WO2018081605A1 - Predictive player tracking in virtual or augmented reality sports - Google Patents

Abstract

Predictive player tracking and user notification in live virtual reality presentations is provided. In various embodiments, player position data is received for a plurality of players within a playfield. Information related to each of the plurality of players is received. A notification is generated based on the player position data and the player information. The notification is sent to a viewer.

Description

PREDICTIVE PLAYER TRACKING IN VIRTUAL OR AUGMENTED REALITY SPORTS

BACKGROUND

[0001] Embodiments of the present disclosure relate to virtual reality sports, and more specifically, to predictive player tracking and user notification in live virtual or augmented reality presentations.

BRIEF SUMMARY

[0002] According to embodiments of the present disclosure, methods of and computer program products for predictive player tracking in virtual or augmented reality sports are provided. A player position data is received for a plurality of players within a playfield. Information related to each of the plurality of players is received. A notification is generated based on the player position data and the player information. The notification is sent to a viewer.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0003] Fig. 1 depicts a system for predictive player tracking in VR sports according to embodiments of the present disclosure.

[0004] Fig. 2 depicts a system for predictive player tracking in VR sports according to embodiments of the present disclosure.

[0005] Fig. 3 illustrates a method for predictive player tracking in VR sports according to embodiments of the present disclosure.

[0006] Fig. 4 depicts a computing node according to an embodiment of the present invention. DETAILED DESCRIPTION

[0007] Player tracking systems enable real time tracking of the locations of individual players in a live sports video feed. Using such systems, individual players may be labeled in real time within a video stream, and additional artificial views may be constructed based on the player tracking data. For example, a top down view may be provided with a diagrammatic field and player icons based on the player locations detected in the video stream. In additional to video analysis, player tracking may also be provided through the presence of beacons on each player, such as in their helmets. Such beacons may include various low power radio devices or transponders from which a location can be triangulated.

[0008] However, merely providing player tracking does not provide a spectator with the information necessary to know where to look to catch moments of interest. Simply put, it is easy to miss the most interesting moments of a game when viewing live. Accordingly, there is a need for a systems and methods that provide a user with a predictive viewing experience, providing ongoing cues as to where to direct their attention.

[0009] Given player tracking data, the present disclosure provides for automatic real time editorializing of sports content. In some embodiments, live player tracking data is combined with historical data to provide automatically generated cues to a user. Such cues may include textual comments, an audible indicator such as speech or sounds, an indicator to change view, an automatic view change, or any combination thereof. In this way, a viewer may be notified of areas or player of interest on an ongoing basis during a live sports experience.

[0010] Player tracking according to various embodiments of the present disclosure may be provided through virtual reality (VR) or augmented reality (AR) interfaces. For example, user notifications may be provided as part of VR video or as an overlay in an AR interface. In other exemplary embodiments, notifications are provided in an app or web viewer. In this way, useful feedback may be provided to a viewer whether they are viewing a game in person, or remotely through VR, AR, or other means.

[0011] In various embodiments, systems and methods are provided that integrate player tracking analytics within a live spectator experience. As noted above, some embodiments include VR or AR content from the point of view (POV) of the user. In some embodiments, the content is delivered as 3D or 360° video via streaming. This integration provides a viewer with hints specific to the VR experience such as spatial audio, interactive metadata, or visual cues of the point of view that they should turn to next during the video broadcast.

[0012] In various embodiments, immersive content is merged with one or more live video streams. In this way, the user may interact with the metadata during a video stream within the VR experience. In the context of a VR solution, where interactivity is possible, each user can have a radically different experience and each can tailor on the fly what they are shown. In this way, unlike in a more rigid approach, the user in effect collaborates with an editorializing AI to create a more compelling immersive experience. In comparison, giving an editorializing AI complete control of the viewing experience may create a suboptimal viewing experience, as there is no universal standard for interesting events. Although in some embodiments, a portion of a user's view is controlled entirely by automatic processes, providing user control over the overall experience increases the appeal of the overall presentation.

[0013] It will be appreciated that a variety of virtual and augmented reality devices are known in the art. For example, various head-mounted displays providing either immersive video or video overlays are provided by various vendors. Some such devices integrate a smart phone within a headset, the smart phone providing computing and wireless communication resources for each virtual or augmented reality application. Some such devices connect via wired or wireless connection to an external computing node such as a personal computer. Yet other devices may include an integrated computing node, providing some or all of the computing and connectivity required for a given application.

[0014] Virtual or augmented reality displays may be coupled with a variety of motion sensors in order to track a user's motion within a virtual environment. Such motion tracking may be used to navigate within a virtual environment, to manipulate a user's avatar in the virtual environment, or to interact with other objects in the virtual environment. In some devices that integrate a smartphone, head tracking may be provided by sensors integrated in the smartphone, such as an orientation sensor, gyroscope, accelerometer, or geomagnetic field sensor. Sensors may be integrated in a headset, or may be held by a user, or attached to various body parts to provide detailed information on user positioning.

[0015] It will also be appreciated that various embodiment are application to virtual and augmented reality environments in general, including those that are presented without a headset. For example, a magic window implementation of VR or AR uses the display on a handheld device such as a phone as a window into a virtual space. By moving the handheld, by swiping, or by otherwise interacting with the handheld device, the user shifts the field of view of the screen within the virtual environment. A center of a user's field of view can be determined based on the orientation of the virtual window within the virtual space without the need for eye- tracking. However, in devices including eye-tracking, more precision may be obtained.

[0016] Referring now to Fig. 1, a system 100 for predictive player tracking in VR sports is illustrated according to embodiments of the present disclosure. System 100 includes a player tracking module 101, receiving a live data feed 102 and determining the location and identity of each player on a field. In some embodiments, live data feed 102 comprises one or more video feed. In some embodiments, live data feed 102 comprises player telemetry data. In some embodiment, player tracking module 101 comprises a learning system capable of distinguishing the position of individual players from the live data feed 102. In some embodiments, a learning system comprises a neural network trained for identification of players within the frames of a video feed.

[0017] A data store 103 includes various player data. In some embodiments, player data includes player identity as well as tags or attributes . Exemplary attributes include age, distance run, or average sprint speed. Exemplary tags include quantitative or qualitative descriptors such as "speedster" for above average sprint speed, or "loudmouth" for history of aggressive social media posts.

[0018] Based on player tracking 101 and corresponding player data 103, notification module 104 dynamically tracks the activities of players having certain tags or attributes. Based on the activities of individual players, notifications are generated and sent to a viewer 105. As noted above, notification may be in the form of various elements of a VR or AR experience such as visible markers, speech, sounds, or modification of a view in the VR environment. For example, in a VR environment having multiple virtual screens, one or more of those screens may be modified in response to the notification.

[0019] In some embodiment, notification module 104 applies a plurality of predetermined triggers to the incoming location and player data. For example, a trigger may fire upon matching on one or more player tags or attributes and location. The result may include display of a notification or an additional action. For example, a notification may be dispatched to viewer 105 for display to a user, or a video stream may be modified before transmission to a user. [0020] For example, a player who is significantly above her average total miles run per game, may prompt a text alert to a view, "Watch out, this player is unusually tired!" Such a text notification may be coupled with a visual or audible indicator. In another example, a player who has an age attribute of 40 years who comes within 5 meters of another player who is tagged as "speedster" may trigger a notification that says "Watch out for an uneven match up here!" In another example, where five players on the same team are all moving rapidly close to the opposing goal at a rate above 2m/s, multiple interface panels within the VR environment may flash "Imminent goal!"

[0021] It will be appreciated that the above rules are examples, and that a variety of conditional triggers may be defined within systems according to the present disclosure based on player data and location. It will also be appreciated that the actions triggered are also exemplary, and that a variety of visual, textual, audial, or other indicators may be generated in a VR or AR

environment, on a mobile device, or via various event feeds such as RSS or microblogging such as Twitter.

[0022] Referring now to Fig. 2, a system 200 for predictive player tracking in VR sports is illustrated according to embodiments of the present disclosure. Data source 201 includes external data drawn from exogenous sources 202, such as ball tracking systems, player tracking, systems, or other third party sources. Data source 203 includes internal data drawn from internal data sources 204, such as manually editorialized data points, social media aggregation, or manual data insights. Learning system 205 receives data from data sources 201...202 and generates insights relevant to the current game state.

[0023] In some embodiments, a feature vector corresponding to the current game state, including player locations and player data is provided to learning system 205. Based on the input features, learning system 205 generates one or more candidate insights. In some embodiments, the output of learning system 205 is a feature vector that corresponds to notification. In some

embodiments, learning system 205 comprises a SVM. In other embodiments, learning system 205 comprises an artificial neural network. In some embodiments, learning system 205 is pre- trained using retrospective game data and manually generated insights. In some embodiments, generated insights are stored in data store 206. In some embodiments, learning system 205 may be additionally trained through curation of previously generated editorial insights.

[0024] Suitable artificial neural networks include but are not limited to a feedforward neural network, a radial basis function network, a self-organizing map, learning vector quantization, a recurrent neural network, a Hopfield network, a Boltzmann machine, an echo state network, long short term memory, a bi-directional recurrent neural network, a hierarchical recurrent neural network, a stochastic neural network, a modular neural network, an associative neural network, a deep neural network, a deep belief network, a convolutional neural networks, a convolutional deep belief network, a large memory storage and retrieval neural network, a deep Boltzmann machine, a deep stacking network, a tensor deep stacking network, a spike and slab restricted Boltzmann machine, a compound hierarchical-deep model, a deep coding network, a multilayer kernel machine, or a deep Q-network.

[0025] In various exemplary embodiments, player tracking data may include, e.g., speed, location data, or proximity information. Speed may be relative to an object or a person, or may be given relative to the playfield. Location data may be in terms of x,y,z coordinates, a fixed reference (e.g., yards to goal line), or a region of the playfield (e.g., midfield). Proximity may be between players, between a player formation, or relative to alignment on the playfield. [0026] In various exemplary embodiments, player tags may include, e.g., qualitative tags or quantitative tags. Qualitative tags may results to personality, e.g., Loudmouth, Dirty player, Hero, Leader, Underdog, Recent Serious Injury, History of Injuries. Quantitative tags may include, e.g., Age, Ongoing statistics such as distance run this game, number of hits, number of time with the ball, or number of passes, Historical statistics such as distance run on average, number of average hits, player record vs the current team, player record in the current venue, or player record in the current conditions.

[0027] Additional contextual data may include Teams Matchup History, Location Factors, Crowd Metrics, Current Weather, Season-Related Information, Performance in the Current Game Compared to the Season, or additional Contextual Clues such as social media posts (e.g., tweets) or references in web publications.

[0028] Referring now to Fig. 3, a method for predictive player tracking in VR sports is illustrated according to embodiments of the present disclosure. At 301, player position data is received for a plurality of players within a playfield. In some embodiments, the player position data is received at regular intervals during a live game. At 302, information related to each of the plurality of players is received. At 303, a notification is generated based on the player position data and the player information. At 304, the notification is sent to a viewer.

[0029] Referring now to Fig. 4, a schematic of an example of a computing node is shown. Computing node 10 is only one example of a suitable computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, computing node 10 is capable of being implemented and/or performing any of the functionality set forth hereinabove. [0030] In computing node 10 there is a computer system/server 12, which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or

configurations that may be suitable for use with computer system/server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like.

[0031] Computer system/server 12 may be described in the general context of computer system- executable instructions, such as program modules, being executed by a computer system.

Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server 12 may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a

communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.

[0032] As shown in Fig. 4, computer system/server 12 in computing node 10 is shown in the form of a general-purpose computing device. The components of computer system/server 12 may include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including system memory 28 to processor 16. [0033] Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0034] Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12, and it includes both volatile and non-volatile media, removable and non-removable media.

[0035] System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and/or cache memory 32. Computer system/server 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a "hard drive"). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus 18 by one or more data media interfaces. As will be further depicted and described below, memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.

[0036] Program/utility 40, having a set (at least one) of program modules 42, may be stored in memory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules 42 generally carry out the functions and/or methodologies of embodiments of the invention as described herein.

[0037] Computer system/server 12 may also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, etc.; one or more devices that enable a user to interact with computer system/server 12; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server 12 to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces 22. Still yet, computer system/server 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter 20. As depicted, network adapter 20 communicates with the other components of computer system/server 12 via bus 18. It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server 12. Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0038] The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. [0039] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0040] Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.

[0041] Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more

programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.

[0042] Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

[0043] These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

[0044] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0045] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0046] The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

CLAIMS What is claimed is:

1. A method comprising:

receiving player position data for a plurality of players within a playfield;

receiving information related to each of the plurality of players;

generating a notification based on the player position data and the information related to each of the plurality of players;

sending a notification to a viewer.

2. The method of claim 1 , wherein the viewer comprises a virtual reality viewer.

3. The method of claim 1, wherein the player position data is received from a real time player tracking system.

4. The method of claim 1 , wherein the information related to each of the plurality of players comprises player statistics or player attributes.

5. The method of claim 1, wherein generating the notification comprises:

applying one or more predetermined rules to the player position data and the information related to each of the plurality of players.

6. The method of claim 1, wherein generating the notification comprises:

determining proximity between at least two of the plurality of players.

7. The method of claim 1, wherein generating the notification comprises:

providing the player position data and the information related to each of the plurality of players to a trained neural network.

8. The method of claim 1, wherein sending the notification comprises:

adding one or more visual elements to a video stream; and sending the video stream to the viewer.

9. The method of claim 1, wherein sending the notification comprises:

sending a textual notification via a network.

10. The method of claim 1, wherein sending the notification comprises:

sending an indication to the viewer to display a predetermined visual element.

11. The method of claim 1 , wherein sending the notification comprises:

sending an indication to the viewer to play a predetermined audio element.

12. A computer program product for predictive player tracking in VR sports, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:

receiving player position data for a plurality of players within a playfield;

receiving information related to each of the plurality of players;

generating a notification based on the player position data and the information related to each of the plurality of players;

sending a notification to a viewer.

13. The computer program product of claim 12, wherein the viewer comprises a virtual reality viewer.

14. The computer program product of claim 12, wherein the player position data is received from a real time player tracking system.

15. The computer program product of claim 12, wherein the information related to each of the plurality of players comprises player statistics or player attributes.

16. The computer program product of claim 12, wherein generating the notification comprises:

applying one or more predetermined rules to the player position data and the information related to each of the plurality of players.

17. The computer program product of claim 12, wherein generating the notification comprises:

determining proximity between at least two of the plurality of players.

18. The computer program product of claim 12, wherein generating the notification comprises:

providing the player position data and the information related to each of the plurality of players to a trained neural network.

19. The computer program product of claim 12, wherein sending the notification comprises: adding one or more visual elements to a video stream; and

sending the video stream to the viewer.

20. The computer program product of claim 12, wherein sending the notification comprises: sending a textual notification via a network.

21. The computer program product of claim 12, wherein sending the notification comprises: sending an indication to the viewer to display a predetermined visual element.

22. The computer program product of claim 12, wherein sending the notification comprises: sending an indication to the viewer to play a predetermined audio element.

23. A system comprising: a computing node comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor of the computing node to cause the processor to perform a method comprising:

receiving player position data for a plurality of players within a playfield; receiving information related to each of the plurality of players;

generating a notification based on the player position data and the information related to each of the plurality of players;

sending a notification to a viewer.

The system of claim 23, wherein the viewer comprises a virtual reality viewer.

The system of claim 23, wherein the player position data is received from a real time ayer tracking system.

26. The system of claim 23, wherein the information related to each of the plurality of ayers comprises player statistics or player attributes.

The system of claim 23, wherein generating the notification comprises:

applying one or more predetermined rules to the player position data and the information related to each of the plurality of players.

The system of claim 23, wherein generating the notification comprises:

determining proximity between at least two of the plurality of players.

The system of claim 23, wherein generating the notification comprises:

providing the player position data and the information related to each of the plurality of players to a trained neural network.

The system of claim 23, wherein sending the notification comprises:

adding one or more visual elements to a video stream; and sending the video stream to the viewer.

31. The system of claim 23, wherein sending the notification comprises:

sending a textual notification via a network.

32. The system of claim 23, wherein sending the notification comprises:

sending an indication to the viewer to display a predetermined visual element.

33. The system of claim 23, wherein sending the notification comprises:

sending an indication to the viewer to play a predetermined audio element.