone cameras such as TM 12Pro. A front camera with a 12MP camera sensor is also provided. The mobile device includes a lidar scanner for low light conditions and a raw video processor for processing raw images and video files. Various other mobile devices with cameras can also be implemented as RMS 200.

Referring now to FIG. 3, an AI-enabled camera is disclosed for use with a remote media capture system. The AI-enabled camera, generally designated 300, can be implemented as various types of cameras as needed or desired, such as the RMS 102, 200, 710, 1136, the RMS of FIG. 6, or various other remote media systems. Can be used with

According to one aspect, the AI-enabled camera 300 is an HD camera, a UHD camera, a 4K camera, an 8K camera, a 360-degree camera, a 3D camera, a 4D camera, an augmented reality (AR) camera, a security camera, a Samsung Galaxy s21Ultra, or an Apple iPhone 12Pro. , a drone with a camera such as a DJI Spark Quadcopter, a GoPro camera that can be connected to a cell phone or other device, or a variety of other digital image capture devices that can record video.

According to one aspect, the AI-enabled camera 300 can be a UHD 4K camera manufactured by Bosch's model MIC IP ultra7100i camera, whose specifications and operating manual are incorporated herein by reference. In another form, AI- enabled camera 300 may include a Hanwha model PNP-9200RH, whose specifications and operating manual are incorporated herein by reference.

According to one aspect, the AI-enabled camera 300 includes a processor and memory 302, a first camera sensor 304, such as a PTZ sensor, a second camera sensor 306, such as an optical zoom-only sensor, and a variety of different image capture sensors. Other sensor technologies, generally designated as an nth camera sensor 308, may be included. AI-enabled camera 300 also includes a control module 310 for controlling each of the camera sensors and video storage 314 with memory for storing recorded video and images. AI-enabled camera 300 also includes built-in AI logic 316 that can be customized depending on usage or activity to sense using AI. For example, embedded AI logic 316 may include AI golf logic that can identify elements of golf holes, players, tee boxes, greens, golf balls, or various other objects. In other settings, other objects may be provided within the embedded AI logic 316 for use in capturing and processing digital media, including, but not limited to, sporting events and outdoor activities. Although shown as embedded AI logic 316, AI-enabled camera 300 can access remotely stored AI logic, such as AI logic 108 such as RMS or NMS, to enable AI detection of recorded images or objects. It can be done.

AI-enabled camera 300 also supports multiple wireless and wired communications, such as WiFi, cellular, Ethernet, PoE, HDMI, RS232, 802.11, Bluetooth, or custom communication interfaces. includes a communications module 318 that can be configured to use types of communications. AI-enabled camera 300 also includes a power supply module 320 configured to provide one or more power levels to power AI-enabled camera 300, the sensors, and the audio microphone as needed or desired. include. According to another embodiment, the sensor 308 can include an optical sensor, and in some forms an optical, motion, infrared, radar or Doppler sensor, Bluetooth sensor, WiFi sensor, RFID sensor, or various thereof. Various types or combinations of sensors may be included, including but not limited to combinations of sensors, and need not be limited to only light sensing.

According to one aspect, AI-enabled camera 300 may be configured to include zoom capabilities, including one or both of optical zoom and digital zoom, and tilt and pan so that AI-enabled camera 300 can be directed to a location. It may be further configured to have functions. For example, the AI-enabled cameras 300 may each be directed and zoomed toward a tee box with a golfer attempting to tee off, and may be adjusted to follow and zoom in on the golfer for subsequent shots during play. can. Using AI logic, the camera can tag specific users and track them while they play. In an alternative aspect, AI-enabled camera 300 may be a fixed field of view camera. In this manner, AI-enabled camera 300 can be configured to capture everything within its field of view and can also deploy digital and optical zoom capabilities without being rotated along an axis.

Referring now to FIG. 4, a block diagram illustrating network media processing and management services is disclosed. A network media processing and management service (NMS), shown generally at 400, can include a network processor 402 connected to a cloud storage and service 404, which processes and processes remote media system (RMS) 450 or digital media. A communication interface 406 is configured to communicate with any other remote video capture system or device configured to communicate video for creation. NMS 400 also includes an AI-enabled graphics processing engine 410 , an image processor 408 , and AI logic 412. Network processor 402 can access various modules or managers to process, manage, and communicate digital media and support resources. For example, NMS 400 may include a remote media source manager 414, a session creation manager 416, a location profile manager 418, and a user profile and statistics manager 420. NMS 400 may also include a content/file manager 422, a video process manager 424, a shot tracking module 426, a digital asset manager 428, and a sensor data manager 430. NMS 400 may also enable the use of format manager 432, output manager 434, and mobile app manager 436. NMS 400 may also include a performance manager 438, an AI logic manager 440, and a course manager 444. NMS 400 may output video received from RMS 450 as digital media to digital media-enabled destination 448 using distribution manager/communications interface 446 .

According to one aspect, NMS 400 may also include an AI-enabled graphics processing engine or GPU 410 and video/image processor 408 configured to process videos and images stored in cloud storage and services 404. For example, GPU 410 and/or image processor 408 can include various types of AI-enabled and image processors, and in one form are created, modified by NMS 400 or other AI-enabled devices or AI logic described herein. , one or more NVIDIA V100 Tensor Core GPUs capable of AI processing to generate and develop and train machine learning (ML) for AI logic 412 that can be distributed and used. According to one aspect, GPU 410 and/or network processor 402 may also utilize additional software and services to create AI logic 412. For example, GPU 410 can use AWS SageMaker to build, train, tune, and evaluate ML models. Sagemaker supports several ML development frameworks and, according to one aspect, can use Keras/TensorFlow. Additionally, NMS 400 can use Sagemaker NEO to prepare AI logic 412 models for deployment to remote processor and AI logic locations. Network processor 402 may use AI logic manager 440 to manage, distribute, update, and delete AI logic distributed to one or more of the plurality of locations using communication interface 406 . For example, one or more golf courses may have independent AI logic 412 created for specific golf holes. Accordingly, AI logic manager 440 may maintain a list and version control of AI logic 412 created and distributed by NMS 400 on a per-course and per-hole basis.

According to one aspect, network processor 402, image processor 408, and/or GPU 410 need not be considered a single processor, but rather can be used to process digital media, content, AI logic, and various It should be considered multiple processors and services that may be accessed by NMS 400 to process and output other outputs and services. For example, network processor 402 may be deployed using Amazon Cloud Services, IBM Cloud Services, Microsoft Cloud Services, or various combinations thereof, and may be implemented using any of the network communication protocols disclosed herein. It can be implemented as a cloud service with access to multiple managers and modules. Cloud storage and services 404 and distribution manager/communications interface 446 may also include various types of cloud storage and distribution services with different storage capabilities and accessibility. For example, some content may be stored for immediate access, while other forms of content may be stored for delayed access using deep storage techniques. For example, cloud storage and services 404 can include Amazon Web Services (AWS) Glacier for storing videos in the cloud. Additionally, content/file manager 422 and distribution manager/communications interface 446 may utilize AWS Cloudfront as a content distribution service to distribute videos to end users.

According to further aspects, video process manager 424 may be used to initiate post-processing of video received from communication interface 406 and RMS 450. For example, the video may be modified or edited to add additional graphical assets and formatted using a particular format provided by format manager 432. In one form, the NMS 400 can use a format manager 432 for post-processing and editing, and can use Python and OpenCV to edit videos on an AWS EC2 web server that can run on the NMS 400. . NMS 400 may also utilize AWS Elemental MediaTransform to transform or format the video prior to distribution using distribution manager/communications interface 446.

In operation, NMS 400 may receive a request to initiate a recording session using RMS 450. For example, a user with a valid user profile stored within user profile and statistics manager 420 may send a signal to NMS 400 using the user's mobile application. The request may originate from digital media enabled destination 448 or RMS 450. Location profile manager 418 may also be used in conjunction with user profile and statistics manager 420 to validate the request, and upon validation, creates a session by session creation manager 416 and activates a recording session using RMS 450 and associated devices. can be sent to RMS 450 for conversion. Session creation manager 416 may use content/file manager 422 to store session events such that when a valid video upload is initiated by an RMS 450 that has a valid session, content/file manager 422 initiates the upload. The videos and associated files/data may be stored using cloud storage and services 404. In one form, once the video transfer is initiated, RMS manager 414 may send an invalidation event to RMS 450 to disable recording of the event. In this way, efficient use of resources in RMS 450 may be achieved and less memory or local storage to RMS 450 may be required.

Once NMS 400 receives the uploaded video, video process manager 424 may begin post-processing the uploaded video stored within cloud storage and services. For example, content/file manager 422 can include the file name and destination of the video upload, and can further obtain post-processing information to process the uploaded video. For example, uploaded videos may contain information such as course name, location, hole number, user or golfer name, date and timestamp, GPS data, file size, file type, completed operations, required operations, or stored in metadata. It can have a specific file name with metadata that can include various other video processing data that can be used. Although described as being provided within the metadata of the video file, a separate log file or video content file can be provided if desired. Video process manager 424 can then process the video using the metadata and other digital assets. For example, the GPU 410 may be used to add a banner to the top of the video that includes the course name, hole number, player name, number of shots, and golf hole distance. Digital asset manager 428 can access digital assets and requirements for a particular course and golfer. According to another aspect, video process manager 424 includes various other forms of digital assets, graphics, text, logos, effects, marketing materials, promotional materials, or other materials that may be added to the processed video. A digital asset manager 428 configured to manage digital assets of the user can be accessed. For example, objects can be added to the video that correspond to particular brands, apparel types, club types, and/or swing types.

In another form, shot tracking module 426 can be accessed and used to add shot traces to golf shots in uploaded videos. For example, the videos may be processed using GPU 410, image processor 408, and AI logic 412 to identify golf balls from each of the videos. The frame position of the ball can be stored in memory, and a trace can be added as an overlay to the video to indicate the direction the ball is moving while the video is playing.

According to another aspect, sensor data manager 430 may be used in conjunction with shot tracking module 426 to manage other graphical representations of sensor data received from RMS 450 that may be added. For example, shot tracking module 426 may identify the ball as described above, further using sensor data to determine swing or ball speed, distance, ball flight, flight path, or using video process manager 424. Graphics can be added representing various other sensor data that can be added to the video. Performance data from the RMS 450's radar unit can provide sensor data uploaded from the RMS 450. Sensor data manager 430 can access session data, record time data, determine sensor data uploaded from RMS 450, and add sensor data to the video accordingly. In other forms, sensor data may be stored remotely to NMS 400 and sensor data manager 430 may be used to access acquired sensor data. For example, a third party sensor, such as a radar unit, can acquire sensor data at RMS 450. Accordingly, sensor data manager 430 may access third party databases or third party APIs to obtain sensor data. In other forms, third party APIs can be added to NMS 400 to access sensor data.

According to further aspects, digital asset manager 428 can be used to add various colors to shots detected using shot tracking module 426 and sensor data manager 430. For example, if the ball moves above a certain speed, a red or "hot" color can be applied to indicate high speed, or a flame graphic can be added to the ball as a tail. Similarly, if the ball flight is within what is considered a "straight line" green color may be applied to the ball flight to indicate no hooks or slices. Conversely, if the ball's flight is not straight, another color, such as yellow or red, can be applied to the ball's flight to indicate that it is not an ideal shot. In one aspect, golfers can indicate via the mobile device and mobile app manager 436 the types of indicators they would like to see displayed. Other forms of processing uploaded videos may also be implemented as described in various additional embodiments herein.

According to another aspect, NMS 400 uses performance manager 438 to identify performance trends related to golf holes, courses, players, or other detectable objects in videos captured using RMS 450. can be identified. For example, performance manager 438 may analyze multiple shots played on a hole and determine shot trends based on data from multiple players. In other forms, the AI logic 412 can analyze the video to identify the topology of the green and determine the overall success rate based on the location of the green's holes. The AI logic 412 that performs green analysis can also detect the direction in which the ball may cut when putted from a particular location on the green. A performance manager 438 using AI logic 412 can identify green characteristics by analyzing the video and can also determine shot trends for a particular golfer and store them within the user profile and statistics manager 420. .

According to further aspects, NMS 400 may use course manager 444, performance manager 438 , and user profile and statistics manager 420 to present analysis and playing suggestions and instructions between players and courses. .

In another aspect, a method of providing statistics is provided. The method includes identifying data associated with at least one of a golf hole or a player. The method further includes providing data related to the golf hole or player. The method may include presenting an average score for a hole, a green in regulation percentage for a hole, an average distance to a pin for a hole, or an average drive distance for a hole. The method may include presenting the player's score, presenting the player's green percentage in regulation, the player's average drive distance, or the player's average distance to the pin. Data may be associated with a single round, a single day, multiple rounds, multiple days, a single player, and/or multiple players. The method may include creating player statistics over a single hole or all holes played. The method may include providing pin drop graphics in the video or hole representation. A pin drop can correspond to a single player's shot or multiple players on the hole. The pin drop may include a link to the video associated with the shot identified by the pin drop.

According to further aspects, course manager 444 can be used to maintain and update course information, which can use video process manager 424. For example, course manager 444 provides digital assets that can be managed by digital asset manager 428 that are added to videos created on particular golf courses and holes. For example, logo information, course links, hole data, and location may be provided using course manager 444. Course manager 444 may also be used to maintain profiles of golf professionals located and working at a particular course. A profile description or biography of one or more golf professionals for a particular course may be maintained by course manager 444 and added to one or more user interfaces using mobile app manager 436. Each of the profiles can be turned on and off using course manager 444, allowing biographical information to be present within the mobile app. In this way, a mobile app associated with a particular course can be used to contact local golf professionals.

Update manager 442 updates updates made in one or more of the managers or modules described above to one of the other managers described above so that updated and modified information remains current throughout the system. Can be used to push to one or more.

5A-5D, a graphical user interface for a media-enabled mobile application is disclosed. The mobile application user interface is shown generally in FIGS. 5A-5D and can be used on a mobile phone, tablet, smart watch, golf cart, pull cart, push cart, powered "follow" cart, laptop computer, or any Can be provided within an application that can be used in whole or in part on other mobile devices. It will be appreciated that mobile applications with user interfaces 5A-5D may also be installed/implemented/accessible on other devices such as conventional computers, internet browsers, etc.

Referring now to FIG. 5A, an application home screen is shown generally at 500 and includes a home screen interface 502 with current weather conditions 504 and a video home background screen 506. Video home background screen 506 may include still images from previously recorded videos, or in some forms may include previously recorded animated videos of the user's golf shots. Home screen interface 502 also includes a messaging banner 512 configured to communicate new messages to app users. For example, it can provide current course conditions, it can provide messages from the golf course, it can provide advertisements or specials on the course, messages from other golfers or friends, or various other items or news items. can be displayed within message board 512. The home screen interface 502 also includes navigational elements including a home screen icon 514, a course icon 516, a check-in or scan icon 518, a My Shots icon 520 with a bubble section, and an account icon 522 containing user profile information. Home screen icon 514 displays home screen interface 502 when selected.

According to one aspect, when the user selects the course icon 516, a location screen interface 524 is displayed and includes a map view and a list view selector 526. When the map view is selected, a map 530 of a course 532 with video recording technology is displayed as a camera icon on the map. If the list view is selected, a list of courses (not explicitly shown) may be provided. Once a user selects a course 532, a golf hole description 538 with location, distance and direction 536, hole number, par and distance of the hole allows the user to access and reserve tee times on the course website. A course description screen 534 is displayed showing course details, such as one or more course links 540 to be viewed. A low-flying video or hole view section 542 provides a graphic or video description of a golf hole with video recording technology.

According to a further aspect, the mobile app can be used in conjunction with the course link 540 to schedule tee times within the location screen interface 524 (not explicitly shown). Course link 540 can include a process payment section and can be configured to use adaptive pricing based on demand. For example, when demand is low, the course link 540 with tee time schedule interface can automatically encourage discount pricing for playing rounds at the golf course.

According to a further aspect, when a golfer is playing a course that has video recording technology and they arrive at a hole, the golfer clicks the check-in or scan icon to access the check-in user interface 544 shown in FIG. 5B. 518 can be selected. The first check-in user interface 546 includes a QR code image 548, a scan now icon 550, and a question link 552 that describes where the QR code is located on a particular golf hole. can include. When the user selects the scan now icon 550, it is time for the golfer to take his shot, and the second check-in user interface 554 displays a countdown 556 of the golfer's video recording time. When recording begins, a third check-in interface 558 is displayed showing a tee-off message 560 and an animated recording icon 562 with a flashing red dot indicating that the camera is recording. Once the player completes the shot, the player can select the stop recording icon 564 to turn off recording. Each golfer can repeat this sequence and have the autonomous video technology record their shots.

According to one aspect, a QR code may not be available when the user arrives at the golf hole, or another form of check-in may be deployed. Accordingly, check-in user interface 546 may be updated to include a start video icon (not explicitly shown). For example, a mobile app can be used with location services to detect when a user arrives at a tee box, can select a check-in or scan icon 518, and can select a video start icon to check-in user interface 546. can be displayed within. Therefore, various other check-in methods can be used and are not limited to just checking in using a QR code and starting recording the user's shots.

Referring now to FIG. 5C, user interface 568 includes a graphical representation of notifications of available videos. User interface 568 shows a message 570 sent to a user of a mobile device having screen 566 . The mobile device can be a user's or golfer's mobile device, and the screen 566 is configured to allow notifications, messages, in-app messages, text messages, etc. to be displayed on the screen of the mobile device. It can be any part of a configured mobile device screen. In this way, once the recorded video has finished processing and the media is available, the user can receive a message that the video is available.

According to another aspect, the user may select the My Shots icon 520 to view a new previously created video. For example, My Shots user interface 572 may include an Activities tab 574, a Groups tab 576, and a Search Videos section 578 for searching for videos within My Shots user interface 572. A "NEW" label 580 is superimposed over new video 582 to indicate whether the video is new. Along with the new video 582 is a shot description 584 that can include the course name, hole description, and date the shot was made and the video was recorded. According to further aspects, My Shots user interface 572 further includes a share icon 588 for sharing new video 582 and a ReelTip icon 586 for sharing new video 582 with local professionals, as described below. include. Upon selection of share icon 588, a share user interface 594 is displayed within user interface 592 of screen 590. Sharing user interface 594 may include a share to social media tab 596 to allow users to share to social media destinations such as Facebook, Instagram, Twitter, and various other social media destinations. can. The sharing user interface 594 also includes a "Watch My Videos" tab 598 to launch a media viewer, a unique video link via text, email, or other messaging that allows users to share video links. Includes a "Copy Link to Video" tab 501 to enable copying and sending. The user can also delete videos using the video deletion tab 503.

According to further aspects, My Shots user interface 572 also includes a group tab 576 that can be selected within My Shots user interface 572. Group tab 576, when selected, displays each of the groups that the user played when the user played the hole (not explicitly shown) in which the video was recorded. For example, if the user was playing with three other golfers, each of the golfers' names and links to their shots may be displayed within the My Shots user interface 572. Additionally, each user in the group can also leave comments within the group tab section, further creating a private "message board" that can only be viewed and edited by the players they played with that day. In further embodiments described below, each user may be automatically added or removed from the groups section. For example, when a user checks in to take a shot using the check in or scan icon 518, the mobile app can automatically add each user profile to the groups section of the groups tab 576, thereby You can create an efficient way to share contact information, posts, comments, and other content with a group of golfers who played golf together that day.

According to a further aspect, group tab 576 may be used to communicate with golfers in a private group (not explicitly shown). For example, each member of a particular group of golfers may have downloaded a mobile app, and each golfer may be recording. Each golfer's shots can be aggregated and privately shown to golfers in a private group, thereby providing a series of shots for each golfer to view and comment on. In this way, groups outside of a single group can be created and displayed within the private groups section, thereby providing a private message board for any size group of players playing that course on that day. and social media platforms.

According to a further aspect, a Reel Tip user interface 507 may be displayed to the user when the user selects the ReelTip icon 586 to share a video with a local professional. Reel Tip user interface 507 may include a local golf course logo 509 where the video was shot and an explanation 511 of how to obtain tips on video from a local professional at that course. The Reel Tip user interface may also include a first pro information tab 513, a second pro information tab 515, and a third pro information tab 517. Pro information tabs can be added or removed based on the availability of pros that day to provide advice. Also, each pro information tab can include a photo section, a name and title section, and a small bio line. When the user selects the pro information tab, a pro information user interface 519 for the selected pro is displayed. For example, when the second pro information tab 515 is selected, the pro information user interface 519 includes a brief bio about the pro, an image of the pro 523, and a share icon 525 for sharing the video with the selected pro. Displays the professional's name and biography section 521. Selecting the share icon 525 may display a share selector (not explicitly shown), allowing the user to enter a link to the selected professional video via text, email, app message, etc. be able to. In this way, a dialogue between the player and the local pro can be created, thereby reducing the communication barriers that may exist between the player and the pro, thereby making the mobile app more accessible to golf players. to support the growth of

Referring now to FIG. 6, a diagram of an AI-enabled golf course is shown. AI golf (AIG) courses, generally designated 600, are designated as multi-hole golf courses and may include any number of golf holes, hole types, and facilities. For example, AIG course 600 can be an 18-hole course, a 9-hole course, a 3-hole course, a putting course, or any size course as desired. Additionally, an AI-enabled golf course need not be a traditional golf course, but can be provided as a golf facility that can be used for practice or entertainment. For example, an AI-enabled golf course can be implemented as a driving range or practice facility with multiple tee box locations, and a golfer hitting a golf ball at the same time can capture and provide video of each shot to the golfer. can. In other forms, an AI-enabled golf course may be implemented as an AI-enabled golf entertainment facility, such as an outdoor facility such as TopGolf or an indoor facility such as Rokgolf. AI-enabled cameras can be provided to record each bay, and video for each player can be recorded and processed for every shot as described herein. Thus, when a golfer leaves the facility, a video of their experience can be automatically created and communicated to the player's or participant's mobile app or other destination and/or social media outlet as needed or desired.

According to one aspect, AIG course 600 also includes a number of radar units that can be used in a variety of ways. The radar units described herein have single or multiple transmitters available that have high frequency (10 GHz) radio pulses that extend in a forward direction and whose reflected pulses can be returned to the receiver and detected by the radar unit. Can be done. The unit can further have array technology on the receiving side that can detect pulses reflecting back from a golf ball or other objects downrange using vertical and horizontal arrays of receiving elements. The timing at which the received pulse hits each receiving element is determined by the angle between that element and the golf ball. The timing difference can be used to determine the horizontal and vertical angles between the ball and the radar unit. Radar units can also be used to measure downrange objects that can generate reflected pulses, including pins, flags, green edges, holes, bunker trees, hazards, etc. Received pulses from a moving object are frequency shifted by an amount proportional to the object's velocity or overall size. For example, a radar unit can be used to measure the distance to the pin. The golf ball's reflected pulse is different from the pin, and when the moving ball stops, the unit can detect the ball's position relative to the pin position (each pin moves to a new position every day).

According to one aspect, the radar unit can include a conical region in front of it that can "see" the golf ball. This area can cover the entire golf course using multiple radar units. According to a further aspect, a radar unit can be used to detect a moving golf ball until it reaches the green and comes to rest. For example, the radar unit may also identify that there was no ball previously and there is now a ball on the green. The radar unit can measure the angle between the radar unit and the golf ball, and can also measure the distance to the golf ball relative to the pin that appeared in the morning after moving but did not move all day. .

When you pair a radar unit with AI-enabled video, the AIG Course 600 uses both the radar input, video input, and AI to detect various aspects of golf course play that would otherwise not be output. enables autonomous video processing that can output video footage specific to golfers. For example, radar has limitations in that it cannot determine one particular golfer from the next or pair stacked golf balls for a particular golfer with a particular portion of the video. By using an intelligent system that uses video processing, AI, and radar to detect specific golfers and their play, radar units can be combined within an AI-enabled golf course system to create a unique experience for golfers. Can be done.

According to one aspect, AIG course 600 includes a first hole 601 , a second hole 602 , a third hole 603 , a fourth hole 604 , and a fifth hole 605 . AIG course 600 also includes water hazards 606, creek hazards 607, and clubhouse 608. The first hole 601 includes a first hole tee box 609, a first hole green 610, and a first hole fairway 611. The first hole 601 is realized as a par 4 and includes a first hole tee box camera 612, a first hole fairway camera 613, and a first hole green camera 614. First hole 601 also includes a first hole radar 615 covering first hole tee box 609 and fairway 611 . First hall 601 also includes a first remote media system (RMS) 616 coupled to each of the first hall camera and first hall radar. RMS 616, and various other RMSs provided in FIG. 6, may be implemented on RMS 100 of FIG. 1, RMS 200 of FIG. 2, RMS 710 of FIG. 7, RMS 1124 of FIG. It can be provided as RMS.

According to further aspects, the AIG course 600 also includes a second hole rear tee box 617, a second hole intermediate tee box 618, a second hole front tee box 619, and a second hole green. A second hole 602 including 620 is included. The second hole 602 is configured to be a par 3 golf hole, with a rear tee box 617 and a front tee box 617 to record the golfer in either tee box and his shot to the green 620 of the second hole. The first camera 621 of the second hole is aligned with the third tee box 619 . The second hole 602 also includes a second hole second camera 622 aligned with the intermediate tee box 618 and green 620 to record the golfer using the intermediate tee box 618. It should be appreciated that each camera can be placed at a different height depending on the elevation or height of each tee and green combination. The second hole 602 also has a first greenside camera 623, a second greenside camera 624, and a third greenside camera 625 configured to record the golfer from various angles on the green 620. include.

According to further aspects, the AIG course 600 also includes a third hole 603 that includes a third hole tee box 626, a third hole green 628, and a third hole fairway 627. The third hole 603 is configured to be a par 4 golf hole. The third hole 603 is configured to use the first greenside camera 623 as a tee box camera for the third hole tee box 626. In this example, when the user is on the third tee box 626, the first greenside camera 623 leaves the second and third greenside cameras to record the action on the second green 620. can be rotated, pivoted, and focused toward the player on the third tee box 626. In this manner, the AIG course 600 may realize cost reductions in the number of cameras needed or required to record play on the AIG course 600. The third hole 603 also includes a first greenside camera 631, a second greenside camera 632, a third greenside camera 630, and a fairway camera 629. The second greenside camera 632 is in a position to record images of the third green 628 and the fourth hole 604, as will be described later.

Referring now to the fourth hole 604, a second greenside camera 632 is aligned with the fourth hole tee box 633 and fourth green 634 to record video on the fourth hole 604. can be done. The fourth hole 604 also includes a fourth green camera 635 to record the action on the green 634 of the fourth hole 604 and is provided as a par three. The RMS 647 is located between the third green 628 and the fourth hole tee box 633 and can be used to process video recorded at each location. Additionally, a fourth green camera 635 may be coupled to the RMS 647 to process and communicate recorded video on the fourth hall 604.

According to further aspects, the AIG course 600 includes a fifth hole 605 as a par 5, with a fifth hole tee box 636, a first fairway landing area 637, and a second fairway landing area 638. , and the green 639 of the fifth hole. The fifth hole 605 further includes a water hazard 606 on the right side of the fifth hole 605 and a creek 607 located between the first fairway landing area 637 and the second fairway landing area 638. The fifth hole 605 includes a fifth hole tee box camera 640, a first fairway camera 642, a second fairway camera 643, and a fifth green camera 644. The fifth hole 605 also includes a fifth hole radar 641 and a first fairway for processing a first portion of the fifth hole 605 including tee box video, radar data, and a first fairway video. Includes RMS648. The fifth hole 605 also includes a second RMS 649 configured to process a second fairway video and a fifth green video captured during play of the fifth hole 605.

According to further aspects, AIG course 600 includes a power network 645 that can power cameras, radar, RMS, and various other powered devices in AIG course 600. It should be appreciated that power network 645 is not limited to a single location and may be distributed by hole or other locations on AIG course 600. Different power levels can also be provided and accessed as needed.

AIG course 600 may also include driving range facilities 650 including driving tee locations 651, driving range cameras 652, one or more driving range radars 653, and driving range RMS 654. Depending on the overall size of the driving range facility 650, additional cameras, radar, and RMS may be provided. According to certain aspects, the driving range facility may be a conventional driving range with grass tees for teeing locations 651 and pin locations within the driving range. In another form, tee location 651 can be a driving bay location that can be used for entertainment similar to the TopGolf experience. For example, a user can reserve a bay within tee location 651 for a certain period of time and practice hitting golf balls toward targets within the driving range. In other forms, each bay may include one or more screens (not explicitly shown) for showing video media of the shot. In certain embodiments, each bay is configured with an AI-enabled camera as a driving range camera 652 to identify and record specific golf shots and process and output the video to a video screen within each bay. or in other forms, the video may be sent to the end user of those shots. The video may also be processed to add additional graphics, such as animations, VR graphics, etc. to the video captured by the driving range camera 652 to enhance the media experience. Although shown as part of the AIG course 600, it is noted that the driving range 650 can be a stand-alone facility that can be provided as an entertainment facility such as Topgolf, Rokgolf, or various other golf entertainment facilities. I want to be understood.

According to further aspects, AIG course 600 may also provide video, including live video or recorded and processed video, to one or more video screens within clubhouse 608. For example, a live feed of hole #4 604 may be displayed on a television screen within clubhouse 608. In one form, a daily near-pin or hole-in-one competition can take place at hole #4 604, and a live feed can be presented on a screen within the clubhouse to provide entertainment to patrons after the round. In some forms, a digital scoreboard may also be presented within the video or as part of a mobile application to show how close the competition is or who is in the lead.

According to another aspect, the video may be displayed when the player arrives at the clubhouse 608, allowing the player to view his shots upon arrival. A player may have a location device that can be tracked within the AIG course 600 (e.g., via GPS in a golf cart, location data from a mobile device, RFID tag, etc.) and may be tracked within the AIG course 600 when the player is at the clubhouse 608. In response to the entry, a recorded video specific to the arriving golfer may be displayed on a screen within the clubhouse 608, such as the restaurant/19th hole, bar, etc.

In other forms, shots may be recorded at entertainment venues such as Topgolf, Toprange, Rokgolf, etc. Each bay may include a display that can output captured video immediately after a shot of the player is taken. In addition, graphics can be added to the video, and in some formats, split screen can provide video of the golfer on one side of the screen, animation of the shot (e.g. top view) or graphic video can be added to the video. Presented on a separate part of the screen. In this way, players can see the actual swing in ball flight and can tag the video using their mobile device or other device where they can access the generated video for sharing, downloading, and viewing. can do.

Referring now to FIG. 7, an AI-enabled golf hole is disclosed. An AI-enabled golf (AIG) hole, shown generally at 700, includes a tee box 702 and a green 704. AIG hole 700 is designed as a par 3 golf hole with a single set of tees as shown. It should be appreciated that additional tees and tee boxes may be used and added to AIG hole 700 as needed or desired. AIG hole 700 also includes a first AI-enabled camera 706 located behind the tee box 702 and a second AI-enabled camera 708 located behind the green 704. Although shown as a two-camera system, additional cameras and/or AI-enabled cameras can be added to AIG hall 700 as needed or desired. Additionally, the first AI-enabled camera 706 can include a first camera field of view 732 and the second AI-enabled camera 708 can include a second camera field of view 734. Each field of view can be changed as necessary before, during, and after use. The first AI-enabled camera 706 and the second AI-enabled camera 708 may be provided as Bosch model MIC IP ultra7100i and include PTZ functionality as described above in FIG. 3. Other cameras may also be considered.

AIG Hall 700 also includes a remote media system (RMS) 710 located near AIG Hall 700 . RMS 710 provides network media processing and management services 714, generally designated as network media services (NMS) 714, and media-enabled destinations 716 for communicating video or digital media after capture and processing using AIG Hall 700. Can be connected.

According to further aspects, AIG Hall 700 also includes a microphone 718 for capturing audio, ball strikes, and player comments, a radar unit 720 for capturing details about the golfer's swing and ball flight, and a mobile device 724. and other devices located near the tee box 702, including an available QR golf code 722 that enables use of the AIG hole 700 for golfers who have a golf course. In one aspect, a QR golf code 722 is provided as a device. AIG hole 700 further includes a pin 726 configured to hold a pin 728 positioned over green 704 and having a pin height 730.

According to one aspect, first AI-enabled camera 706 and second AI-enabled camera 708 may be connected and powered by RMS 710. For example, the RMS710 has a PoE interface that allows you to connect multiple remote cameras while powering the cameras over long distances (in one example, the range for PoE is about 100 meters, or about 328 feet). communication interface. In one aspect, up to four PoE powered cameras can be attached to one main computer. The Wi-Fi radio on the main computer that communicates with the computer at the opposite end of the hall may also be powered by PoE. Each PoE cable may be sunk underground and connected to and powered by the RMS 710. Additionally, microphone 718 and radar unit 720 can also be connected directly to RMS 710 using a microphone cable, Ethernet cable, fiber optic cable, coaxial cable, or custom cable, depending on the type of microphone or radar unit deployed. . According to one aspect, the first AI-enabled camera 706 can also include an interface that allows connecting an external microphone or other sensor. Furthermore, the radar unit 720 need not be separately connected to the RMS 710, but can be connected using the communication interface of the first AI-enabled camera 706; It may be integrated into a housing with. Although described as connected to the first AI-enabled camera 706, it should be understood that one or more external devices can be connected to the second AI-enabled camera 708, if desired.

According to one aspect, the AIG hole 700 automatically detects the golfer's play, automatically records the golfer's play, processes the recorded video, and efficiently communicates or communicates the processed video. Including technology that allows you to upload. AIG Hall 700 can implement various embodiments and combinations of embodiments for activating recording. According to one aspect, one or more of the AI-enabled cameras 706/708 can be configured to detect the presence of one or more golfers within a predetermined area associated with the AI-enabled camera 706/708. can. For example, the first AI-enabled camera 706 may detect when a golfer is on the tee box 702 using a motion sensor within the camera and record video while the golfer is on the tee box 702. may be configured to start. Additionally, a second AI-enabled camera 706 uses a motion sensor to detect when one or more golfers are no longer on the green 704 and to stop recording video in their absence. Can be configured. In one form, both cameras may be turned on or off together or independently when a golfer is detected at each location. The recorded videos may be timestamped together and communicated to RMS 710 for further processing. In this way, a limited amount of video can be captured and recorded only when the golfer is present, thereby reducing the memory and The amount of processing is reduced.

According to further aspects, AIG Hall 700 can detect the presence of a golfer using wireless devices, signals and service detection. For example, a golfer, golf cart, watch, mobile device, or other device may have RF, Wifi, GPS, Bluetooth, or location-based service capabilities, and AIG Hall 700 may have one or more Can be modified to accommodate multiple. For example, a golfer may have an RFID chip detectable by one or more devices at AIG hall 700. An RFID chip or RFID tag can be affixed to the golfer, and the tee box 702 can include an RFID sensor that can detect when the RFID tag is located near or on the tee box 702. In other forms, the golf cart can include a GPS location-based service that can be used to trigger when the camera can start recording or stop recording based on the golf cart's location. In another aspect, the golfer can have a GPS-enabled smartwatch that can provide location or GPS services that can be detected by AIG Hall 700. A location services-enabled device, such as a mobile device, smart watch, golf watch, smartphone or tablet, or other GPS or location services-enabled device for communicating a GPS location; You can start and stop the camera based on. In certain forms, a golfer can have a mobile device and mobile application configured to communicate with the NMS 714 and provide a GPS location. NMS 714 can store multiple GPS locations of AIG holes that can be used in a mobile app on mobile device 724 for multiple golf courses. When a user actively uses a mobile device 724 in an AIG hall 700, the mobile device 724 can communicate its location to the NMS 714, and once it is verified to be on the tee box 702, the NMS 714 An activation signal or initiation event may be sent to RMS 710 to activate enabled camera 706 and second AI-enabled camera 708. When mobile device 724 leaves green 704, mobile device 724 may communicate its location to NMS 714 sufficient to send a deactivation signal or stop event to RMS 710 to stop recording. In this manner, location services can be used to trigger recording and not record play in AIG Hall 700. Although described as having NMS 714 track the location of mobile device 724, it should be understood that RMS 710 can communicate with mobile device 724 independently of NMS 714. Additionally, one or more geofences may be placed around the tee box 702 and green 704 of sufficient size to activate and deactivate play recording. Geofences are a form of location service that can be stored and modified within NMS 714, and mobile device 724 and NMS 714 can initiate activation and deactivation upon entering and leaving each geofence.

According to another aspect, the golfer can use the mobile device 724 to activate and deactivate recordings via a mobile application stored on the mobile device 724. For example, when a golfer is about to make a shot, they can use a mobile application and select a start recording icon within the mobile application. Mobile device 724 may communicate with RMS 710 and/or NMS 714 to activate recording using AI-enabled camera 706/708. When the golfer finishes his tee shot or exits the green, the golfer can select the stop recording icon within the mobile application and the RMS 710 and/or NMS 714 will direct the AI-enabled camera 706/708 to stop recording. You can send a request to . In this way, a golfer can initiate recording at AIG Hall 700 using manual start/stop, and RMS 710 and NMS 714 can The player identifier can be used to process the video for the golfer.

According to one aspect, golfers can be detected using AI golf logic 712 of AIG hole 700. For example, a mobile device 724 having a mobile application can be used to scan a QR golf code 722, and the AIG hall 700 activates one or more cameras in response to the QR golf code 722 being scanned. can do.

In further embodiments, upon activating the AI-enabled camera using one or more of the techniques described herein, the first AI-enabled camera 706 and/or the second AI-enabled camera 708 You can take an image of the golfer who started the game. Golfer attributes such as clothing color, skin color, height, golf club, or various other attributes may be compared to AI logic with AI golf logic 712, and the AI logic 712 is compared to the captured image. can be used for. The results of the comparison can then be used to actively record the golfer and further process the video with the AI logic comparison results. For example, the results of the comparison may be a log file, a user file, an AI log file, or a single entry for one golfer, a series of entries for multiple golfers, or for all golfers who played AIG Hole 700. It can be stored in other storage files that can even contain daily entries. The files can then be used to process the recorded video to generate video segments for each identified golfer. When the golfer is no longer detected at the AIG hole 700, the RMS 700 can initiate a stop recording event for each camera and the recorded video is passed to the AI golf logic 712 and Further processing can be performed using RMS710.

According to another aspect, a golfer using a mobile device 724 can use a QR code or QR golf code 722 to initiate a recording. QR Golf Code 722 is a golf-specific QR Code that can be used to activate one or more specific remote cameras located at a specific golf hole. Contains hole identifier. The QR golf code 722 has built-in visual logic that can be decoded by a mobile app on a mobile device 724 to enable recording to be activated using a remote camera placed at that particular location. include. In this disclosure, a mobile device 724 may be used to scan and capture the QR golf code 722 using a mobile app. Mobile device 724 may then send a message to initiate a session for mobile device 724 and the user with the unique identifier of AIG Hall 700 to initiate a recording session. Mobile device 724 can communicate a message with unique credentials to activate recording at AIG hall 700.

According to further aspects, QR golf codes 722 and AI golf logic 712 can be combined to activate, deactivate, and process recordings for particular golfers. For example, a golfer can initiate a recording using a QR golf code 722 placed at a particular location on the AIG hole 700, and one or more AI-enabled cameras produce video of the particular golfer. You can take photos of golfers that can be processed and used to play. The user ID obtained from the mobile device 724 can be paired with the image, and the AI golf logic 712 generates AI log output specific to the golfer and connects the RMS 710 and/or to process the recorded video. Can be used by NMS714.

According to further embodiments, the QR golf code 722 may be combined with location services, GPS, motion detection, or other methods of detecting the presence of a camera on the AIG hall 700 as a way to activate a recording session. Additionally, the QR golf code 722 can also include an RFID tag placed below the printed or posted QR golf code 722. When the mobile device 724 is activated to scan the QR golf code 722, it may also activate the RFID reader of the mobile device 724. By activating the RFID reader, the QR golf code 722 containing the RFID tag can confirm that a user or mobile device is in the vicinity of the QR golf code 722. Accordingly, an additional layer of authentication can be achieved before activating AIG Hall 700, thereby avoiding security risks or threats that may pose a risk to AIG Hall 700. Each RFID tag is created specifically for each golf hole and has unique authentication information that can be added and communicated to the NMS 714 to initiate and authenticate the session.

According to another aspect, RMS 710 can be configured in a variety of ways to support ongoing recording, processing, and delivery of video to NMS 714. Various aspects of a remote media system (RMS) are described throughout the figures and methods and can be implemented by the RMS 710. For example, the RMS 710 may be used to process various signals and images to identify valid golfers and initiate recording of the golfers. The recorded session is processed by the RMS 710 using the video and audio inputs to identify when the golfer hits the golf ball and further slice segments of the video to create a processed video for the specific golfer. can be created. RMS 710 also compresses the video to ensure efficient and cost-effective uploading of processed video.

According to further aspects, RMS 710 can act as an agent and performance manager for each camera installed in AIG hall 700. As an agent, RMS 710 uses events communicated between the devices to record video for a particular golfer, and to communicate with mobile device 724, NMS 714 and first AI-enabled camera 706 and second AI-enabled camera 708. Negotiate communications between. RMS 710 can also be used to record events and other performance data of devices within AIG Hall 700's local network and can communicate log files to NMS 714 for remote access and storage. RMS 710 may also store operational data for each device as well as installation and calibration data for each device connected to RMS 710. In one aspect, RMS 710 can include initial calibration data for each camera, which can include GPS locations of each installed device, such as cameras, radar units, microphones, QR codes, and other sensors. In one form, the position or camera position can be obtained and used to determine the distance to the green on the tee box or the flag on the tee. AI-enabled cameras 706/708 can be calibrated with a reference device, such as a yardstick, to obtain a specific optical zoom for each camera. A yardstick image is a combination of the number of pixels acquired using a yardstick and can serve as a reference for detecting and storing the distance of objects within the camera's field of view. By using the reference, as pin 728 on green 704 moves along the green, the distance of the pin can be calculated based on the number of pixels lost or gained at a particular optical level. . Additionally, as the tee 736 on the tee box 702 moves, the distance from the tee to the camera can also be determined and stored. When combined, the difference in distance from (camera to tee) to (camera to pin) can be used to determine the overall distance from tee 736 to pin 728. Various other objects and distances may be used by RMS 710 to determine some distances.

In another aspect, each AI-enabled camera 706/708 and/or radar unit 720 may be used during recording to capture details of the shots made by the golfer. For example, the first AI-enabled camera 706 can record video of the golfer and use the video to add a trace on the video indicating the direction the golf ball was hit using the RMS 710 and/or the NMS 714. can do. In this case, each frame of the golfer's video segment can be processed and image recognition and AI golf logic 712 can be used to place the golf ball within the frame. As the ball moves from frame to frame, the position in the video can be identified and stored such that the X/Y coordinate system positions the ball within the frame. The resulting X/Y coordinates can be used to draw the line along which the ball has moved in the recorded video. Depending on the distance traveled over the duration of the frame and the height reached by the ball within each frame, it also determines the overall speed of the ball, as well as the height (vertex) and curve (left/right) of the ball traveled be able to.

In another form, radar unit 720 is used in conjunction with the video or independently from the captured video to detect location and ball flight details and send the details to RMS 710 and/or NMS 714 for video processing. Can communicate. As mentioned above, radar unit 720 uses radar technology to capture the velocity, distance, height, and curve of the ball and communicates the resulting information to generate graphics that can be added to the video segment. It can be possible to create. As of the filing date of this disclosure, https://trackmangolf. One such system, such as the TrackMan Range manufactured by TrackMan, described in detail at www.com/products/range, or other radar systems, may be used as needed or desired. be able to.

Referring now to FIG. 8, a method of activating recording using an autonomous media processing system is disclosed. The method may be used by one or more of a system, device, processor, module, software, firmware, or various other forms of processing to perform the method described in FIG. Further, the method of FIG. 8 may be implemented as being within various portions of FIGS. and may be modified to include features.

The method generally begins at step 800 and can be used at various geographic locations where a given activity is performed. As an example, the method can be used for golf course activation, video capture, and video processing. At step 802, the method detects whether a golfer is detected at a golf hole. For example, a golfer may be detected as he approaches a tee box in connection with playing a golf hole. Detection can occur in a variety of ways, including using in-mobile GPS, RFID devices, Wi-Fi detection, Bluetooth detection, location services, radar detection, motion detection, thermal or thermal detection, or various other sensing techniques. It can be carried out. In addition to detecting the presence of individual golfers, similar transmitters can be provided on golf carts and the like to indicate the presence of one or more golfers. It will be appreciated that other detection mechanisms may also be used. For example, in one form, a location service for a golfer on a mobile device that has an application for recording video can be detected. For example, a geofence can be placed around a particular tee box, and when a golfer with a mobile app or other item triggers the geofence, the golfer can be detected.

According to another aspect, at step 802, a user can scan a QR code using a mobile app on a mobile device, as described herein. The method captures a QR code and sends the QR code with a mobile device or app identifier and a golf hole unique identifier added to the message to initiate a recording session. used for For example, the method can combine a unique QR code with a user or mobile identifier and use it to communicate a message to the service, which can have a unique identification code and the user.

According to another aspect, at step 802, a golfer may be detected by a user selecting a recording icon within a mobile app. For example, the method can be used to monitor mobile device input including requests to start recording. The method may send a message including a request confirming that the golfer has been detected. In one form, the method may combine and communicate a mobile app identifier and a mobile device location, respectively, to confirm that the user is at a golf hole with an AI-enabled camera.

Upon detecting the presence of a golfer, the method may proceed to step 804 and a session ID may be created for the golfer. A session ID is unique to a golfer and includes information specific to the golfer, such as a golfer-specific ID, a date and time stamp, the location of the golf hole, and other items that can be used to create the session ID. can include. In one form, the method can be used to access a golfer's mobile application that can have unique information about the user that can be used to initiate a session ID. Once the session ID is created, the method may proceed to step 806 and activate one or more AI-enabled cameras and any associated microphones at a particular golf hole. In one form, the method can include accessing the created session ID and communicating the session ID as a valid ID for a particular golfer. In this way, AI-enabled cameras and microphones can be activated without having to manually initiate recording with the camera or without capturing the individual with the camera.

In another form, scanning a QR code can be used to activate the camera and microphone at step 806. For example, the method may include receiving a QR code identifier of the golf hole being played from the golf player's mobile device. The QR Code identifier can be sent to a remote media system or network media processing and management service to initiate a valid scan or session. If the QR code identifier is valid, an activation code can be sent to a local resource, such as an RMS or AI-enabled camera, to activate the recorded video and audio.

Upon activation of the camera and microphone, the method proceeds to step 810 where an image of the golfer may be captured. For example, a golfer may be positioned on a tee box and an activated camera may capture an image of the golfer. In another form, the golfer can manually launch the camera using the start icon within the mobile app, and the method can capture images of the golfer. In another form, the golfer may be scanning a QR code at a particular location near the tee box, and the camera may capture an image of the golfer. For example, an AI-enabled camera or RMS may have the GPS coordinates of a particular QR code that is being scanned, and an AI-enabled camera may have the GPS coordinates of a particular QR code that is being scanned with a session ID. You can pan, zoom, tilt, and focus at or near the ® . Accordingly, an image of the golfer can be captured and used to further identify the golfer in future video captures.

Once the image of the golfer is captured, the method may proceed to step 812, where the image may be compared to AI logic and/or NN within the RMS local to the AI-enabled camera or golf hole. In some cases, the method can access a cloud-based service with AI logic and/or NN to compare images. The AI logic described herein can be used to identify various objects. For example, the color of a golfer's shirt, shorts, hat, shoes, pants, socks, skin color, or various other colored clothing can be identified and tagged using images. The tagged data may be provided within the metadata of the image, but in other forms may be provided as an image file with the image data, or with the golfer's session ID. . In other forms, the method can be used to identify golf objects that may be held by a golfer. For example, the AI logic can also include AI golf logic that can be accessed and the image can be compared to the AI golf logic to determine or identify the golfer. The AI golf logic may include identifying a particular club with a number, golf ball, golf tee, tee box, or various other golf objects, as disclosed herein. By identifying and tagging images of golfer objects using AI logic and/or AI golf logic, the method can be used to create golfer-specific videos.

At block 816, the method may continue to enable recording video using an AI-enabled camera at the tee box of the golf hole to detect when the golfer enters the tee box. For example, after capturing an image of the golfer in step 810, the AI-enabled camera can pan, tilt, zoom, and focus as needed on the tee box being played. AI-enabled cameras can detect when a golfer enters the tee box. In one form, the stored AI object identifier can be used to detect when a golfer enters the tee box. In other forms, the AI-enabled camera can mark zones within the image frame as valid locations for the tee box and can detect when activity may occur within the zone. Zones can be marked automatically after calibrating the camera during installation and marking the zone of a particular tee box. Multiple zones or tee boxes can be marked and stored within the AI-enabled camera or RMS for use in detecting when a golfer enters the tee box.

Upon detecting a user, the method may proceed to step 822 and identify the golfer on the tee box. As discussed above, various objects may be identified in steps 812 and 814 and may be used to identify the golfer when the golfer is on the tee box. If the golfer is not valid or may be a golfer who should not be recorded due to lack of ID, the method returns to step 820 to detect when another user may be present on the tee box. At block 822, if a valid golfer is detected, the method proceeds to step 824 and records the golfer on the tee box. The method then proceeds to step 826 and determines whether the golfer has left the tee box. A golfer on a tee box can be detected using various methods described herein. If the golfer has not left the tee box, the method proceeds to step 824 and continues recording the golfer on the tee box. In step 826, if the golfer leaves the tee box, the method proceeds to step 828 and stops recording the golfer.

Once recording is stopped, the method can proceed in two directions, one process detecting whether another golfer is present and the other process processing the captured video. Each process can be performed serially or otherwise, and can be performed simultaneously. In this way, a first golfer's video can be processed and uploaded, a second golfer's video can be captured, and each golfer's video can be efficiently captured and processed, and the golfer can Allows for a reduction in delay when being able to receive recorded video.

Accordingly, in step 830, the method accesses the captured video and audio for the golfer and processes the media in step 832. For example, the video and audio may be digital recordings that include timestamps for each frame. However, the frames may not be synchronized with each other. Additionally, audio files or tracks of a particular time period may not be overlaid with simultaneously captured video. Accordingly, each media file can be processed, aligned, and combined into a single media file as needed or desired.

Once the media has been processed, the method can proceed to step 834 and can detect when a golf ball strike occurs. For example, media files, video files, and/or audio files may be accessed to detect when a golf ball is hit by a golfer. When accessing a video file, the method may scan the image data of the video file using image processing to identify the golf ball as it moves from frame to frame. The method may also use AI golf logic to detect a golf club at a particular location and a golf ball that deviates from a particular location within the frame. In another form, you can access and listen to audio files when you may have hit a golf ball. For example, the method may include accessing an audio file to compare or look for the sound of a golf ball hitting, and may identify a particular frame when the ball was stuck. In another aspect, media files or both video and audio files can be accessed to detect visual images or frames of when the golf balls are stacked and audio frames when the balls are stacked. Upon identifying when the ball is stuck, the method can proceed to 836 and identify the beginning of the video segment. For example, an average golf swing may take less than two seconds. Thus, a golf ball strike can be used to identify a 2-3 second period or frame period prior to a ball strike. Further, the method can identify the frame when the golfer exits the tee box. In this manner, the start and end portions of the video can be identified and the method can proceed to step 838 and slice the video into final segments. In this way, reduced versions of videos captured by AI-enabled cameras can be efficiently created and uploaded, thereby increasing upload speeds and reducing the cost of uploading videos. Although shown to slice video segments in a specific way, other combinations that identify video and audio segments can be deployed to reduce video and audio file sizes for subsequent upload and processing It will be appreciated that the overall benefits of this can be obtained. Various video formats and media file sizes, such as 8K and 4K videos, may be too large to communicate over cellular networks. Accordingly, the method in step 840 can handle larger video formats and, if necessary, H. 264 format and upload as HD, UHD, or other digital media file formats. The method can then proceed to step 842, where the video can be uploaded to a network location or destination for further processing. In one form, the session ID may include a network destination to upload the video for further processing by an RMS, NMS, or other device or service. Additional data files may also include, but are not limited to, data files, operational files, control logs, metadata, sensor data, radar data, and other forms of data or information files that may be uploaded with the processed video. You can upload using the session ID.

At step 828, the method may also proceed to step 846 and detect whether another golfer has been detected. If another golfer is detected, the method proceeds to step 804 and repeats as necessary. At step 846, if no additional golfers are detected, the method may proceed to step 848 and the camera and microphone may be placed in an idle or reduced power state. The method can then proceed to step 800 and repeat.

The method of FIG. 8 may be configured in various methods or method sequences in particular embodiments to enable efficient capture, processing, and distribution of user experiences on a golf course. The method in Figure 8 detects when a specific QR code is scanned on a golf course, activates an AI-enabled camera to identify the golfer, and uses AI objects and video slices to create a video of the golfer. allows you to record and process videos to create efficient uploads of videos with reduced latency.

FIG. 9 illustrates a method for autonomous media post-processing according to one aspect of the present disclosure. The method may be used by one or more of a system, device, processor, module, software, firmware, or various other forms of processing to perform the method described in FIG. Further, FIG. 9 may be implemented as being within various portions of FIGS. 1-8 and 10-11, and in some aspects may incorporate the various functions, uses, and features described therein. may be modified to include.

The method generally begins at step 901. Once the video is received from a remote video source in step 903, the method proceeds to step 905 and identifies activity within the video. Various activities described herein can be stored within various AI logic created using machine learning as neural networks. The portion of the video may be compared to the AI logic, and if no activity is detected, the method may proceed to block 907 and process the video to identify new activity. In some forms, processing may include tagging or identifying objects in the video that are specific to the activity and may be used by machine learning for one or more activities. Once the video is processed, the method proceeds to block 909 and determines whether to create a new activity within the neural network. For example, while various activities may be identified as described herein, in some forms sub-activities within an activity category may also be created. Examples of this activity include a golfer slicing or hooking a ball, a golfer throwing a club, a golfer high-fiving another golfer, a golfer making a hole-in-one, or various other activities or subs that may be created as a form of golf activity. Can contain activities. If an activity is to be created, the method proceeds to step 911 and identifies an available object or set of objects present within the image frame of the video. The method may proceed to step 9 1 3 to label the identified object and then proceed to block 9 1 5 to add the object or frame to the AI logic of that activity. In some forms, if the activity exists, the object may be added to the activity's neural network; in other forms, if the activity does not exist and the neural network is unavailable, the method may add the object to the activity's neural network within the AI logic. New neural networks and machine learning instances can be generated for use. The method then proceeds to step 917 to process the AI logic and proceeds to step 919 to determine whether the activity is valid and can be published within the AI logic. For example, the accuracy of a neural network can include a dependence on the number of objects identified for its activity and provided to the machine learning instance. If only one instance exists, the AI logic is likely to fail. When additional objects are identified and used within the machine learning instance, the AI logic has a statistically better chance of identifying the activity. If additional objects are needed for the activity, the method proceeds to step 901 until additional video is received. If the activity is currently enabled in step 919, the machine learning instance may enable AI logic for that activity in step 921 and proceed to step 923 to distribute the AI logic to various locations as needed. can. The method then proceeds to step 925 and ends. The method may include zooming in on the video, zooming out on the video, or panning within the video, and the degree of zooming in/out or panning may be determined by AI logic based on detected aspects of the video. . Zoom and pan aspects may be performed automatically.

If activity is identified in step 905, the method proceeds to step 927 and determines whether the video is available for output or storage. For example, a local video processor may be processing enough video for distribution. Accordingly, a remote video processor, such as system 900, can use data provided to the video to detect whether the video requires additional processing. If the video is valid for output, the method may proceed to step 929 and format the video using a format manager. For example, a video may need to be formatted for output to a mobile device or application with specific formats, file sizes, and other specifications required in connection with posting the video. Videos provided to various locations and applications may include Facebook, YouTube, Instagram, Snapchat, and other applications. Each utilized app may require its own format for publishing to a particular network. Accordingly, the format manager can determine one or more positions of the video and format it accordingly. In other forms, the video may be processed to be delivered to a network location with high definition or 4K video output on a fixed output device, such as a particular monitor. Various types of formats can be used to output video to various destinations. Once the video is formatted, the method proceeds to step 931 and distributes the formatted video using a distribution manager. For example, a video may be a single instance delivered to a cloud storage account configured to store the video. However, in other forms, the video may be formatted into multiple formats, thus creating multiple videos that may need to be distributed. Accordingly, in step 931, the video is distributed to those destinations. The method then proceeds to step 925 and ends.

If the video is not available for output at step 927, the method proceeds to process the video. For example, the method includes three different types of processing that can be used to process video, and are provided in no particular order and only as a basis for describing the processing of video. At block 933, the method determines whether one or more user actions need to be performed. For example, a local video processor may provide information to a particular user whose video has been recorded. Therefore, that information can be used to identify the user within the video. Various types including facial recognition, geofencing, GPS or location services location identification, grid identification, manual input from the user's mobile app, or various other triggers that can be used to identify specific users in the video identification can be used. The method may also use AI logic to identify a particular user and provide video to that user's characteristics, details, and/or objects. Once the user is identified, the method proceeds to step 937 and extracts segments of the video associated with the user. For example, the identified user may be a football player with a particular jersey number and name. The method identifies all segments of a video where soccer players are present and extracts those segments from other players. In another form, a golfer may be playing a hole on a golf course with other players, and the video may include numerous other shots or activities taken by the other golfers. Thus, the method can identify particular users and activities within various segments of a video and remove segments that do not include users. In this way, you can create videos just for golfers. Once the video segment has been extracted, the method proceeds to step 939 and determines whether the end of the video has been reached. Otherwise, the method continues to step 937 and repeats. If the video is finished, the method proceeds to step 941 and determines whether the video should be processed for a new user. For example, as mentioned above, multiple golfers or players may be part of the same captured video. Accordingly, if desired, a new user can be identified at block 935 and the method can proceed as described above. In this way, multiple segments specific to a particular user can be extracted from a single video, thereby reducing the number of video uploads required for processing. For example, at a soccer field, a single video can be uploaded and a method can extract the video footage of each player, thereby providing it to each player, each player's teammates, coaches, etc. You can create unique video segments for each player. At block 941, although multiple users may be detected, the method may not want to extract video segments for all users, and the method can contain profiles.

If the method determines in step 941 that no additional user segments should be extracted, the method may proceed to step 943. In step 943, the method determines whether the segment requires further processing. For example, if only a single segment of a video is extracted, no additional processing is required to combine the segments. If the video segments require additional processing in step 943, the method proceeds to step 945 and combines each user's segments into a single video. For example, segments can be extracted and stored as part of a video or video segment. At step 945, the segments may be combined together to create a single composite video for the user. Once the segments are combined, the method proceeds to step 947 and combines the video segments for the remaining users to create a unique video for each user. Thus, each participant can have their own video with segments created for their unique experience.

Once the video has been processed as desired, the method proceeds to step 949 and determines whether effects need to be added to the video. For example, a content manager, such as content manager 422 of FIG. 4 or other autonomous content manager, may identify videos of golfers playing a golf hole that is a recreational area, such as Omni Barton Creek. The content manager may store an introductory video of a drone flyover of a golf hole being played and may add the introductory video to the user's video segment. In other forms, an animated graphic showing the distance to the hole can be drawn from the tee box to the green from a "top down" view of the hole. Other effects may also include adding user and other player audio or additional captured video in the activity. In one form, portions of the video segment can be identified or tagged to add tracers to the movement of the ball as part of creating the effect. In another example, AI logic can be used to detect when the ball is located around the green in an undesirable location for the golfer. In that case, you can add enhanced effects to the video, such as traps, water hazards, etc. when the ball enters the forest. Enhanced effects can include animated video overlays. For example, an animation of the Loch Ness Monster stealing a golf ball as it enters a water hazard may be added to the video segment. Other animations may also be used and added as needed or desired. In this way, augmented reality can be added to a user's video. According to a further aspect, the video can add a ball tracing effect to shots made by the golfer. For example, this method can be used to identify a golf ball within a frame of a video and add colored trace lines to each frame to indicate the ball's path. If the video includes a video segment of the ball entering the green, a trace can be added to the video as the ball lands on the green. In some cases, AI logic or image processing can be used to locate the ball within the frame, and in some cases, the video can be reversed after the ball is located on the green. For example, when a user approaches his golf ball on the green, AI logic or image processing can identify the user and add effects or other content before the user picks up or interacts with the ball. In this way, through reverse processing of the video data, the ball can be traced back to previous frames or segments, and the video modified accordingly for that particular user. In another form, the effects may include audio effects, music, or sounds added to the video. For example, music can be added over all or part of the video and can include varying audio levels. You can also add unique sounds to your videos based on what's happening in the video. For example, a user can drive a ball into a forest, and a "chainsaw" sound, clapping sounds, laughter, cheers, or other sound effects can be added to the video segment. In another form, AI logic or image processing can be used to identify when a golf ball enters the cup, and a "ball falling into the cup" sound effect can be added. Effects can be predetermined based on activities or subactivities identified by AI logic. In this way, the method can access labels within video segments and automatically add desired effects to portions or segments of the video.

After adding effects as needed, the method proceeds to step 953 and determines whether graphics need to be added to the video. If no additional graphics need to be added, the method proceeds to step 929 and ends. If additional graphics are to be added, the method proceeds to step 955 where additional graphics are added from an asset resource, such as asset 914, using content manager 422 of FIG. 4 or other assets or content resources as needed or desired. Get the content or graphics you want. An asset or graphic may include one or more graphics for addition to a video image or video segment. For example, the graphics may include the golfer's name, the date, the golf course, the hole number, the distance to the hole, the club used by the golfer, the current weather conditions, the maximum height of the ball or the speed of the ball after it is hit, the curvature of the ball in flight, the maximum distance traveled by the ball, the current stroke or number of strokes taken, the par of the hole, information about other players currently playing, or other player information as needed or desired. It can include information such as course information. According to another aspect, the golf course may include the name of the golf course, the logo of the golf course, the age or time of establishment, the name of the current professional, the name of the owner, or whatever the golf course wishes to be added to the video segment. may include graphical assets added to segments of the video, such as other types of marketing assets or graphics. Although described as adding assets for the golf industry, other graphical assets can be added to the video as needed or desired. Once the graphical assets are obtained, the method proceeds to step 957 and adds assets or graphics to a particular video image or segment to modify the segment. The method then proceeds to step 929 and the method ends.

The method of FIG. 9 can be modified as necessary to combine or remove various parts as desired. For example, once the activities or sub-activities are identified in step 905, the method can be used to segment the video and further process the video segments to identify the sub-activities. A segment can be labeled as having its subactivities, and the labels can be further used to process the segment, add effects, add graphics, or perform various other types of processing on the video segment. Can be done. In this way, automated processes using AI logic can efficiently edit and process videos without the need to manually modify and edit the videos individually.

If the video is valid for output, the method may proceed to step 929 and format the video using a format manager. For example, a video may need to be formatted for output to a mobile device or application with specific formats, file sizes, and other specifications required in connection with posting the video. Videos provided to various locations and applications may include Facebook, YouTube, Instagram, Snapchat, and other applications. Each utilized app may require its own format for publishing to a particular network. Accordingly, the format manager can determine one or more positions of the video and format it accordingly. In other forms, the video may be processed to be delivered to a network location with high definition or 4K video output on a fixed output device, such as a particular monitor. Various types of formats can be used for the video for output to various destination assets 914 using the content manager 422 of FIG. 4 or other assets or content resources as needed or desired. An asset or graphic may include one or more graphics for addition to a video image or video segment. For example, the graphics may include the golfer's name, the date, the golf course, the hole number, the distance to the hole, the club used by the golfer, the current weather conditions, the maximum height of the ball or the speed of the ball after it is hit, the curvature of the ball in flight, the maximum distance traveled by the ball, the current stroke or number of strokes taken, the par of the hole, information about other players currently playing, or other player information as needed or desired. It can include information such as course information. According to another aspect, the golf course may include the name of the golf course, the logo of the golf course, the age or time of establishment, the name of the current professional, the name of the owner, or whatever the golf course wishes to be added to the video segment. may include graphical assets added to segments of the video, such as other types of marketing assets or graphics. Although described as adding assets for the golf industry, other graphical assets can be added to the video as needed or desired. Once the graphical assets are obtained, the method proceeds to step 957 and adds assets or graphics to a particular video image or segment to modify the segment. The method then proceeds to step 929 and the method ends.

According to another aspect, in step 953, the method can also include post-processing to include graphics or video enhancement. In one aspect, the player's name may be provided on the screen before their shot. In another aspect, the player's score may be provided on the screen. In another aspect, the club being used can be displayed. Various other graphics can be overlaid on the screen to provide video resembling professional broadcasts. The graphics overlaid on the video may include various data related to the player or the shot being played.

FIG. 10 illustrates a method of using a media-enabled mobile application according to one aspect of the disclosure. The method can be used to output the user interfaces shown in FIGS. 5A-5D and can be used on mobile phones, tablets, smart watches, golf carts, pull carts, push carts, powered "follow" carts, laptop computers, or may be provided within an application that can be used in whole or in part on any other mobile device. It will be appreciated that the mobile application having the user interfaces 5A-5D and the method of FIG. 10 may also be installed/implemented/accessible on other devices such as conventional computers, internet browsers, etc.

The method generally begins at step 1000, and the method proceeds to display a UI and background processing within the mobile application. The series of decision trees can be activated upon starting the method of FIG. 10, and can be activated by selection within a user interface or process executed within the mobile application. Although each decision tree is described in response to activation, it need not be expanded in the order presented in FIG. 10, and may be expanded in multiple different orders. Additionally, a circled "A" indicates a position to loop from and to a position within the illustrated decision tree sequence. Other loops may also be used as needed or desired.

At decision block 1002, if a home button within the UI of the mobile app is selected, the method may proceed to step 1014, where a background image or animation of the golf shot may be displayed within the user interface. Animation may be part or all of a media file created using AMPS 100 or other media processing systems provided herein. In another form, users can tag videos that are presented as background animations on the home screen. Upon displaying the home screen, the method proceeds to step 1016 and obtains local weather data using the mobile application's current location-based weather service. Once the weather conditions are obtained, they may be presented within the mobile app's home screen at step 1018. The method then proceeds to step 1020 and determines whether a new message can be presented in the message area of the home screen. Messages can come from the golf course, other golfers, weather messages, and other forms of content. In other forms, messages may also include notifications from other golfers, notifications from mobile app providers about new course openings, local golf information, links to golf videos or daily or weekly golf videos, and presentations to golfers. can include various other types of media content that can be used. If a new message is available, the method proceeds to step 1022 and displays the new message within the home screen. If the new message is not a new message available, the method proceeds with displaying the home screen without the current message.

If the location icon is selected within the mobile app at decision block 1004, the method proceeds to step 1024 where a map view of the location having the AI-enabled golf course is displayed within the location map of the mobile app. For example, a mobile app can access Google Maps, determine the GPS location of a golf course with AI-enabled technology, and add a camera graphical icon that can be selected within the map view. The method may then proceed to decision step 1026 and detect whether an AI-enabled golf course list view has been selected. If no list view is selected, the map view continues to be presented within the user interface. If list view is selected, the method proceeds to step 1028 and displays a list of available golf courses. The method then proceeds to step 1030 and detects whether a location has been selected. If no location is selected, the method proceeds with displaying the previously selected list view or map view. If a location is selected in step 1030, the method proceeds to step 1032 and displays course details for the AI-enabled golf course. For example, the course details may include the name and location of the course, a website or tee time purchase site, a golf hole description of the hole including yardage, a hole graphic, a drone flyover, or other hole information. In one form, if a hole has one or more competitions, such as a near pin, hole-in-one, longest drive, or other competition, prize amounts for particular holes, competitions, and conditions may be offered. In some examples, two or more golf holes on a course may be competitive, and a list of golf holes and prizes may also be presented within the user interface.

If a check-in or scan icon selection is detected in decision step 1006, the method proceeds to step 1034 and displays a check-in or scan icon for selection by the golfer while at a golf hole with an AI-enabled camera. The method then proceeds to step 1036 and detects whether the QR scan button is selected. If the button is not selected, the method continues at step 1034. If the QR scan button is selected, the method proceeds to step 1040 and creates a session ID for the mobile application and user. For example, the session ID may include the mobile's cell phone identifier, user identifier, date and time, and location. Once the session ID is created, the method proceeds to step 1042 to access the mobile phone's camera and open the viewfinder to allow the user to scan the QR code present on the golf hole. The QR code(R) is presented near the tee box of the hole being played. A QR Code(R) is a unique code generated for a specific hole on a specific golf course at a specific tee box, with an RFID tag embedded underneath to further assist in the authentication of the QR scan. can also be included.

In another form, at decision block 1044, if the golfer scans the golf code, the golf hole's AI-enabled camera captures an image of the individual and processes the image using AI to identify or tag the golfer. be able to. Additionally, the method can add a timestamp to the session ID, and the AI-enabled camera can add a timestamp to the captured image. The method then proceeds to provide a session ID and identify one or more of the golfer, such as clothing color, height, skin color, or various other attributes that can be identified using AI logic. Images tagged with identified objects can be captured. Image data may be used by AI logic and NN to detect golfer characteristics.

Upon scanning the QR code in step 1044, the method proceeds to step 1046 to detect the unique ID within the golf hole's QR code and proceeds to step 1048 to send a message to the AI-enabled camera. to start recording the golfer. Messages can be communicated via session ID, unique ID, player name or ID, date and timestamp, detected AI attributes or characteristics, or various other information that can be used to initiate recording of the golfer. It can also contain other types of data. The method can then proceed to step 1050 and begin a countdown in seconds of time for the user to take a picture. As proposed, AI-enabled cameras are already recording, but providing a countdown would provide golfers with a timetable to start hitting their shots. When the countdown reaches zero, the method proceeds to step 1052 and displays the recorded image with a flashing icon to indicate that the camera is recording the shot. Also, in step 1052, the user interface displays a stop recording icon that allows the user to stop recording the shot when the shot is complete. The method can then proceed to step 1054 and detect whether the camera should stop recording shots. For example, a user can select a stop recording icon to send a message to the AI-enabled camera to stop the user's recording. In another form, the user may forget to select the stop recording icon. If necessary when this occurs, the method may include detecting when the second user starts a new session, and allowing a time interval, such as 1 to 5 minutes, to end the session. can be used. In other forms, the method also uses an AI-enabled camera to detect whether a user is present on the tee box, or a motion sensor to detect whether a user is no longer present on the tee box. be able to. This method can also use GPS in the mobile phone to detect whether the user is walking away from the tee box, and in some forms can use the accelerometer in the mobile device to detect whether the user is walking away from the tee box. It can be detected whether the user is walking or riding a golf cart. Various combinations of the methods described above can be used to detect when a user is present or absent on the tee box. Upon detecting the lack of presence, the method proceeds to step 1054 to stop recording by sending a signal to the AI-enabled camera, and then proceeds to step 1056 to end the recording session.

If the My Shots icon is selected at decision step 1008, the method proceeds to step 1058 and identifies whether new video has been received. If a new video is received, a "new" bubble icon is added to the first image of the video and the method proceeds to step 1060 to present a list of videos to the user in the user interface. In one form, videos may be presented in a list view with the most recent videos at the top of the list. In other forms, the list may be presented after a search or in other forms where it is presented from oldest to newest. In another embodiment, the method may be modified to include group icons that allow the user to view various groups, videos, and message boards for golf shots made. For example, a group may include each individual who had a shot with the user that day. However, other forms may include groups that all may have played the same golf course on that day. In other forms, the group may be a selected group of golfing friends who may be playing various other courses and wish to share videos with the user.

Upon displaying the video list, the method proceeds to step 1062 and detects whether a video has been selected to be viewed. If no video is selected, the method continues at step 1060. If a video is selected, the method proceeds to step 1064 where a video player may be launched to view the selected video. A video player can be a player that resides on a mobile device. In other forms, the video player can be a network-based video player that can be used to play videos on a mobile device. Additionally, the player may include various controls that allow the user to stop, start, pause, scrub, mirror, and download the selected video. You can also use various other actions while watching the video. Additionally, the player does not need to be "activated" until the user selects the play button and can be presented in the user interface with other selectable elements and content as shown in FIG. 5C.

Upon launching the video player, the method may proceed to step 1066 and detect whether a share icon has been selected. For example, a share icon can activate a list of destinations that can be selected to send or share the video. The destination may include any app available on the user's mobile device in shared mode, such as Facebook, Instagram, Twitter, Snapchat, Pinterest , YouTube, the current app, or other apps as needed or desired. However, it is not limited to these. Destinations may also include saving the app locally on the mobile device or using a cloud service for storing videos and photos. The method may also include presenting a "Watch My Video" selector, a "Copy Video" selector, a "Copy Link" selector, and a delete selector for deleting the video. At block 1068, the method may also display a "Share with Pros" icon in the user interface. The "Share with Pros" icon allows the user to select a local golf professional whose course they would like to share their video with. For example, the video can include the location ID where the video was taken and can be shared with local pros at that golf course to obtain golf advice on the video.

At block 1070, a share selection is detected and the method proceeds to step 1072 to detect whether the "Share with Pros" icon has been selected. If the "Share with Pros" icon is not selected, the method proceeds to step 1080 to identify the selected destination and share the link to the video with the selected destination. In one form, the method provides default text for videos such as "Look at my hole-in-one!", "Here's my shot from Pebble Beach!", "With my kids on TopGolf!!!", or Various other messages can be added that can be created as defaults based on the location where the video was taken. In other forms, users can provide their own messages to add to the video link and can send the link to the desired destination.

If the user selects to share with professionals at step 1072, the method proceeds to step 1074 and displays a list of local professionals for the course where the video was shot. For example, a golf course may have multiple pros, and a list of each pro for that course may be presented. In other forms, the method could be modified to only present a list of professionals who may be on the course that day, or who may want to be part of providing tips to golfers. In other forms, the Pro may not be present, the "Share with Pros" icon may not be presented within the user interface, or an empty list may appear within the user interface with "Come back soon!" or similar May be presented with a message. If available, if the user selects a pro, the method proceeds to step 1076 to detect which pro to share with, and then proceeds to step 1078 to send the link of the video to the selected pro. The link can be sent via text message, email, in-app message, notification, or various other communications, and includes the message "Jon Lux has shared a video and would like a free tip!" ” or various other messages that may be modified or added. In one form, the message can be sent as a text message that may or may not include the sender's and/or recipient's actual mobile phone number. This method can be modified by the user or professional to prevent the mobile phone number from being displayed as part of the text message. The method can also be used for email, app messaging, notifications, or various other forms of communication.

If the profile icon is selected in step 1010, the method proceeds to step 1080 and displays the account icon and proceeds to block 1082 to display the user's profile icon. If the account icon is selected at step 1084, the method proceeds to step 1086 to display the username and password section, and then proceeds to step 1088 to display the payment information section. The method can then proceed to step 1090, where if the user selects a section to modify, the user can modify the selected information. For example, a user may enter a new username, password, email address, privacy settings, or various other types of account information. In one form, the method may also provide clause links to clauses that the user can view or access. According to another aspect, the user can add payment information as part of the account information. For example, payment information may include traditional payments such as credit card information, but may also include other payments such as Venmo, PayPal, Bitcoin, or various other payment methods. Payment methods can be used to pay for rounds of golf, competitions or games such as near pin, hole-in-one, longest drive, competition, etc. scheduled via the mobile app. Payments can also be used to pay individual or group bets that can be played on a golf course between the user and other users. If the account is modified in step 1090, the method proceeds to step 1092 where the new account information can be verified and saved.

If the account section is not selected at step 1084, the method may proceed to step 1086 and detect whether the profile section is selected. If no profile section is selected, the method may proceed to block 1080. If the profile section is selected at step 1086, the method may proceed to block 1094 and display the user's player profile. The player profile includes the player image or photo, player name which may be different from the username in the account section, date of birth or year, handicap, number of golf games played per year, pro tees, men's It can include your favorite tees such as regular, senior tee, junior tee, lady tee, or other tees. The player profile can also include a "What's in the Bag" section that can include which balls the player wants to use and the names and types of clubs, putters, and wedges the golfer is using. For example, golfers may use the Callaway driver, Titleist Hybrid, Mizuno irons, Volkey wedges (52 degrees and 60 degrees), and Scotty Cameron putters. Various manufacturers may be presented to the golfer when setting up a player profile. Some or all of the player profile information can be added as media information to videos created for each user. Additionally, player profile information is stored in a database and can be used to discover information about each player that can be used to market new products and services to the player according to the player profile. In this way, the database can be used to introduce new products and services to users that can help players improve their games and can also serve as a platform for product and service providers to market. I can let you know. Upon changing the player profile, the method proceeds to step 1098 and updates the profile. In one example, the method can be modified to allow a user to send a new profile share to a selected destination if the user updates a portion of his or her profile. For example, a user may want to share that their handicap has changed or that they just bought a new driver or putter. Various elements of a player profile can be modified and shared as needed or desired.

If a new video is received at step 1012, the method proceeds to step 1001 and sends a message to the user's mobile device. The message can be a text message, an in-app message, a notification, an email, a messenger app text, or various ways to message that a new video is available for viewing. The method may also proceed to step 1003, where a badge associated with the mobile app may be changed to indicate that a new video is available. For example, the application name and logo can be updated to display the number of new videos available within the mobile application. In another form, the latest videos can be added as links to the mobile app and an in-app icon, such as the My Videos icon or the My Shots icon, can be updated with the number of new videos. Within the My Videos or Shots section, a "new" bubble reference may be presented as a partial overlay to the video image of the new video. According to another aspect, step 1012 may be modified to include or add messages. Using this method, a message that a new post or video has been uploaded can be sent to one or more groups within the mobile app. For example, if a user is included in a group share on a mobile app, sending a message of one or more users' available videos to other users in the group to indicate that the video is available. Can be done. Group message availability can also be added to the app icon or My Shots icon as a separate bubble icon with a different color and position on the icon. In this way, golfers in a group can communicate messages and videos to each other about videos, shots, competitions, or other messages without having to use a third-party messaging platform, thereby improving the overall The best golf experience can be kept within the same application on your mobile device.

FIG. 11 shows a block diagram illustrating a multi-view AI compatible golf hole according to one aspect of the present disclosure. A multi-view AI-enabled golf hole (MAIG hole), indicated generally at 1100, includes a tee box 1102 with a plurality of tees 1104 and a green 1106 with a hole 1108 that holds a pin 1110 having a pin height 1112. The tee box 1102 includes a first tee box AI compatible camera (TCAM1) 1114, a second tee box AI compatible camera (TCAM2) 1116, and a third tee box AI compatible camera (TCAM3) 1118. MAIG hall 1100 also includes a tee box radar unit 1120 located near tee box 1102. The green 1106 also includes a first greenside AI-compatible camera (GCAM1) 1122, a second greenside AI-compatible camera (GCAM2) 1124, and a third greenside AI-compatible camera (GCAM3) arranged around the green 1106. Contains 1126. Tee box 1102 also includes a tee side microphone 1128 and green 1106 also includes a green side microphone 1130. MAIG hole 1100 also includes a second radar unit 1132 located remotely from tee box 1102 and may include one or more sensor arrays to detect movement on MAIG hole 1100. Tee box 1102 also includes a QR golf code 1146 on one or more of the plurality of tees 1104.

The MAIG hall 1100 also includes a communication interface 1134 that connects various components of the MAIG hall 1100 to a remote media system (RMS) 1136 having AI golf logic 1148. MAIG hall 1100 further includes a golf course power (GCP) source 1138 configured to power various portions of MAIG hall 1100. RMS 1136 is configured to communicate with a network media processing and management service (NMS) 1140 that is configured to process video recorded and uploaded to NMS 1140. NMS 1140 is configured to communicate with one or more destinations 1142 operable to receive digital media created using MAIG hall 1100 and NMS 1140. Also shown in FIG. 11 is a mobile device 1144 operable for use with MAIG Hall 1100.

According to another aspect, TCAMS 1-3 (1114, 1116, 1118) and GCAMS 1-3 (1122, 1124, 1126) may be installed and calibrated in MAIG hall 1100 from time to time. For example, each camera can be installed using survey and GPS data to capture the exact location and overall height of each installation. For example, some cameras may be placed higher than others depending on the topology of MAIG hall 1100. By capturing the exact location of each camera, the distance between each camera can be determined, and the image data can be used to determine the location of various objects detected within the images or videos captured by each camera. can be triangulated. In some forms, one or more cameras may include built-in GPS functionality to assist in locating the coordinates of the cameras installed on the MAIG hall 1100. By having a specific position of each camera, object distance measurement can be achieved. For example, GCAM1 1122 and GCAM3 1126 record the hole 1108, pin 1110, pin height 1112, tee 1104, the golfer's position at the time of play, the distance to hole 1108, the distance the ball traveled after hitting it, and the distance it landed on green 1106. It can later be used to triangulate the distance the ball can be in the hole 1108, or various other distances to areas or objects on the MAIG hole 1100. Other cameras may also be used. Additionally, various locations on and around the green 1106 can be triangulated to create a virtual grid or map of the area of the green 1106. MAIG holes 1100 (including various grass cuts, fairways, first cuts, rough cuts, fringe, sand, water, etc.) are mapped using an AI-enabled camera that can be used to identify objects within the image frame. , efficient distance calculations can be created and used while playing MAIG Hole 1100.

According to further aspects, MAIG hall 1100 can include a daily calibration routine that can be managed by RMS 1136 or NMS 1140. For example, depending on environmental conditions, the optical view performance may change from time to time and the camera focus may drift slightly. This drift can result in measurement errors in the distances of objects within the MAIG hole 1100. Thus, during initialization, a fiducial with a certain height can be provided. The reference may be a temporary reference such as a measuring stick or a surveyor's pole. In other forms, the pole height can be marked for each of the cameras (not explicitly shown) and used as a reference for daily calibration or when image capture quality may vary. . In other forms, the pin height can be used as a reference to determine the specific height used to calibrate each camera.

In other forms, each of the cameras can be calibrated based on optical or digital zoom levels. For example, if GCAM1 1122 includes 10x optical zoom capability, GCAM1 1122 may be set to a series of zoom levels (eg, 1X, 2X, 5X, 10X, etc.) and calibrated using a reference object. In this way, the overall size of the reference object can be stored within each camera or RMS 1134 and used to calculate distance. In another form, it is possible to determine the number of pixels present at the zoom level of the reference object, and when the zoom level of the camera changes, the number of pixels changes for each zoom level, determining the distance of the object. can be memorized and used later. For example, at a 1x zoom level, the number of pixels captured by the reference object may be 1,000 pixels. At a 5x zoom level, the number of pixels can increase to 5,000. Although described as a 1:5 mapping, it should be understood that the number of pixels may vary based on camera type, lens type, temperature, error in lens travel distance during focusing, etc. Various other techniques as needed to calibrate GCAMS 1-3 (1122, 1124, 1126) and TCAMS 1-3 (1114, 1116, 1118) or to enhance optical image capture and distance accuracy can also be expanded.

According to another aspect, MAIG hall 1100 also includes a tee box radar unit 1120 and a second radar unit 1132. Each radar unit may be coupled to RMS 1134 for storing radar data detected by each radar unit. In some cases, each radar unit can store captured data and communicate the captured data when RMS 1134 requests transmission of the data. The radar data may include time-stamped data that may be synchronized with captured video of the MAIG hall 1100. According to one form, each radar can be used to find new daily pin locations and statistics or data for moving objects, such as golf balls in play. Further, radar data can be combined with AI golf logic 1148 to identify the position/velocity of golf objects and objects present or located on MAIG hole 1100.

According to another aspect, MAIG hall 1100 can record multiple player shots from multiple viewpoints or angles. For example, TCAMs 1-3 (1114, 1116, 1118) can be used to record the exit ball flight of a golfer teeing off for the first time. Additionally, while the ball is in flight, one or more greenside cameras GCAM1-3 (1122, 1124, 1126) can record the flight of the ball, while another greenside camera The ball may be recorded as it approaches and lands on the green 1106. In this way, multi-view videos can be created, where multiple segments of a shot can be presented and combined into the user's final video. For example, each video can be created for a particular golfer and communicated to NMS 1140 for processing. Each video may have a unique session ID created during the recording of the video segment for the golfer, and the NMS 1140 may combine the videos into a single video of the shot. In other forms, MAIG 1100 may also be used to create a split-screen view of a tee shot by a golfer. For example, if a right-handed golfer is teeing off, TCAM1 1114 can record from behind the tee box 1102 or on the line, and TCAM2 1116 can be used to record the front view of the golfer's shot. Can be done. Each of the videos, once synchronized and processed into a final video by the NMS 1140, can be presented such that the entire video is presented on one side of the final video and the front view video is presented on the other side. . In this way, the golfer receives both views in a single video.

According to another aspect, MAIG hole 1100 may use a single camera to track the play of multiple golfers playing MAIG hole 1100 together. For example, two sets of four golfers may approach the MAIG hole 1100 when playing a round of golf. Each golfer can scan the QR golf code 1146 to create a session and take their own shot from the tee box 1102 when it is their turn. When the first golfer tees out, the RMS 1136 using one of TCAMs 1-3 (1114, 1116, 1118) and AI logic 1148 identifies the golfer who scanned the QR golf code 1146. Upon scanning the QR golf code 1146, image data for a particular golfer may be captured and stored for subsequent use and processing. After each golfer scans the QR golf code 1146, a unique session ID is created and each golfer's unique aspects are detected at the RMS 1136 and AI logic 1148. After each golfer hits the first shot and approaches the ball, the RMS 1136 can assign a camera to record each golfer's remaining shots. For example, golfer #1 may be hitting the back of the green 1106. Therefore, GCAM1 1122 can be assigned to record golfer #1. Additionally, if Golfer #2 hits a golf ball to the right of the green 1106, GCAM2 1124 can be assigned to record Golfer #2. According to a further aspect, if golfer #3 lands the ball in front of the green 1106, the tee box camera may be used to record golfer #3. For example, TCAM2 1116 can be provided as a PTZ camera, as described herein, and can be rotated toward golfer #3 and record the rest of the play accordingly. In this way, multiple players can record their own shots using a "personal camera," and the M AIG Hole 1100 can record each golfer's shots without having to slice the entire video stream into separate segments. Can be recorded on a single video session.

According to a further aspect, NMS 1140 can be used in conjunction with RMS 1136 to create a video of each golfer playing in a group. For example, when a golfer scans a QR golf code 1146 using their mobile device 1144 , a session may be requested by NMS 1140 to allow RMS 1136 to initiate a recording event for that golfer. Golfer ID and AI detection data may be stored by RMS 1136 and/or NMS 1140 for processing that particular golfer's video. Additionally, a camera may be assigned to the golfer based on the detected landing position of the golf ball and may be stored in the user's log file for that session. When the next golfer hits, a new session is created for each golfer who scans the QR golf code 1146 and a unique identifier associated with each video created is obtained. As each golfer scans or checks in, WAIG Hall 1100 records each golfer and communicates each golfer's video from RMS 1136 to NMS 1140 for post-processing of each video. For example, a log file for each identified golfer can be communicated with each video, radar unit data of the shot, including the video, golfer name, hole distance, shot distance, or various other aspects of play. Various aspects can be included. The NMS 1140 can then process each of the videos using the unique ID generated, including the golfer's name, course name, hole number and distance, number of strokes completed, drive or shot length, pin Graphical data can be overlaid on performance data such as distance to distance, and various other forms of hole data. NMS 1140 can also add shot traces to each tee box shot to further enhance each golfer's viewing experience. Thus, a single video stream can be created by a single camera assigned to each golfer and processed by the RMS 1136/1140 as each golfer finishes playing at the WAIG hole 1100. This can improve production efficiency considering each golfer completes the hole at a different time, reduces upload time and video processing requirements, and puts less strain on the overall AIMS supporting WAIG Hole 1100. Become.

Referring now to FIG. 12, a graphical user interface for a golf tournament mobile application is disclosed in accordance with one aspect of the present disclosure. The user interface, shown generally at 1200, can be used, in whole or in part, with mobile applications such as those shown generally in FIGS. 5A-5D. User interface 1200 may include a competition golf course map view 1202, a golf course list view 1212, a golf course description 1224, a golf hole view 1234, and a golf hole competition reservation view 1240.

According to one aspect, the competition golf course map view 1202 includes a course guide tab selector 1204, a prize selector 1206, a prize icon indicated generally at 1208, and a mobile app user current location icon 1210. Golf course map view 1202 provides a visual indication of where a user can conduct competitive golf competitions. Each of the prize icons 1208 has a prize dollar amount integrated as part of each icon for each course to allow the user to have a visual indication of where the highest prize competition may be located. include. Each prize icon can be updated as follows. Golf course map view 1202 also includes a prize selector 1206 for displaying courses with and without competitions available. When a user detects prize selector 1206, a user interface, such as map 530 of course 532 in FIG. 5A, may be displayed.

According to one aspect, the user may also select list view tab 1214 to display golf course list view 1212. Golf course list view 1212 can include sorting by selector 1216 that can be used to display a list of golf courses, shown generally at 1218. List 1218 may include golf courses 1220 sorted and displayed by selector 1216, with one or more golf courses 1220 having a particular prize value for the competition being played at each of the courses in list 1218. The winning amount 1220 may be included. Listing 1218 may also display courses that may not be hosting golf competitions, but can still provide media recording services as described herein. According to one aspect, sorting by selector 1216 may allow the user to sort by distance to the golf course and in other forms, including prize money from highest to lowest, competition type, private or public. You can sort by competitions, charity competitions, or other forms of competitions that may be available to users of the Competitive Golf Mobile App. In one form, the list 1218 need not be limited to a particular region, such as South Carolina, but may display prizes across regions such as the United States, Canada, and Ireland. User interface 1200 may also include a filter feature that allows the user to filter based on the types of competitions that may occur. For example, a user may only wish to play hole-in-one competitions, sort 1216 and filter by game, hole-in-ones (not explicitly shown), list 1212 of specific prizes by game, or map 1202 view can be displayed.

According to one aspect, when a user selects a course using icon 1208 or course 1220, a golf course description 1224 may be displayed, including golf course name and location 1226, hole description 1228 of the golf hole with competition , tee times and website links 1230, and winning amounts 1232 and descriptions of the games being played in the hole. In some forms, the user can navigate through the golf course description 1224 to view a layout 1236 of golf holes with competitions and prize amounts 1232. Once the user selects the prize amount 1232, a golf hole competition reservation view 1240 may be displayed to the user to allow the user to play with the particular competition and purchase cost. For example, golf hole competition reservation view 1240 may include competition prize amount 1242, golf course name and hole number 1244, current purchase amount 1246, and competition hole and tee descriptions 1248. A tee disclaimer 1250 is provided below the hole and tee description 1248. Before the user can use "Purchase" 1252 to make a purchase to play in a competition, the user must agree to terms 1256 using terms check mark 1254. For example, the terms may include that the person is old enough to play the game, that the player is not a professional golfer, and that the player agrees to pay taxes on the winnings. In another form, the provisions may be regionally bounded based on the location of the competition being played. For example, a hole-in-one competition may be legal in Florida but illegal in South Carolina. Therefore, the terms can be modified to only allow terms based on the region and type of competition that the user may be purchasing. Due to the state-by-state nature of various laws, mobile applications that use region-based provisions may be accessed by users, allowing for real-time updates of provisions based on the user's location, as explained in further detail below. , provides mobile app providers with an advantageous way to present the terms of a golf competition that can be updated within a cloud service. Once the user confirms the clause check mark 1254, the purchase icon 1252 may be used to pay for admission. Payments may be in the form of mobile payment services that may be set up using payment services such as Apple Pay, Venmo, or other mobile payments. In another form, payment can be set up using a user profile, such as account information 522 in FIG. 5A, where the user can enter credit card information (not explicitly shown) and purchase Payments for can be automated within the mobile app.

According to another aspect, when a user scans a QR code to check in and play a hole, the prize amount 1242 may be displayed to give the golfer the option to compete before hitting the shot. can. For example, when a user scans a golf code using a QR scan, such as QR code 548 in FIG. 5B, a user interface 1240 is displayed to the user to allow the user to participate in daily competitions. be able to. Users can therefore wait until they actually play the holes they have purchased in a competition, and use QR codes and location detection to find out which holes are being played, purchases, as well as terms specific to the hole being played.

FIG. 13 illustrates a block diagram of a method for providing autonomous golf competitions within a mobile application according to one aspect of the present disclosure. The method can be used to output a user interface, such as user interface 1200 shown in FIG. 12, or any other user interface, such as a mobile phone, tablet, smart watch, golf cart, pull cart, push It can be provided within an application that can be used in whole or in part on a cart, a powered "follower" cart, a laptop computer, or any other mobile device. It will be appreciated that a mobile application having the user interface 1200 and the method of FIG. 13 may also be installed/implemented/accessible on other devices such as conventional computers, Internet browsers, and the like.

The method generally begins at step 1300, and the method proceeds to display a UI and background processing within the mobile application. The series of decision trees can be activated upon initiating the method of FIG. 13, and can be activated by selection within a user interface or process executed within the mobile application. Although each decision tree is described in response to activation, it need not be expanded in the order presented in FIG. 13 and may be expanded in multiple different orders. Additionally, the circled "A" indicates the position of looping "from" and "to" the illustrated decision tree sequence. Other loops can also be used as needed or desired.

According to one aspect, if a map view is selected at decision step 1302, the method proceeds to block 1312 and displays a map within the user interface that includes a location where the AI-enabled golf course is located. For example, the method can determine the user's current location and access a database that stores a list of golf courses with particular GPS coordinates. During step 1312, the method may determine which golf courses are within a particular distance (e.g., 5 miles, 10 miles, 50 miles, etc.) and display the courses using icons on the map. can. The method may then proceed to decision step 1314 and determine whether any of the displayed golf courses have competitions available. Competitions can include various skill-based golf competitions with monetary prizes for participants, including, but not limited to, near pin (C2P), hole-in-one (HIO), longest drive, first birdie, first eagle. , or other playable games including on-course competitions, or any combination thereof. Additionally, a golf course may also include multiple competitions at different golf holes.

If a competition is not available, the map will be displayed with courses that only have AI-enabled features. If a competition is available, the method proceeds to step 1316 and displays a "Prizes Only" selector that allows the user to view only golf courses with prizes in the competition. This allows the user to quickly view available competitions. If the user does not want to watch the competition, the method proceeds with displaying a map with AI-enabled courses. If the user selects the prize selector at decision step 1318, the method proceeds to step 1320 to identify a course with a prize and then to step 1322 to identify a prize amount. For example, HIO competitions may have higher prize money than C2P competitions and may be displayed accordingly. Additionally, each prize can change daily based on no winners the previous day or the course or service provider elects to fund a higher prize. Once the prize is determined, the method proceeds to step 1324 and displays the prize amount in an icon located on the map where the course is located. In this way, the user can get a quick view of the prize-winning course within a single user interface to where the user may be located. User interface 1202 of FIG. 12 illustrates a map view with prizes on a golf course.

At decision step 1304, a list view may be created and presented within the user interface, and proceeding to step 1326, a geographic location in which the user or mobile device may be located may be determined. As mentioned above, regions can be within the user's radius, but can also be presented based on larger locations or countries. For example, the region may be Texas, Ireland, Canada, or other region. Once the region is identified, the method proceeds to step 1328 and identifies courses within the region. For example, a course may include both an AI-enabled course and an AI-enabled course with a competition. In other forms, a list of courses that do not have AI-enabled technology may be provided for the user to learn about, select, and reserve tee times as needed or desired. Once the AI-enabled courses within the region are determined, the method proceeds to step 1330 and creates a list showing the courses from the closest to the farthest from the user's location. User interface 1212 in FIG. 12 shows an example of a list view. The method then proceeds to decision step 1332 to detect whether a new sort can be selected. For example, if the user wants to sort the list to show the highest or lowest winnings of a competition, the highest or lowest priced purchases, the location closest or farthest to the user, or any other type as needed or desired. There is. If sorting is selected, the method proceeds to step 1334 to sort the list of courses and proceeds to decision step 1336 where the method determines whether the user wishes to filter the list. If sorting is not selected, the user only needs to filter the courses, and at decision step 1336, the user can select a filter to display the list. For example, the user may choose not to display the competition, and only wants to display the course without the competition. In other forms, the user can select, among, but not limited to, various other sorting variables that may be created as needed or desired, such as prize level, competition type, hole difficulty, average number of HIOs achieved this year, etc. You can filter based on a variety of factors including number of HIOs, distance, price paid, available tee times, daily rates, average distance to the pin, and more. Once the filter has been created, the method may proceed to step 1338 and display a list based on the selected filter. Thus, an efficient display of specific types of golf courses and experience offerings can be accessed, filtered, and displayed to the user within the user interface.

Once a course is selected in decision step 1306, the method proceeds to step 1340 to obtain course information for the selected course and proceeds to decision step 1342 to detect whether a competition is available. For example, if the selected course has a competition, the method accesses a database of information describing the competition, proceeds to step 1344 to determine which holes have a competition, and then proceeds to step 1346. You can proceed and decide on the type of competition. The method may then proceed to step 1348 to determine the prize money for the competition, and proceed to step 1350 to determine the purchase cost to play the competition. Upon determining the competition information for the selected course, the method may proceed to step 1352 and display the determined competition information to the user within the user interface. User interface 1224 of FIG. 12 illustrates an example of the user interface provided in step 1352.

If play is selected by the user at decision step 1308, the method proceeds to step 1354 and displays competition information for the selected game. The method then proceeds to step 1356 and detects the user selected course and competition location. For example, if a user selects a course in North Carolina that has competition, state law may limit the types of games that can be played, and the terms of the course and competition may vary based on location. Can be updated. Similarly, if courses and games are selected in Florida, the provisions for conducting competition in Florida at a course may be different than in North Carolina. Accordingly, the method may determine the location of the competition and proceed to step 1358 to update the terms based on the location of the competition being played. The method then proceeds to step 1360 and displays a checkbox in the user interface to allow the user to accept the terms and displays a link for the user to view the location-based terms. can. If the user does not agree to or select the checkbox in step 1362, the method proceeds to display competition information. If the user chooses to agree to the terms at decision step 1362, the method proceeds to step 1364 and enables a purchase icon in the user interface to allow the user to pay for the selected competition or game. It can be done. The "Purchase" or "Purchase" icon is enabled when the user accepts the terms within the terms, but in other forms the "Purchase" icon is enabled when the terms are provided elsewhere in the user interface. can be activated. User interface 1244 in FIG. 12 illustrates a user interface that may be created.

If the user makes a purchase into the competition at decision step 1368, the method proceeds to step 1370 to process the payment. Payments may be in various digital or mobile payment formats as described herein. Once the payment is processed, the method may proceed to step 1372 and detect whether a QR code was previously scanned as an indication that the user is at a golf hole. For example, a user may choose to prepay for a competition before going to the golf course. If so, in step 1372 the method does not initiate user verification. If, at decision step 1372, the user has previously scanned a golf hole QR code, the method proceeds to step 1374, where the user may take his or her shot in the selected competition at the time of verification. You can activate the AI-enabled camera and record the shot.

If the user is located at a golf course and scans a QR code at a particular golf hole in decision step 1310, the method proceeds to decision step 1376 and determines whether the user has already paid for the competition. can be detected. If the user has previously paid for a competition at the hole, the method may proceed to step 1374 and proceed to a countdown to allow the user to take a shot at the hole. A countdown similar to FIG. 5B may be displayed and support recorded video recorded as described herein. At decision step 1376, if the user has scanned but has not paid for the competition, the method may proceed to step 1354 and determine whether to allow the user to play in the competition. If the user does not wish to play in the competition, the method proceeds with allowing the user to record his or her shots as described above. If the user chooses to play in the competition, the method detects that the user agrees to the terms and the payment is processed before the user takes the shot. Thus, the user can choose to pay in advance or upon arrival at the hall, as needed or desired.

Referring now to FIG. 14, a block diagram illustrating a competition-based network media processing and management service is disclosed. A competition-based network media processing and management service (CNMS) is indicated generally at 1400 and may include some or all of the NMS 400 shown in FIG. 4 above. Accordingly, CNMS 1400 is provided to illustrate a competition-based NMS, and may include a network processor 1402 connected to cloud storage and services 1404, which provides a remote media system (RMS) 1450 or digital media. A communication interface 1406 is configured to communicate with any other remote video capture system or device configured to communicate video for processing and creation. CNMS 1 400 also includes an AI-enabled graphics processing engine (GPU) 1408 , a video/image processor 1410 , and AI logic 1412 . Network processor 1402 may have access to various modules or managers to process, manage, and communicate digital media and resources to support one or more competitions at various golf courses. For example, CNMS 1 400 may include a game manager 1414, a distance manager 1416, and a location manager 1418. The CNMS also includes a competition manager 1420, a purchasing manager 1422, and a competition video process and results manager 1424. CNMS 1400 also includes a leaderboard manager 1426, a winner detection manager 1428, a prize manager 1430, a terms manager 1432, and a payment processing manager 1434. CNMS 1400 can also output video received from RMS 1450 as digital media to a digital media-enabled destination 1448 using distribution manager/communications interface 1446. CNMS 1400 also includes an AI logic manager 1440 and update manager 1442 for managing various updates.

According to one aspect, the game manager 1414 can be used to manage games for each golf course using the CNMS 1400 and allow for enabling and disabling competitions on a per-course and per-hole basis. . For example, the game manager 1414 may include, but is not limited to, hole-in-one competitions, near pin competitions, longest drive competitions, lowest score competitions, group competitions, head-to-head competitions, scramble competitions, Ryder Cup competitions. various other types of competitions, games, betting, and/or gambling competitions that may be implemented for golf, including the various available events that may be offered and used locally on a particular golf course. It can include games. Each game can be selected by a game manager interface (not explicitly shown) that is linked to a particular golf course and enabled and disabled as needed. Additionally, the prize or value for each game can be linked to the selected game and can include the date and time each game may be launched. The game can also be started and stopped automatically every day.

According to another aspect, game manager 1414 may also maintain public and private games accessible using CNMS 1400. For example, a public game can be a game developed at a specific location and made available for anyone to play. However, in other embodiments, the CNMS 1400 may be used for private games, which may be invitation-only or private access games. For example, a group of 20 players playing a course may want their own game created and maintained by CNMS 1400. Accordingly, the game manager 1414 can create a private game and provide each invitee with a link to launch the private game to be played on a particular course. As discussed below, a private game may also include a scoreboard, which may be a private scoreboard that may be accessed only by invitees and updated as played.

According to further aspects, game manager 1414 may also maintain competition information that may be used for each game being played. In addition to providing course, game type, and hole information, game manager 1414 may also maintain purchases and winning amounts for each game being played. For example, a daily near pin competition may be set at $100 per day during the week with a $10 purchase and $500 per day on the weekend with a $20 purchase. In other forms, the course may have a hole-in-one competition that increases at a certain level each day until someone achieves a hole-in-one. For example, a hole-in-one costs $10 for a $1000 prize, and the prize can increase by $100 per day until it reaches $10,000, or when a golfer achieves a hole-in-one. Additionally, purchases may increase to higher levels, such as $10 to $20, as the prize increases. Game manager 1414 can automatically increase purchases when certain levels are reached. In yet another form, the game manager 1414 can set the competition to a certain level and, if a golfer does not win, increase the prize money based on the number of participants who played the previous day. For example, if a hole-in-one competition is being held in Florida and is set at an initial level of $5,000, it may take 1,000 shots before a hole-in-one is achieved. Thus, if 100 golfers pay $10 per day to play, the prize money could be as high as $15,000 until a hole-in-one is achieved. Other levels can also be considered, as this is an example of how winnings can be automatically increased based on a player's purchases. For example, a golf course or third party service provider may charge a maintenance fee for providing competitions and may adjust prizes accordingly.

In further embodiments, the game manager 1414 can maintain near pin (C2P) competitions that can vary based on the overall distance to the pin or cup. In traditional C2P competitions, the player closest to the pin wins that day's competition. However, in other forms, the game manager 1414 may allow setting a minimum distance to a pin to qualify as a winner. For example, a minimum distance of 1 foot, 3 feet, 5 feet, etc. can be set for a C2P competition and the values can be set accordingly. The game manager 1414 may also allow for daily prize increases until the golfer comes within the distance detected by the CNMS 1400. In this way, various games can be created and modified as needed or desired.

According to further aspects, CNMS 1400 also includes a distance manager 1416 and a location manager 1418 for presenting active games within a user interface of a mobile app, such as user interface 1200 of FIG. 12. The location manager 1418 can be used to maintain the locations of golf courses and/or holes where competitions may be played, and the distance manager 1418 allows the mobile device to maintain stored competitions and locations with the location manager 1418. Distance from one or more courses can be detected. CNMS 1400 also includes terms and conditions manager 1432 that includes end user license agreements for use of CNMS 1400. Terms manager 1432 also includes a repository of agreements that are maintained and updated on a per golf course basis based on the region or location of the golf course. For example, a hole-in-one competition may not be legal in South Carolina, but may be legal in Nevada. Accordingly, each state's provisions and the available games that may be used by CNMS 1400 and end users may be modified based on whether the games are legal in the region being played. In this manner, clause manager 1432 can provide region-based clause agreements to users of CNMS 1400. Additionally, purchase manager 1422 can be enabled and disabled based on regional location and whether the player has agreed to the terms. For example, purchase manager 1422 may be used to maintain whether a user has paid to play a game on a golf course and enable the user to play the game on that course. Purchasing manager 1422 collaborates with terms manager 1432 to enable payments to be initiated, and may further collaborate with payment processing manager 1434 to process payments using various processing methods. can. For example, a user may use PayPal, Venmo, Apple Pay, or various other payment methods. Users can also pay using credit cards, debit cards, cash cards, etc. The purchase manager 1422 along with the payment processing manager 1434 can determine whether the payment is valid and allow the user to play in a competitive match with users arriving at the hole or course. If the payment is not valid or not paid before the shot is made, the CNMS 1400 does not mark the captured video as a competition video and processes the captured video using, for example, the NMS 400 of FIG. . If the user has paid for the competition, the user's video is marked as a competition video that needs to be processed by the CNMS 1400.

According to one aspect, CNMS 1400 uses video recorded at RMS 1450 and a competition video process and results manager 1424 to process video of a competition to determine which player will win the competition. For example, if a user chooses to play a game presented on the RMS 1450 and a golf course that has an active game or competition, the RMS 1450 and CNMS 1400 may play a game that has been recorded for the user on a particular golf course and hole. Identify the video as a meeting-based video. The video data or information of the recorded video, including the competition video identifier, can be utilized by the CNMS 1400 to determine the outcome of how the golfer performed. Using the RMS 1450 on a particular hole, the golfer can pay for the purchase, and the purchase manager 1422 can send verification to the RMS 1450 that the golfer is participating. RMS 1450 then records the golfer's shots, and once the video is communicated from a particular RMS, purchasing manager and video process and results manager 1424 can confirm that the user is a participant. For example, a particular object in a video image captured during a QR code scan may be identified and tagged by the RMS 14 50 as a competitor. Competitor images can be compared to recorded videos to ensure that they were actually taken by the golfer who paid for the purchase.

According to another aspect, each valid user's competition video may be processed by competition video process and results manager 1424 to determine the results of the captured video. For example, an uploaded competition video may include an information file or metadata with the video identifying the golfer, course, hole, and competition being played. Competition video process and results manager 1424 then processes the video to determine the performance of the shot shot. For example, if the shot was on the longest drive, the competition video process and results manager 1424 may access the sensor data manager 430 or the shot trace manager 426 of FIG. 4 to determine the total distance flown. Competition video process and results manager 1424 can also access multiple AI-enabled camera video recordings to triangulate distances as needed. Once the individual performance results are determined, the scoreboard manager 1426 can be updated and maintained in cloud storage 1404 with a score database for each course and game.

In another form, the competition video process and results manager 1424 may be used to process the competition video to determine whether a hole-in-one was achieved. For example, competition video and information may be marked as being a video recorded shot of a hole-in-one. AI logic 1412 may be accessed to identify golf holes on a golf course and further identify whether the ball will enter the cup of that particular hole on a frame-by-frame basis. As discussed above, AI logic can be created for a particular course and compared to video recorded using video/image processor 1410, GPU 1408, and AI logic 1412. If the shot goes into the cup and remains in the cup, the competition video may be marked as a hole-in-one within the competition video information for that video. Cloud storage 1404 can be updated accordingly.

In a further form, the competition video process and results manager 1424 may be used to process the competition video to determine the distance of the stopped ball from the pin. For example, competition videos and information may be marked as C2P competition videos. The RMS 1450 and CNMS 1400 can be used to calculate the distance of the ball from the pin in various ways described herein. For example, the RMS 1450 can have multiple AI-enabled cameras that can be used to triangulate the distance of the ball from the pin. Once the distance is determined, the scoreboard manager 1426 can update a database in the cloud storage and service 1404 to provide the distance of the ball from the pin. As the day progresses and additional shots are added, the scoreboard manager 1426 can update the database to add new shots to the scoreboard. The scoreboard manager 1426 also updates the sort order of the scoreboard database from shortest to longest (e.g., smallest distance to farthest distance), and the scoreboard manager 1426 updates the scoreboard for a particular course to a particular digital media. It may also be possible to display or output it to the corresponding destination 1448. Thus, near real-time results taken for the competition can be refreshed, updated and displayed at the selected destination. In one form, in public competitions, the full distance may not be preferred to encourage players to participate, and the actual distance is displayed only when the round or day ends. In other forms, the competition may be a morning competition or an afternoon competition. Then, when the next competition starts or the last competition ends, the respective results will be posted. Various other time intervals for display may be provided by scoreboard manager 1426. In another form, if the competition is a private competition, the scoreboard manager 1426 may allow only invitees to view the scoreboard.

Once the competition is complete, the winner detection manager 1428 can access the stored scoreboard to determine which player won the competition. For example, the scoreboard manager 1426 can update the scoreboard database by course and hole, and when a competition ends, the winner detection manager 1428 accesses each game or competition to determine the winner. be able to. Winner detection manager 1428 may initiate a message, such as an email, notification, text, etc., to notify the player that they have won the competition.

According to another aspect, the scoreboard manager 1426 that remembers the user's name allows access to the user's profile information, such as the user profile 422, to provide payments. At the end of each day or competition, prize manager 1430 may determine whether there are any winners and what the prize should be for each winner based on the competition that took place. For example, if the prize for a near pin competition is $1000, the prize manager 1430 can access a payment platform (not explicitly shown) to pay the individual. In one form, the payment may be automatically paid to an account, such as a PayPal or Venmo account. In other forms, the prize manager 1430 can initiate an event in which a paper check payment is sent to the user. Various other forms of payment may be established and used by prize manager 1430.

According to another aspect, prize manager 1430 may also deduct taxes associated with the prize. For example, if the winner is entitled to $10,000, the prize manager 1430 can flag the winner as tax-level and begin withholding taxes on the player before paying the prize to the winner. The winner can then pay the withholding tax amount.

According to further aspects, the prize manager 1430 may also pay parties other than the winner of the competition. For example, if a daily C2P competition is held at a golf course and the overall revenue for play is collected daily, the fees for play will be shared between the golf course and a third party service provider. can do. For example, if the prize is $100 for the winner and a fee of $500 is collected, the prize manager 1430 would award the prize to each of the golfer ($100), the golf course ($200), and the service provider ($200). The share can be calculated for. Thus, prize manager 1430 can automatically distribute revenue without the need for the golf course or third party to maintain, calculate, and distribute prizes. By providing the CNMS 1400 with a variety of ways to automate video recording and competition play, a golfer's overall golf experience can be greatly enhanced while increasing interest in the sport.

FIG. 15 depicts a block diagram of a method of providing autonomous golf competitions according to one aspect of the present disclosure. The method can be used by the AMPS 100 shown in FIG. 1, the CNMS 1400 shown in FIG. 14, or other systems or devices that can use the method of FIG. 15. The method generally begins at step 1500, where invoking the method of FIG. 15 may initiate a series of decision trees, which may be expanded in a number of different orders and sequences. Furthermore, the circled "A" indicates the "from" and "to" positions within the illustrated decision tree sequence. Other loops can also be used as needed or desired. The input required within the method may originate from previously stored data, new data, information input from a user interface, or various combinations thereof. According to one form, the method of FIG. 15, or a portion thereof, may be provided as an application program interface (API) with third party access to the method of FIG. 15.

If at decision step 1502 it is determined to update or enable the competition, the method proceeds to step 1512. Competition updates may occur periodically or at intervals, or may be a single event or competition occurring on a particular day. If a competition is to be activated, the method proceeds to step 1512 to activate the course and to step 1514 to determine which holes are selected for the competition. The method can then proceed to step 1516 and a game can be selected to play on a particular hole. For example, a par 3 can have a near pin selection. The method can then proceed to step 1518 and purchases and awards can be determined. For example, the purchase may be at a specific level, such as $20, or may be automatically selected or increased. Furthermore, although a value can be provided for the prize, in other forms the prize can be fixed or automatically determined. Once the purchases and prizes for a competition are determined, the method proceeds to step 1520 and determines whether another competition or game should be updated or activated for the course. For example, a golf course may want to have a near pin competition and a hole-in-one competition. Each competition can be located in a separate hole, or in one form, the same hole. Upon adding or updating a game, the method may proceed to step 1522 and update course competition data for the golf course. Course competition data or information may include specific details of competitions available for play and for display to a user accessing a user interface configured to access and display competition information. can be used. The method can then proceed to update each golf course competition as needed or desired.

At decision step 1504, a purchase event may be detected. For example, course and competition information can be accessed by golfers using mobile apps, mobile devices, computers, or various other interfaces that can access competitions. According to one form, the user interface of FIG. 12 can be used with the method of FIG. 15. If a purchase event is detected, the method proceeds to step 1524 to determine the selected course and to step 1526 to also determine the holes to be played. The method may then proceed to step 1528 to determine the game to be played and proceed to step 1530 to determine the price. The method can then proceed to step 1532 and determine which terms to agree to. Each information element, including courses, holes, games or competitions, purchase prices, and prizes, may be presented to a user within a user interface (not explicitly shown). The terms may be presented to the user, and in step 1534 the method may detect whether the user has agreed to the terms. If the user does not consent, the method proceeds to step 1504 and repeats or ends. If the user agrees to the terms, the method proceeds to step 1536 and payment processing is enabled. At decision step 1538, if the payment is successful, the method proceeds to enable the user to participate in the competition. If the payment was not successful, the method proceeds to step 1540 to request a new payment method and proceeds to decision step 1542 to detect whether the payment was successful. If the payment is successful, the method proceeds to step 1546 where the competition is enabled for the user. If the payment is not successful again, the method proceeds to step 1544 and disables the purchase option for that user and the competition becomes unavailable to that user until the payment option is resolved.

According to one aspect, if competition video is received in decision step 1508, the method may proceed to step 1560 and begin processing the video. For example, the video and video information may be provided from RMS or other data sources or services, the course is determined in step 1560, the holes are determined in step 1562, and the game or competition is determined in step 1564. . The method can then proceed to step 1566 and detect or identify the player. For example, player profiles or mobile information can be provided with the video, and in other forms, images of the golfer can be verified to identify the player in the video. Various other forms of player identification and detection may also be used, as described herein. Once the player is identified, the method may proceed to decision step 1568 and determine that the video is a valid competition video. In one form, the identified player includes purchase credentials stored in memory for players purchasing to play in a particular competition. Thus, the identified player's purchase credentials can be used to process the video as a competition video. If the video, player, or proof of purchase cannot be verified, the method proceeds to step 1570 and marks the video as an invalid competition video and proceeds to step 1572 to indicate that an invalid video was submitted. The course manager or service provider may be notified. In other forms, the method may proceed to process the video for the player as non-competition-based video and distribute the video to the end user. In this way, the method can be used to process only verified videos, thereby reducing the possibility that non-players gain access to games or competitions to which they are not entitled. . If the video is verified as a competition video in step 1568, the method may proceed to step 1574 and process the video based on the game being played as described herein. The method can then proceed to step 1576 and update the competition scoreboard accordingly.

At decision step 1510, the method may determine whether a prize needs to be provided and proceeds to step 1578. For example, if a daily competition is being held, at the end of the day, the method may proceed to step 1578 to identify the course, step 1580 to identify the game, and step 1582 to determine the winner. For example, a scoreboard for a particular game and a particular course can be maintained in a database, and at the end of the day, the scoreboard for that game can be accessed to determine who the winner is. In some forms, there may be more than one winner depending on the competition being played, and multiple winners may be identified. Once the winners are determined, the method proceeds to step 1584 and determines a prize for one or more winners. For example, if only one winner occurs in a competition, that winner receives all prize money. However, if two people win, the proceeds may be split between the winners. In other forms, each winner may earn the full value. Once a payout is determined, the method proceeds to step 1586 where a payout to the winner may begin. The method can then proceed to step 1588, and if a payment is required to the other player or third party, the method proceeds to initiate the payment. The method can then proceed to step 1590 and repeat at 1578 to determine whether another competition is to be processed and processed accordingly.

It will be appreciated that various other additional method steps may be included in the method described above or the method described above may be modified according to the features and functionality of the system described above. It will be appreciated that such aspects and embodiments are more than abstract concepts implemented by a computer or other controller. The above aspects are performed automatically based on various inputs that cannot be easily accessed or determined, and the resulting final product could not otherwise be provided in the same automatic manner.

Although only some exemplary embodiments have been described in detail above, those skilled in the art will appreciate that many exemplary embodiments can be modified without departing substantially from the novel teachings and advantages of the embodiments of the present disclosure. It will be readily understood that modifications are possible. Accordingly, all such modifications are intended to be included within the scope of the embodiments of this disclosure as defined in the appended claims. In the claims, means-plus-function clauses are intended to encompass structures described herein as performing the recited functions, as well as structural equivalents, as well as equivalent structures. There is.

Not all of the activities mentioned above in the general description or examples may be required, some of the particular activities may not be required, and one or more further activities in addition to those described may be required. Note that may also be performed. Furthermore, the order in which activities are listed is not necessarily the order in which they are performed.

The specification and illustration of embodiments described herein is intended to provide a general understanding of the structure of various embodiments. The specification and examples are not intended to serve as an exhaustive or comprehensive description of all elements and features of devices and systems employing the structures or methods described herein. Many other embodiments will be apparent to those skilled in the art upon reviewing this disclosure. Other embodiments may be used and derived from this disclosure, so that structural substitutions, logical substitutions, or other changes may be made without departing from the scope of this disclosure. Accordingly, this disclosure should be considered illustrative rather than restrictive.

Certain features that are, for clarity, described in this specification in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features that are, for brevity, described in the context of a single embodiment, may also be provided separately or in any subcombination. Further, references to values stated in ranges include each and every value within that range. Advantages, other advantages, and solutions to problems are described above with respect to specific embodiments. However, any benefit, advantage, solution to a problem, and any feature(s) that may occur or make any benefit, advantage, or solution more prominent may be of interest to any or all of the claims. should not be construed as a necessary, necessary, or essential feature.

The subject matter disclosed above is to be considered illustrative rather than limiting, and the appended claims are intended to cover any and all such modifications, enhancements, and other implementations that fall within the scope of this invention. It is intended to cover all forms. Therefore, to the fullest extent permitted by law, the scope of the invention should be determined by the broadest permissible interpretation of the following claims and their equivalents, and the foregoing detailed description shall not be restricted or limited by.

Although only some exemplary embodiments have been described in detail above, those skilled in the art will appreciate that many exemplary embodiments can be modified without departing substantially from the novel teachings and advantages of the embodiments of the present disclosure. It will be readily understood that modifications are possible. Accordingly, all such modifications are intended to be included within the scope of the embodiments of this disclosure as defined in the appended claims. In the claims, means-plus-function clauses are intended to encompass structures described herein as performing the recited functions, as well as structural equivalents, as well as equivalent structures. There is.

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