Patent Publication Number: US-2022212086-A1

Title: Virtual reality sports training systems and methods

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. Ser. No. 17/087,121 filed Nov. 2, 2020, which is incorporated herein by reference in its entirety; which is a continuation-in-part of U.S. Ser. No. 16/690,501 filed Nov. 21, 2019, now U.S. Pat. No. 10,821,347, which is incorporated herein by reference in its entirety; which is a continuation of U.S. Ser. No. 16/404,313 filed May 6, 2019, now U.S. Pat. No. 10,486,050, which is incorporated herein by reference in its entirety; which is a continuation of U.S. Ser. No. 15/431,630 filed Feb. 13, 2017, which is incorporated herein by reference in its entirety; which claims the benefit of U.S. provisional application 62/294,195, filed Feb. 11, 2016, which is incorporated herein by reference in its entirety, which is also a continuation of U.S. Ser. No. 14/694,770 filed Apr. 23, 2015, which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND OF THE INVENTION 
     Field Of The Invention 
     The present invention relates in general to systems and methods for training athletes. More particularly, the invention is directed to virtual reality simulated sports training systems and methods. 
     Description of the Related Art 
     Virtual reality environments may provide users with simulated experiences of sporting events. Such virtual reality environments may be particularly useful for sports such as American football in which players may experience many repetitions of plays while avoiding the chronic injuries that may otherwise result on real-world practice fields. However, conventional virtual reality sports simulators may not provide meaningful training experiences and feedback of the performance of a player. 
     Accordingly, a need exists to improve the training of players in a virtual reality simulated sporting environment. 
     SUMMARY OF THE INVENTION 
     In one embodiment, a virtual reality projection system is disclosed. The virtual reality projection system comprises: an electronic display configured to project a virtual reality baseball environment shown in a first-person perspective of a user training a batting swing in the virtual reality baseball environment; and a graphics engine module connected to the electronic display, the graphics engine module configured to: generate the virtual reality baseball environment; generate a digitized image of a user selected real-life baseball pitcher, wherein the user-selected real-life baseball pitcher is selected from a plurality of real-life baseball pitcher profiles stored in an electronic database; retrieve from the electronic database, real-life pitching data of the user selected real-life baseball pitcher; display in the virtual reality environment, the digitized image of the user selected real-life baseball pitcher with an appearance replicating the real-life baseball pitcher in real-life from the first-person perspective of the user; display in the virtual reality environment, a pitching sequence by the digitized image of the user selected real-life baseball pitcher, from either a wind-up or a stretch delivery; display in the virtual reality environment, a replicated release of a digital baseball from a digital hand of the digitized image from a release point replicating a pitch thrown by the user selected real-life baseball pitcher, wherein the digital hand is positioned in a three-dimensional space of the virtual reality baseball environment from a location associated with the release point when replicating the replicated release of the digital baseball; and display in the virtual reality environment, the digital baseball disappearing from view of the user after the replicated release and before a digital marker representing a batting area. 
     In another embodiment, a machine readable non-transitory medium storing executable program instructions is disclosed which when executed cause a data processing system to perform a method comprising: generating a virtual reality baseball environment in an electronic display; generating a digitized image of a user selected real-life baseball pitcher, wherein the user-selected real-life baseball pitcher is selected from a plurality of real-life baseball pitcher profiles stored in an electronic database; retrieving from the electronic database, real-life pitching data of the user selected real-life baseball pitcher; displaying in the virtual reality environment, the digitized image of the user selected real-life baseball pitcher with an appearance replicating the real-life baseball pitcher in real-life from the first-person perspective of the user; displaying in the virtual reality environment, a pitching sequence by the digitized image of the user selected real-life baseball pitcher, from either a wind-up or a stretch delivery; and displaying in the virtual reality environment, a replicated release of a digital baseball from the digitized image from a release point based on the real-life pitching data, replicating a real-life pitch thrown by the user selected real-life baseball pitcher; displaying the replicated release of the digital baseball continuing in a simulated trajectory of a thrown virtual pitch, from the release point of the user selected real-life baseball pitcher toward a strike zone adjacent the user in the virtual reality baseball environment; displaying a visible menu of pitch types in the virtual reality environment; registering a user selection of one of the pitch types, wherein the user selection represents a guess by the user of a pitch type of the thrown virtual pitch; and determining whether the user selection matches an actual pitch type of the thrown virtual pitch. 
     In yet another embodiment, a method of simulating a baseball pitcher&#39;s pitch is disclosed. The method comprises: generating a virtual reality baseball environment in an electronic display; generating a digitized image of a baseball pitcher; displaying in the virtual reality environment, a pitching sequence by the digitized image of the baseball pitcher, from either a wind-up or a stretch delivery; displaying in the virtual reality environment, a replicated release of a digital baseball from the digitized image from a release point based on arm positioning viewable during the wind-up or during the stretch delivery of the baseball pitcher, replicating a pitch type thrown by the baseball pitcher, the replicated release of the digital baseball is displayed continuing in a simulated trajectory of a thrown virtual pitch, from the release point of the baseball pitcher toward a strike zone adjacent the user in the virtual reality baseball environment, wherein the replicated release and the simulated trajectory are based on the pitch type; and displaying in the virtual reality environment, the digital baseball disappearing from view during the simulated trajectory and before reaching the strike zone. 
     These and other features and advantages of the invention will become more apparent with a description of preferred embodiments in reference to the associated drawings. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an exemplary flowchart illustrating a method for implementing a virtual reality sports training program. 
         FIG. 2  is an exemplary flowchart illustrating the calculation of the decision and timing scores. 
         FIG. 3  is an exemplary flowchart illustrating the decision scoring for a football quarterback. 
         FIG. 4  is an exemplary flowchart illustrating the timing scoring for a football quarterback. 
         FIG. 5  is a front, perspective view of a user in an immersive virtual reality environment. 
         FIG. 6  is a side, perspective view of a user wearing a virtual reality head-mounted display showing a virtual reality environment. 
         FIG. 7  is a front, perspective view of a simulated environment of a football game and a handheld game controller for the user to interact with the game. 
         FIG. 8  is a front, perspective view of the simulated environment of a football game just before the initiation of a play. 
         FIG. 9  is a front, perspective view of the simulated environment of a football game immediately after the initiation of a play. 
         FIG. 10  is a front, perspective view of the simulated environment of a football game showing the correct decision. 
         FIG. 11  is a front, perspective view of a simulated environment of a football game showing a multiple choice question presented to the user. 
         FIG. 12  is a front, perspective view of a simulated environment of a football game showing the possible areas from which the user may select. 
         FIG. 13  is a front, perspective view of a simulated environment of a football game showing the possible areas from which the user may select in an embodiment. 
         FIG. 14  is a front, perspective view of a simulated environment of a football game showing the possible areas from which the user may select in an embodiment. 
         FIG. 15  is a front, perspective view of a simulated environment of a football game where the user is asked to read the defense. 
         FIG. 16  is a front, perspective view of the simulated environment of a football game showing possible areas of weakness from which a user may select. 
         FIG. 17  is a front, perspective view of the simulated environment of a football game showing offensive player running patterns. 
         FIG. 18  is a front, perspective view of a user selecting the area of weakness in an embodiment. 
         FIG. 19  is a front, perspective view of a user interacting with a virtual reality environment via a virtual pointer. 
         FIG. 20  is a front, perspective view of a user selecting an audio recording in an embodiment. 
         FIG. 21  is a front, perspective view of a user selecting a lesson with the virtual pointer. 
         FIG. 22  is a front, perspective view of a user selecting from multiple choices using the virtual pointer. 
         FIG. 23  is a front, perspective view of a user receiving the score of performance in an embodiment. 
         FIG. 24  is a front view of a playlist menu in one or more embodiments. 
         FIG. 25  is a front view of a football field diagram showing details of a play in one or more embodiments. 
         FIG. 26  is a front, perspective view of a simulated environment of a football game immediately before a play is executed. 
         FIG. 27  is a front, perspective view of a user selecting a football player with the virtual pointer in one or more embodiments. 
         FIG. 28  is a front, perspective view of a user receiving the score of performance in an embodiment. 
         FIG. 29  is a schematic block diagram illustrating the devices for implementing the virtual reality simulated environment of a sporting event. 
         FIG. 30  is an exemplary flowchart showing the process of implementing the virtual reality simulated environment of a sporting event on a smartphone or tablet. 
         FIG. 31  is an exemplary flowchart showing the process of implementing the virtual reality simulated environment of a sporting event on a mobile device. 
         FIG. 32  is an exemplary flowchart showing the process of implementing the virtual reality simulated environment of a sporting event on a larger system. 
         FIG. 33  is a schematic block diagram illustrating a mobile device for implementing the virtual reality simulated environment of a sporting event. 
         FIG. 34  is a stereoscopic front perspective view of a three dimensional panoramic virtual reality environment system simulating a baseball pitch thrown from a digitized avatar of a real-life pitcher, as seen from a baseball batter&#39;s perspective, according to an exemplary embodiment. 
         FIG. 35  is a stereoscopic front perspective view of the system of  FIG. 34  with a user wearing a tracked stereoscopic glasses and swinging a bat at a simulated pitch according to an exemplary embodiment. 
         FIG. 36  is an enlarged view of a digitized avatar of a real-life pitcher within a three dimensional panoramic virtual reality environment system simulating a baseball pitching sequence according to an exemplary embodiment. 
         FIG. 37  is a perspective view displayed inside a head-mounted display, which shows a digitally generated strike zone location box from a batter&#39;s perspective displayed at the end of the pitching sequence of  FIG. 36 , according to an exemplary embodiment. 
         FIG. 38  is a perspective view displayed inside a head-mounted display, which shows a strike or ball decision graphic with countdown timer and the gaze-controlled crosshair according to an exemplary embodiment. 
         FIG. 39  is an illustration of a digitized real-life pitcher performing a pitching sequence and reference points determined in generating a release point in a virtual reality environment according to an exemplary embodiment. 
         FIG. 40  is an illustration of digitized real-life pitcher performing several pitch sequences with different heights in the ball release points, and reference points determined for each pitcher in generating respective release points at arbitrary locations in a virtual reality environment according to an exemplary embodiment. 
         FIG. 41  is a side schematic view illustrating before the alignment of the digitized avatar of a pitcher&#39;s release point and pitch release relative to a position of a user batter according to an exemplary embodiment. 
         FIG. 42  is a side schematic view illustrating after the alignment of the digitized avatar of a pitcher&#39;s release point and pitch release relative to a position of a user batter according to an exemplary embodiment. 
         FIG. 43  is a side schematic view illustrating generating a field background and stadium environment relative to a position of the digitized pitcher&#39;s avatar and the user batter according to an exemplary embodiment. 
         FIG. 44  is a side schematic view illustrating the tracking of a user&#39;s bat swing to determine if a simulated pitch was hit in the system of  FIG. 35 . 
         FIG. 45  shows a top view schematic and a side view schematic of a tracked bat swing to determine if the bat reaches a point of contact of the simulated pitch in a plane that intersects a simulated flight path of the simulated pitched baseball. 
         FIG. 46  shows a top view schematic and a side view schematic of a tracked bat swing that was determined to have hit the simulated pitched baseball. 
         FIG. 47  is a schematic view illustrating two algorithms for determining whether a tracked swing of a baseball makes contact with a simulated baseball pitched in the system of  FIG. 35  according to an exemplary embodiment. 
         FIG. 48  is a flowchart of a method of matching a perspective of a batter user with the generated digitized avatar of a real-life pitcher in a three dimensional virtual reality environment according to an exemplary embodiment. 
         FIG. 49  is a flowchart of a method of simulating a flight path of a simulated pitched baseball from a digitized avatar of a real-life pitcher in a three dimensional virtual reality environment according to an exemplary embodiment. 
         FIG. 50  is a block diagram of a system for generating a three dimensional virtual reality simulation of baseball pitches from digitized avatars of real-life baseball pitchers according to an exemplary embodiment. 
         FIG. 51  is a screenshot of a virtual reality environment displaying a training mode for pitch type identification according to an exemplary embodiment. 
         FIG. 51A  is a flowchart of a process of generating various training mode features in a virtual reality environment according to an exemplary embodiment. 
         FIG. 52  is a screenshot of a virtual reality environment displaying results of a user decision in a training mode for pitch type identification according to an exemplary embodiment. 
         FIG. 53  is a screenshot of a virtual reality environment displaying results of a user decision timing/distance in a training mode for swing decision according to an exemplary embodiment. 
         FIG. 54  is a screenshot of the virtual reality environment of  FIG. 53  with a visible display of results according to an exemplary embodiment. 
         FIG. 55  is a screenshot of a virtual reality environment displaying a strike zone plane, a guessed pitch location, and actual pitch location, and a user pitch type selection according to an exemplary embodiment. 
         FIG. 56  is a screenshot of the virtual reality environment of  FIG. 55  illustrating a user identification of a pitch location in the strike zone plane according to an exemplary embodiment. 
         FIG. 57  is a screenshot of a virtual reality environment displaying a visible menu of characteristics of a thrown virtual pitch and a difference in distance from a user guessed location and an actual pitch location according to an exemplary embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The following preferred embodiments are directed to virtual reality sports training systems and methods. Virtual reality environments provide users with computer-generated virtual objects which create an illusion to the users that they are physically present in the virtual reality environment. Users typically interact with the virtual reality environment by employing some type of device such as headset goggles, glasses, or mobile devices having displays, augmented reality headgear, or through a cave automatic virtual environment (CAVE) immersive virtual reality environment where projectors project images to the walls, ceiling, and floor of a cube-shaped room. 
     In one or more embodiments, a sports training simulated environment is contemplated. While in a virtual reality environment, a user views a simulated sporting event. In an embodiment, a user acting as a football quarterback in the virtual reality environment may see a pre-snap formation of computer-generated defensive and offensive football players. In an embodiment, the virtual football is snapped, the play is initiated, and the offensive and defensive players move accordingly. The user sees several of his virtual teammates cross the field, and the user must decide among his teammates to whom he should throw the ball. The user makes his selection, and the sports training simulated environment scores the user&#39;s decisions. Scores may be based on timing (i.e., how quickly the user decides) and/or on selection (i.e., did the user select the correct player). In one or more embodiments, the user may repeat the virtual play or may move on to additional plays. The scores are stored in a cloud based storage. The user&#39;s progress (or regression) over time will be tracked and monitored. The user can access the scores and data via a personalized dashboard in either a webpage or mobile application. 
     In one or more embodiments, the user may be queried on other aspects of a simulated sporting event. For example, a user acting as a virtual quarterback may be asked to read a defense and identify areas of weakness against a play. In one or more embodiments, multiple possible answers are presented to the user, and the user selects the answer he believes is correct. 
     In one or more embodiments, a comprehensive virtual reality sports training environment is contemplated. A coach may develop customized plays for his team. The players of the team then interact individually with the virtual reality simulated sporting event and have their performances scored. The scores of the players may then be interpreted and reviewed by the coach. 
     One or more embodiments provide a means for improving athlete decision-making. Athletes in a virtual environment may experience an increased number of meaningful play repetitions without the risk of injury. Such environments may maximize effective practice time for users, and help develop better players with improved decision-making skills. 
     Embodiments described herein refer to virtual reality simulated environments. However, it shall be understood that one or more embodiments may employ augmented reality environments comprising both virtual and real world objects. As used herein and as is commonly known in the art, the terms “simulated environments,” “simulated,” “virtual,” “augmented,” and “virtual reality environment” may refer to environments or video displays comprising computer-generated virtual objects or computer-generated virtual objects that are added to a display of a real scene, and may include computer-generated icons, images, virtual objects, text, or photographs. Reference made herein to a mobile device is for illustration purposes only and shall not be deemed limiting. Mobile device may be any electronic computing device, including handheld computers, smart phones, tablets, laptop computers, smart devices, GPS navigation units, or personal digital assistants for example. 
     Embodiments described herein make reference to a training systems and methods for American football; however, it shall be understood that one or more embodiments may provide training systems and methods for other sports including, but not limited to, soccer, baseball, hockey, basketball, rugby, cricket, and handball for example. As used herein and as is commonly known in the art, a “play” is a plan or action for one or more players to advance the team in the sporting event. Embodiments described herein may employ head mounted displays or immersive systems as specific examples of virtual reality environments. It shall be understood that embodiments may employ head mounted displays, immersive systems, mobile devices, projection systems, or other forms of simulated environment displays. 
       FIG. 1  is an exemplary flowchart illustrating a machine-implemented method  101  for implementing a virtual reality sports training program. The process begins with a 2 dimensional (“2D”) play editor program (step  110 ) in which a coach or another person may either choose an existing simulated play to modify (step  112 ) or else create a completely new simulated play from scratch (step  114 ). The simulated play may be created by a second user such as a coach, where the simulated play defines the pre-determined location of the simulated players and the movements of the simulated players during the play. 
     An existing play may be modified by adjusting player attributes from an existing play (step  116 ). A new play may be created by assigning a player&#39;s speed, animation, stance, and other attributes for a given play (step  118 ). The simulated sports training environment provides a simulated environment of a sporting event to a user by one or more computing devices, where the simulated environment depicting the sporting event appears to be in the immediate physical surroundings of the user. The simulated sports training environment generates simulated players in the video display of the sporting event, where each of the simulated players is located in a pre-determined location. In one or more embodiments, the simulated sports training environment initiates a simulated play for a period of time, where one or more simulated players move in response to the play. Assignment of ball movement throughout the play determines the correct answer in the “Challenge mode” (step  120 ). 
     Multiple viewing modes are possible to present the created play (step  122 ). A 3D viewing mode supports video game visualization and stereoscopic viewing of the play created (step  124 ). In a helmet mode, the view of the play is from the individual player&#39;s helmet view point (step  126 ). In a free decision mode, the user may choose the navigation throughout the environment (step  128 ). All of these modes may be viewed in any virtual reality system (step  134 ). 
     The user may be faced with a challenge mode (step  130 ) where the user&#39;s interactions with the play are monitored and scored (step  132 ). In one or more embodiments, the sports training environment presents a question or query to the user, receives a response from the user, and scores the response. The ball movement is assigned to a player throughout a play to signify the player who has possession of the ball. In one or more embodiments, the simulated sports training environment may send the scored response to another user such as the coach. In one or more embodiments, the simulated sports training environment may send the scored response to another user to challenge the other user to beat one&#39;s score. 
       FIG. 2  is an exemplary flowchart illustrating the method  201  for calculating the decision and timing scores in the challenge mode. The user interacts with a play in a virtual reality environment, and a question or query is posed to the player (step  210 ). The player then interacts with the virtual reality system through a handheld controller, player gestures, or player movements in one or more embodiments (step  212 ). The interaction is monitored by the virtual reality environment which determines if the interaction results in a correct answer (step  214 ), correct timing (step  216 ), incorrect answer (step  218 ) or incorrect timing (step  220 ). Each of these decision and timing results are compared to an absolute score for the correct answer (step  222 ), an absolute score for the correct timing (step  224 ), an absolute score for the incorrect answer (step  226 ), or the absolute score for incorrect timing (step  228 ). The comparison of the absolute scores from the correct answer (step  222 ) and a comparison of the absolute score of the incorrect answer (step  226 ) determines the decision score (step  230 ). The comparison of the absolute score of the correct timing (step  224 ) and the absolute score of the incorrect timing (step  228 ) determines the timing score (step  232 ). The decision score (step  230 ) is assigned a number of stars for providing feedback to the player. A decision score of 60% or less generates no stars (step  234 ), a decision score of 60-70% results in one star (step  236 ), a decision score of 70-90% results in two stars (step  238 ), and a decision score of 90% or greater results in three stars (step  240 ) in one or more embodiments. The timing score (step  232 ) is assigned a number of stars for providing feedback to the player. A timing score of 60% or less generates no stars (step  242 ), a timing score of 60-70% results in one star (step  244 ), a timing score of 70-90% results in two stars (step  246 ), and a timing score of 90% or greater results in three stars (step  248 ) in one or more embodiments. 
       FIG. 3  is an exemplary flowchart illustrating a method  301  for determining the decision scoring for a football quarterback in one or more embodiments. A coach or another person creates a play (step  310 ), where, in this example, the wide receiver is chosen as the correct teammate for receiving the football (step  312 ). The wide receiver chosen by the coach as the recipient of the ball is deemed the correct answer for the player in the challenge mode. A play commences in a simulated environment, and the challenge mode is initiated as the player goes through a simulated play where the player interacts with a device and choses the player to receive the ball (step  314 ). The answer or response is chosen through a player interacting with a gamepad controller, on a tablet by clicking on an individual, or by positional head tracking. The player decision is monitored, resulting in either a correct answer (step  316 ) or an incorrect answer (step  318 ). The incorrect answer results from the player selecting players other than the player selected by the coach or play creator. The score is calculated by dividing the correct answers by the total number of questions asked (step  320 ). 
       FIG. 4  is an exemplary flowchart illustrating a method  351  for determining the timing scoring for a football quarterback. A coach or another person creates a play (step  352 ), where, in this example, the ball movement is chosen (step  354 ). The coach determines the time that the ball is chosen to move from the quarterback to the wide receiver that will be deemed as the correct timing in the challenge mode. A play commences in a virtual reality environment, and the challenge mode is initiated as the player goes through a simulated play where the player interacts with a device and chooses the player to whom the quarterback will throw the ball (step  356 ). The player timing is monitored, resulting in either a correct timing (step  358 ) or an incorrect timing (step  360 ). The timing is determined from the time of the snap of the football to the point in time that the quarterback throws the ball to the wide receiver. The incorrect timing is a time of release of the football that is inconsistent with the timing established by the coach. The time score is calculated by dividing the correct answers by the total number of questions (step  362 ). 
       FIG. 5  is a front, perspective view of a user  510  in an immersive virtual reality environment  501  which may be referred to as a CAVE. A user  510  typically stands in a cube-shaped room in which video images are projected onto walls  502 ,  503 , and  504 . The real player  510  is watching the virtual player  512  running across a virtual football field. 
     In an embodiment, the player  510  will be acting in the role of a quarterback. Players in the CAVE can see virtual players in a virtual football field, and can move around them to get a view of the virtual player from a different perspective. Sensors in the virtual reality environment track markers attached to the user to determine the user&#39;s movements. 
       FIG. 6  is a side, perspective view  521  of a user wearing a virtual reality head-mounted display  522  showing a virtual reality environment. The head-mounted display  522  has a display positioned inches away from the eyes of the user. Employing motion and orientation sensors, the head-mounted display  522  monitors the movements of the user  510 . These movements are fed back to a computer controller generating the virtual images in the display  522 . The virtual reality images react to the user&#39;s  510  motions so that the user perceives himself to be part of the virtual reality experience. In one or more embodiments, a smartphone or mobile device may be employed. 
       FIGS. 7-11  depict a sequence of virtual reality images for testing and training a quarterback to select a teammate in best position to receive the ball. Several screen shots depict a player interacting with a virtual reality environment where the player responds to a specific play by, for example, receiving a football, responding to the defensive players, deciding one or more actions, and completing the play.  FIG. 7  is a front, perspective view of a simulated environment  601  of a virtual football game and a handheld controller  610  for the user to interact with the simulated football game  601 . The hand held controller  610  has a joystick  612  and four buttons  614  (labeled as “A”),  616  (“B”),  618  (“X”), and  620  (“Y”). The simulated football game image shows both the offensive and defensive teams. Player  624  is labeled as “A”, player  626  as “B”, player  628  as “X”, and player  630  as “Y.” 
     A user, acting as a quarterback, will see the simulated players move across the field, and will be required to decide when to throw a football and to select which of the simulated players  624 ,  626 ,  628 , and  630  will be selected for receiving the ball in an embodiment. A user may select player  624  by pressing the button  614  (“A”), player  626  by pressing the button  616  (“B”), player  628  by pressing button  618  (“X”), and player  630  by pressing button  620  (“Y”). In one or more embodiments, real time decisions are made by the user by pressing buttons on a controller which correspond to the same icon above the head of the player. 
       FIG. 8  shows the positions of the players just before the initiation of a play. In  FIG. 9 , a play is initiated and in real-time, the user must choose which player to whom he will throw the football. In  FIG. 10 , the user selects which player will be selected to receive the football. In one or more embodiments, virtual ovals  625 ,  627 ,  629 , and  631  encircle the players  624 ,  626 ,  628 , and  630 . In this example, oval  627  is cross hatched or has a color different from that of the ovals to indicate to the user that player  626  was the correct choice. If the user does not decide correctly, the user can redo the play until he makes the correct choice. The score is based on how quickly decisions are made, and the number of correct decisions compared to total testing events. 
       FIGS. 11 and 12  illustrate that the simulated environment  701  can be configured to challenge users with multiple choice questions.  FIG. 11  shows a quarterback&#39;s perspective of a simulated football game before a play is initiated. The virtual reality environment shows a pop up window  710  presenting a question posed to the user. In this example, the virtual reality environment is asking the user to identify the areas of vulnerability of a coverage shell. In  FIG. 12 , the play is initiated and the user is presented with four areas  712 ,  714 ,  716 , and  718  representing possible choices for the answer to the question posed. In one or more embodiments, the user may select the area by interacting with a hand held controller, or by making gestures or other motions. 
       FIG. 13  is a front, perspective view of a simulated environment  801  of a virtual football game showing the possible areas from which the user may select in an alternative embodiment. The user is presented with a view before the initiation of a play, and a pop-up window  810  appears and asks the user to identify the Mike linebacker (i.e., the middle or inside linebacker who may have specific duties to perform). Three frames  812 ,  814 , and  816  appear around three players and the user is given the opportunity to choose the player he believes to be the correct player. 
       FIG. 14  is a front, perspective view of a simulated environment of a football game in an embodiment. The user is presented with a view before the initiation of a play, and a pop-up window  910  appears and asks the user to identify the defensive front. Four frames  912 ,  914 ,  916 , and  918  have possible answers to the question posed. The user is given the opportunity to choose the answer he believes is correct. In one or more embodiments, the user may choose the correct answer through interacting with a game controller, or by making gestures or other movements. 
     One or more embodiments train users to read a defense. For Man and Zone Reads such as picking up Man and Cover  2  defense, embodiments may have  20  play packages such as combo, under, curl, and so forth. Embodiments enable users to practice reading Man vs. Zone defenses. Users may recognize each defense against the formation, such as against a cover  2 , and may highlight areas of the field that are exposed because the defense is a cover  2  against that specific play. Players and areas may be highlighted. In one or more embodiments, a training package may consist of  20  plays each against Man and Cover  2  and highlighted teaching point. 
       FIGS. 15-18  are front, perspective views of a simulated environment  901  of a football game where the user is asked to read the defense. As a first step, the user is asked to identify the defensive coverage, which is cover  2  in this example. In  FIG. 16 , the user is asked to identify areas of weakness or exposure against the play, represented as areas  1012 ,  1014 ,  1016 ,  1018 ,  1020 , and  1022 . In  FIG. 17 , the user is asked to create a mismatch against a zone and expose the areas. The play is represented by players  1030 ,  1032 , and  1034  traversing the field as depicted in running patterns  1031 ,  1033 , and  1035 . 
     In  FIG. 18 , the user may use his hand  1050  to assess and identify the areas of the field that have “weak points” against that coverage. 
       FIGS. 19-23  are front, perspective views of a user interacting with a virtual reality environment  1101 . In one or more embodiments, the user may be wearing a head mounted display as depicted in  FIG. 6 , or may be wearing glasses having markers in an immersive virtual reality environment as depicted in  FIG. 5 . As shown in  FIG. 19 , the user sees an environment  1101  having a window  1110  describing the current lesson, an icon  1112  for activating audio instructions, and a window  1116  describing a virtual pointer  1120  represented here as a virtual crosshairs. In one or more embodiments, the virtual pointer may be fixed with respect to the display of the device. A user may interact with the virtual reality environment by aiming the virtual pointer toward a virtual object. The virtual pointer provides a live, real time ability to interact with a three-dimensional virtual reality environment. 
     In one or more embodiments, the virtual pointer  1120  moves across the virtual reality environment  1101  as the user moves his head. As depicted in  FIG. 20 , the user moves the virtual pointer  1120  over the icon  1112  to activate audio instructions for the lesson. The user may then use the virtual pointer  1120  to interact with the virtual reality environment  1101  such as by selecting the player that will receive the ball. As shown in  FIG. 21 , the user may then either replay the audio instructions or move to the drill by sweeping the virtual pointer  1120  over and selecting icon  1122 . 
       FIG. 22  is a front, perspective view of a simulated environment  1201  illustrating that the virtual pointer  1120  may enable a user to select answers from a multiple choice test. A window  1208  may pose a question to the user, where the user selects between answers  1210  and  1212 . The user moves virtual pointer  1120  over the selected answer in response to the question. In  FIG. 23 , the virtual reality environment generates a score for the user, and the user is able to attempt the test again or move to the next level. 
       FIG. 24  is a front view of a menu  1301  in one or more embodiments. In one or more embodiments, the user is presented with a series of plays in a playlist. The user navigates the application (“app”) by successfully completing a play which then unlocks the next play in the playlist. For example, icons  1310 ,  1312 ,  1314 ,  1316 ,  1318  and so forth, represent plays the user has successfully completed. Each of the icons may have a series of stars such as star  1311  which represents the score for that play. The icons  1360 ,  1362 ,  1364 , and  1366  represent the “locked” plays that later become accessible as the user completes the series of plays. 
       FIGS. 25-28  illustrate a training lesson in one or more embodiments.  FIG. 25  is a diagram  1401  of a pre-snap formation showing details of a basic play concept shown to the user in one or more embodiments. In  FIG. 26 , the user selects the center  1510  with the virtual pointer  1120  to snap the ball. In  FIG. 27 , the play is executed and the user decides to which player he will throw the ball. The user selects player  1512  and the user&#39;s actions are monitored and scored. In  FIG. 28 , the user is presented with his score  1526  as well as star icons  1524  indicating performance. The user may choose between icons  1520  and  1522  with the virtual pointer  1120  to select the next action. 
       FIG. 29  is a schematic block diagram illustrating the system  1601  for implementing the virtual reality simulated sporting event. In one or more embodiments, the system  1601  may comprise a web-based system  1610  having a controller or processor  1611 , a computer system  1612  having another controller or processor  1613 , and website/cloud storage  1616  also having a controller or processor  1617 . Both the web-based system  1610  and the computer system  1612  may be employed for creating, editing, importing, and matching plays, as well as for setting up the interaction/assessment, evaluating the interaction, viewing options, and handling feedback. The web-based system  1610  and the computer system  1612  communicate to the website/cloud storage  1616  through an encoding layer such as Extensible Markup Language (“XML”) converter  1614 . During this process the native software application .play file that is generated is in the XML language. The converter strips away XML tags, leaving just the remaining code without the XML tags. The mobile viewer is designed to read the remaining code and visualize the data from the code so the virtual simulations can run on the smartphone/tablet. The website/cloud storage  1616  may be employed for storing plays, handling interaction outcomes, playlists, feedback, and analysis of player decisions, timing, location, and position. The website/cloud storage  1616  may interface with several types of virtual reality systems including smartphones and tablets  1634 , native apps  1630  running on mobile viewers  1632 , or other computers  1620 . In one or more embodiments, a USB file transfer/mass storage device  1618  receives data from a computer system  1612  and provides the data to the single computer  1620 . The single computer  1620  may interface with a single projector system  1626  in one or more embodiments. The single computer  1620  may interface with a cluster of multiple computers  1622 , which, in turn, drive an Icube/CAVE projector system  1624 . 
       FIG. 30  is an exemplary flowchart showing the method  1701  of implementing the virtual reality simulated sporting event on a smartphone or tablet. In one or more embodiments, a play is developed on a desktop computer (step  1710 ). The files are then uploaded to a cloud (step  1712 ). The cloud then may download the play onto a mobile device (step  1714 ) such as a smartphone simulator virtual reality headset (step  1716 ), a tablet 3D view (step  1718 ), augmented reality (step  1720 ), or a video game view (step  1722 ). 
       FIG. 31  is an exemplary flowchart showing the method  1801  of implementing the virtual reality simulated sporting event employing a desktop or a web-based platform. A desktop computer may be employed as a play creation and editing tool. In one or more embodiments, the file type is formatted through an encoding layer such as XML, and is saved as a “*.play” file. Once created, the file can be sent to the XML converter. The file type is XML, and it is saved as a .play file. In one or more embodiments, a user or coach may use the web-based version of the editing and play creation tool. The web-based version will also send the file to the XML convertor. 
     The desktop (step  1810 ) and the web-based platform (step  1812 ) interact with the XML convertor (step  1814 ). The XML converter transfers data to the website (step  1816 ) having the cloud-based play storage (step  1818 ). After going through the XML convertor, the play is then able to be stored on the website. This website serves as the cloud based storage facility to host, manage, and categorize the play files. The plays are downloaded to a mobile viewer (step  1820 ) where the user interacts with the simulated play (step  1822 ). The website is integrated with a mobile app that automatically updates when new play files are added to the cloud based storage in the website. The mobile viewer, employing an app, interprets the play file. The user then can experience the play, and be given the result of their actions within the play. This data is then sent back to the app/website. 
     Data is captured from the user interactions (step  1824 ) and is stored (step  1826 ). Once the data is captured, the system will display the data on the app or website so the athlete can monitor progress, learn information about his performance, and review his standing among other members from their age group. The data is accessed by the end user and the scores and progress are tracked (step  1828 ). The data capturing is the most important aspect in one or more embodiments. This data can then be used to challenge other users, invite other users to join in the same simulation, and to track and monitor a user&#39;s progress throughout their lifetime. 
       FIG. 32  is an exemplary flowchart showing the method  1901  of implementing the virtual reality simulated sporting event on a larger system. Plays are created on a desktop (step  1910 ) and files are sent to an internal network (step  1912 ), a USB mass storage device (step  1914 ), or to the cloud (step  1916 ). The data is then downloaded to a program on a local computer (step  1918 ) and is then forwarded to TV based systems (step  1920 ), projector based systems (step  1922 ), or large immersive displays integrated with motion capture (step  1924 ). Examples of such large immersive displays include Icube/CAVE environments (step  1926 ), Idome (step  1928 ), Icurve (step  1930 ), or mobile Icubes (step  1932 ). 
       FIG. 33  shows an embodiment of a mobile device  2010 . The mobile device has a processor  2032  which controls the mobile device  2010 . The various devices in the mobile device  2010  may be coupled by one or more communication buses or signal lines. The processor  2032  may be a general purpose computing device such as a controller or microprocessor for example. In an embodiment, the processor  2032  may be a special purpose computing device such as an Application Specific Integrated Circuit (“ASIC”), a Digital Signal Processor (“DSP”), or a Field Programmable Gate Array (“FPGA”). The mobile device  2010  has a memory  2028  which communicates with the processor  2032 . The memory  2028  may have one or more applications such as the Virtual Reality (“VR”) or Augmented Reality (“AR”) application  2030 . The memory  2028  may reside in a computer or machine readable non-transitory medium  2026  which, when executed, cause a data processing system or processor  2032  to perform methods described herein. 
     The mobile device  2010  has a set of user input devices  2024  coupled to the processor  2032 , such as a touch screen  2012 , one or more buttons  2014 , a microphone  2016 , and other devices  2018  such as keypads, touch pads, pointing devices, accelerometers, gyroscopes, magnetometers, vibration motors for haptic feedback, or other user input devices coupled to the processor  2032 , as well as other input devices such as USB ports, Bluetooth modules, WIFI modules, infrared ports, pointer devices, or thumb wheel devices. The touch screen  2012  and a touch screen controller may detect contact, break, or movement using touch screen technologies such as infrared, resistive, capacitive, surface acoustic wave technologies, as well as proximity sensor arrays for determining points of contact with the touch screen  2012 . Reference is made herein to users interacting with mobile devices such as through displays, touch screens, buttons, or tapping of the side of the mobile devices as non-limiting examples. Other devices for a user to interact with a computing device include microphones for accepting voice commands, a rear-facing or front-facing camera for recognizing facial expressions or actions of the user, accelerometers, gyroscopes, magnetometers and/or other devices for detecting motions of the device, and annunciating speakers for tone or sound generation are contemplated in one or more embodiments. 
     The mobile device  2010  may also have a camera  2020 , depth camera, positioning sensors  2021 , and a power source  2022 . The positioning sensors  2021  may include GPS sensors or proximity sensors for example. The power source  2022  may be a battery such as a rechargeable or non-rechargeable nickel metal hydride or lithium battery for example. The processor  2032  may be coupled to an antenna system  2042  configured to transmit or receive voice, digital signals, and media signals. 
     The mobile device  2010  may also have output devices  2034  coupled to the processor  2032 . The output devices  2034  may include a display  2036 , one or more speakers  2038 , vibration motors for haptic feedback, and other output devices  2040 . The display  2036  may be an LCD display device, or OLED display device. The mobile device may be in the form of hand-held, or head-mounted. 
     Referring now to  FIGS. 34-50  in general, in another embodiment(s), aspects of the subject technology may generate a baseball related simulation that may be beneficial for users (as batters) to practice hitting in preparation of competition against real-life pitchers. Aspects of the embodiments described below may digitize the image of a real-life baseball pitcher and display the image as a digital avatar within a baseball replicated environment. As may be appreciated by those individuals that have tried hitting a real-life baseball thrown by a pitcher, the act of hitting a pitched baseball is often regarded as perhaps being the single most difficult act in all of competitive team sports. The challenge of hitting a professionally pitched baseball is more challenging than for most. The speed of a pitched baseball can often reach somewhere in the range of 90 miles per hour (MPH) to over 100 MPH for today&#39;s pitchers. The distance from the pitcher&#39;s plate (also known as a pitcher&#39;s rubber) to home plate is 60 feet and 6 inches by Major League Baseball (MLB) rules as well as for most baseball levels from high school and up. The typical time for a pitch to reach the plate once it leaves the pitcher&#39;s hand is approximately 400 to 500 milliseconds. The human eye has been found to only recognize the pitched baseball in just a few points along the path of trajectory from the pitcher&#39;s hand to the point of contact near the home plate. If one factors in the need for the batter to recognize not only when the ball will be at the point of contact but also from where the baseball is released by the pitcher in three dimensional space, the trajectory of the baseball&#39;s flight path, and whether the baseball will cross over home plate between the upper and lower limits of the batter&#39;s strike zone, it is understood that an extreme challenge exists for the batter to decide within split seconds whether or not to swing at the pitch. 
     The common approach for batters is to practice against live pitching or to use a mechanical pitching machine to practice form and timing. However, this approach is limited by the fact that every pitcher&#39;s delivery has its own subtle characteristics that heretofore are not replicated by conventional tools and practices. For example, one pitcher may release a pitch using what is known as a true overhand delivery (from a “12 o&#39;clock to 6 o&#39;clock” release), while some may throw from a three-quarters slot, some from a side arm release, and a few from what is known as a submariner&#39;s release where the arm lowers down to below the waist as the arm is swung upward and forward. 
     Some video games can generally replicate a general delivery type as described above and may use a generic pitcher avatar to “simulate” a certain pitcher for a certain team, however an actual real-life pitch and delivery may vary significantly from the video game generated delivery of said pitcher. In addition, while some video games include a relative speed of a pitch and calculate whether a user&#39;s action (which may be tracked by a game controller) resulted in contact, users often experience a substantial lag (for example, from tracking of said game controller) in the triggering action as well as an unnatural perspective because the pitcher often looks larger than life on a monitor. The release point between pitchers may remain static and becomes easy to predict and is not reflective of the pitcher&#39;s real-life release point. So while a user may become proficient at hitting a pitch from a static release point and may physically compensate for the video game system&#39;s lag, such practice does not translate into successful use in a real-life situation because the timing and release point recognition is very different. 
     Even amongst pitchers using a similar delivery type (overhead, three-quarters, etc.), pitchers have varying physical attributes (for example, height, arm length, etc.) and delivery mechanics that vary the release point that batters see from pitcher to pitcher. Recognizing and being prepared for delivery from a particular pitcher&#39;s release point is a strong tool for a batter&#39;s preparation against an opponent. This approach eliminates one of the decision making factors described above that need to be made within the split seconds available during a pitch. However, there remains the daunting task of actually recognizing a pitch type, timing and the trajectory of the pitched ball. 
     To date, the only way that is close to practice against a pitcher&#39;s delivery (known as “read the pitch”) was to watch still shots or video footage of a pitcher. However, it is almost impossible to capture still shots and video footage exactly from the batter&#39;s perspective, but instead are typically captured by a photographer/cameraman at a third-person perspective offset from the batter&#39;s perspective. As a result, traditional still shots and video footage still fail to provide the batter the immersive experience of facing a real-life pitcher on the baseball field. Moreover, still shots and video do not allow a batter to simulate a swing at a pitch with certainty in the results. One can swing against a video clip and only guess as to whether or not contact was made and how successful the contact; in other words, did contact result in a foul ball, a weak/strong ground ball, a line drive, or fly ball? In live-action, players are limited to practice swings against a pitcher&#39;s delivery while waiting from far to the side of home plate (usually in a warm up circle next to the dugout). From this perspective, the batter is limited to timing pitches but cannot see from the same first person perspective that happens in an actual at-bat. 
     In the embodiments disclosed below, aspects of the subject technology provide a first-person perspective of pitches that simulate the actual real-life delivery and trajectory of pitches from real-life pitchers. The user (sometimes referred to generally as the “batter”) may watch a digitized avatar of a real-life pitcher perform their own pitching sequence with a simulated baseball delivered from the pitcher&#39;s tracked release point that leaves the pitcher&#39;s hand with the spin pattern of a selected pitch type from the pitcher&#39;s known pitch types. Depending on the pitch, pitch data is used to simulate the flight path for a pitch type at the spin rate (and spin axis) associated with the pitcher&#39;s pitch and within the known range of speed, velocity and acceleration for a pitch type from the selected pitcher. The system may control whether a pitch will enter the strike zone or pass outside the strike zone so the batter can recognize with practice whether some pitches released at various release points for the pitcher will be a strike or ball. 
     Referring now to  FIGS. 34-38 and 50 , a virtual reality projection system  2100  (sometimes referred to generally as the “system”) is shown both in illustration and block diagram embodiments. In an exemplary embodiment, the system  2100  generates a three dimensional, panoramic first person view of a pitcher  2150  and the surrounding environment. The surrounding environment may include a home plate, batters&#39; boxes, the pitching mound, base lines, bases, dirt and grass infield parts, an outfield, an outfield wall, stadium seating, and any other elements one may find for a stadium setting. Some embodiments have images of professional (or otherwise) stadiums that can replicate the scene a player is about to experience. In use, the batter may look around and experience the same visual sensation one would perceive at the actual stadium. The pitcher  2150  may be a digitized avatar of a real-life pitcher with movements created by replicating real-life movements of said pitcher from stored video of past pitching performances. The pitcher  2150  may also be a digitized avatar of a real-life pitcher with movements created by animating the body joints of said avatar through techniques known as key-framing or motion capture. The system  2100  may thus enhance the practice experience by seeing the pitcher in the same environment the batter will perform. The processes for simulating the pitcher&#39;s appearance in a selected environment is described in more detail further below. 
     Referring to  FIG. 50  for the moment, the system  2100  generally includes a projection system  2130  coupled to a processor  2160 , and a graphics engine module  2170 . The graphics engine module  2170  may be dedicated hardware, software, or some combination thereof and is generally configured to generate the virtual reality graphics simulating a selected pitcher&#39;s delivery including delivery from a calculated release point, simulating the trajectory and spin of a thrown pitch, generating the virtual reality surrounding environment of both the digitized pitcher  2150  and the stadium, any pop-up elements, and any simulated hits of a pitch by the user. The processor  2160  may be similar to any of the processors described in  FIGS. 1-33  above and/or may be a dedicated graphics processor. Some embodiments also include a memory bank  2180  for temporary storage and retrieval of data being processed and a database or memory storage  2190 . Some embodiments may also include a camera or set of cameras  2140  connected to the processor  2160  and/or other elements shown. Any data related to a pitcher may be stored and accessed from the database  2190 . The database  2190  may store data associated with a plurality of pitchers. Information retrieved from the database  2190  and used by the system  2100  includes for example initial position (ball release point), initial velocity, initial acceleration, spin rate and other data tracked from real-life pitchers&#39; previous games. The database  2190  may be updated manually or automatically as more pitching data become available, for example as new baseball games are carried out in the season. The pitch data may be streamed via a streaming protocol as a means of the update, for example, the HMD user may choose to stream new pitch practice data remotely via wireless network from a network server or cloud. 
     A user device  2105  may be coupled to the processor  2160  and may vary from embodiment to embodiment. For instance, in the exemplary embodiment shown in  FIGS. 34 and 35 , the user device  2105  maybe a CAVE type projection room with the projection system  2130  projecting generated virtual reality scene segments onto four walls (front, left, right and floor)  2120  to generate a panoramic virtual reality scene  2110 . The user may wear a pair of stereoscopic glasses  2102  that turn the images on the surrounding walls  2120  into a stereoscopic view. One or more walls may be removed to form a more portable system, for example a system with only the front wall and floor. Cameras  2140  may track the position of the user (and the user&#39;s eyes as described in some processes below) in the CAVE as well as any accessories carried by the user (including but not limited to a baseball bat, an interactive controller). Once a pitch is thrown, some embodiments will provide a trail  2111  of the pitch&#39;s flight path (for example as a series of balls  2101  placed along the pitch&#39;s trajectory), with the ball&#39;s seam position at each interval along the baseball&#39;s flight path shown from the batter&#39;s perspective so that the batter may learn to identify one pitch type from another based on the pitch trajectory and rotation of the seam pattern visible. Some embodiments will provide a mechanism for detecting if the pitch was hit with the tracked baseball bat  2104 . While the embodiment shown and described is in the form of a CAVE, some embodiments may be adjusted to operate in a head mounted display (HMD) unit ( FIGS. 36-38 ) so that the movement of batter&#39;s HMD is tracked in relation to the virtual environment, and adjust flight path of the pitched baseball in the field of view of the HMD. The batter may use gaze directed crosshairs to interact with pop-up elements such as a quiz question asking about the type of pitch, location of the pitch on strike zone plane, ball or strike ( FIG. 38 ). The batter&#39;s bat swing may also be tracked in relation to the virtual environment, and checked if the pitch was hit. Some embodiments include a sound generation module  2195  that generates an impact sound dependent on the quality of the hit (for example, foul ball, hard/weak ground ball, line drive, pop fly, or homerun). 
     In use, a pitcher&#39;s profile may be selected from the database  2190  by the user so that the selected pitcher&#39;s digitized avatar  2150  is displayed in the virtual reality scene  2110 . The selected pitcher&#39;s profile includes video footage of the pitcher&#39;s delivery and general body movements that are part of the delivery.  FIG. 36  shows an enlarged view of a selected pitcher  2150  in mid-delivery during a wind-up type sequence. Some simulations will show pitchers delivering from a stretch position. As will be appreciated, every pitcher has his own arm/hand positioning as well as step placement during a delivery which affects the timing of delivery. Some pitchers go so far as to intentionally include hitches in their delivery to throw off a batter&#39;s timing. Being able to prepare against an accurate replication of a pitcher&#39;s delivery is highly beneficial to a consistent swing against that pitcher. The user may also focus on practicing against a specific type of pitch, by filtering out all other types of pitches, and working on the swing timing and/or swing position. The user may also focus on practicing against a specific range for the pitch speed, by filtering out all other ranges of pitch speed, and working on the swing timing. The user may also focus on practicing against a specific opposing pitcher by loading previous real-life at-bats data of such pitcher. 
     The pitcher&#39;s profile data also includes for example, each pitch type (including but not limited to two seam fastball, four seam fastball, change of speed, curveball, sinker, slider, split finger fastball, cut fastball, and knuckleball) that the pitcher has thrown and has been recorded along with a range of speed for each pitch type, the release point of each pitch type, trajectory paths, strike zone pitch distribution, and spin rates and spin patterns for each pitch type. The pitch type may be based on the initial grip of the baseball and the manner of hand movement used when releasing the grip (for example, degrees of supination, pronation, etc.). Thus a user may input into the system a setting which repeats the same pitch type over different parts of the strike zone or according to the selected pitcher&#39;s statistical preferences, or the user may ask for random pitch types thrown so that he can learn to recognize and distinguish one pitch type from another. 
     Referring to  FIGS. 37 and 38 , other embodiments may provide practice against a selected pitcher for determining whether a simulated pitch will be a strike or a ball (outside the strike zone). The system  2100  is able to use the selected pitcher&#39;s tracked data to accurately replicate known release points and simulate the same flight paths of pitches. A change in a pitcher&#39;s release point may be the difference in whether a same pitch type is either a strike or a ball. In some embodiments, a pop-up strike zone field  2115  ( FIG. 37 ) may be displayed for the batter&#39;s reference. Some embodiments may provide a pause in the pitch&#39;s flight to present the user a displayed query graphic  2125  which may ask for example, whether the pitch is a strike or a ball. A timer  2135  may be displayed requiring the user to select a choice before the end of the timer. As shown, it will be appreciated that the timer may reflect a real-life time available to decide an aspect of the pitch. While the example is shown with respect to the decision of a ball or strike, it will be understood that other aspects may be presented in the query graphic  2125 , such as asking for the pitch type, estimated pitch speed, in case of strike which of the 9 (3 by 3) strike zones did the pitch go through. 
     Referring now to  FIGS. 39 and 40 , illustrations showing how the release point  2155  for a selected pitcher may be determined. The digitized avatar  2150  for a pitcher may be replicated from actual game footage provided from any number of known third party sources. As described earlier, footage data used may be organized into data entries by pitch type so that the release point for each pitch type a pitcher uses is charted and used in the virtual reality setting rather than just showing for example an average release point for all the pitcher&#39;s pitches. In addition, the release point for each pitch type may be further organized by strike or ball results so that a batter may practice distinguishing from each for the same pitch type. Each video clip of a pitch thrown by the selected pitcher may be annotated to mark the player&#39;s height, the pitching mound apex (adjacent the pitcher&#39;s plate), and the height of the baseball from the mound apex level at the point of release for recorded pitch. As shown in  FIG. 40 , each pitcher has several video clips per pitch type in the database, with variations in the height of the ball release point recorded depending on the different pitches, as represented by avatars  2150   a,    2150   b,  and  2150   c  each showing the baseball being released at a different height. The processor  2160  and graphics engine module  2170  may adjust the virtual reality graphics to replicate the release point  2155  based on the annotated data. 
     Referring now again to  FIGS. 34 and 45  along with  FIGS. 41-43 , in operation, it will be further appreciated that the system  2100  provides an enhanced realistic experience by simulating a user&#39;s environmental experience as close to the real-life experience of batting against a selected pitcher as possible. The virtual reality scene  2110  may be displayed so that the depth perception and scale of the digitized pitcher&#39;s avatar  2150  appears natural. 
     Referring also to  FIG. 48  along with  FIGS. 41-43 , an exemplary process  2200  for matching perspective of the user with a selected pitcher&#39;s avatar is shown. Elements of the flowchart in the process  2200  are designated by placement in parenthesis while numerals without parenthesis refer to elements in the diagrams of  FIGS. 41-43 . Each pitch video may be pre-processed to turn all background pixels to full transparency, but the pitcher&#39;s image and baseball&#39;s image may be left as-is. This is sometimes known as rotoscoping. Each pitch video is annotated to mark the ball release point, pitcher&#39;s height, and locations of pitcher mound apex where the pitcher&#39;s pivot foot is placed. To simulate a particular pitch from the ball pitch database, first the ball release point is acquired from the ball pitch flight data, which typically is 50-55 feet away from home plate. Based on the pitch type and also height of the ball release point for this particular pitch, the best matched pitch video (rotoscoped and annotated) is selected from this specific pitcher&#39;s pool of video clips, in a way that the ball release point from the video is the closet to the actual ball release point for this particular pitch. This pitcher&#39;s avatar and associated video may be displayed on a video plane (for example in the form of a rectangular plane geometry), always facing the batter (user “U” as shown in  FIG. 41 ), and the video plane is positioned so that the actual ball release point  2155  lies within the video plane. The eye position of the batter may be acquired ( 2210 ) from the motion tracking system which tracks the batter&#39;s stereoscopic glasses (for example glasses  2102  of  FIGS. 34 and 35 ). The position of batter&#39;s eyes is updated ( 2220 ) in real-time. This pitch video plane may be anchored in a way that the pitcher&#39;s pivot foot is perceived to be fixated right at the apex of the pitching mound (because of line of sight) only from the perspective of the batter as shown in  FIG. 41 . More specifically, when the position of the user&#39;s eyes changes, the pitch video plane may be constantly adjusted in real-time to maintain the aforementioned line of sight, so that the pitcher&#39;s pivot foot appears to be exactly on top of the pitch&#39;s mound apex (essentially on top of pitcher&#39;s plate). In addition, the video pitcher may be constantly scaled and translated so that from the batter&#39;s perspective, the pitch release point  2155 ′ shown on the video plane matches exactly the release point  2155  of the actual pitch being simulated (because of line of sight). More specifically, without translating and scaling of the video pitcher, the release point  2155 ′ that appears in the video plane may not appear to be in the correct point of release in a natural environment as the perspective is off, because the projection surface may be in actuality closer than the 60 feet 6 inches a real-life pitcher would be. The height and pivot foot location of the perceived pitcher as well as the pitch release point  2155 ′ are calculated in real-time based on the annotation data in the pitch video clip. The pitcher video plane is then scaled ( 2230 ) in a way that the ball is perceived to be released exactly from the actual ball release point  2155 , while keeping pitcher&#39;s pivot foot anchored on top of pitcher&#39;s plate, as shown in  FIG. 42 . The video pitcher is perceived as if he is standing on the pitcher&#39;s mound at 60 feet 6 inches away from home plate. 
     The exemplary process  2200  for matching perspective of the user also includes adjusting the stadium and the baseball field. The stadium including the field may be captured as a 360 degrees panorama photo or video and applied to a sphere (represented by the arc  2165 ′), or may be geometrically modeled, or may be a hybrid of the two, for example the field is geometrically modeled and the stadium is captured as a 360 degrees panorama photo. The stadium including the field may be proportionally scaled ( 2240 ) in a way that the pitcher appears to be the same height. For example, if the perceived pitcher may be scaled to be slightly taller than his actual height (in order to match the actual pitch release point), the stadium may be scaled slightly larger by the same proportion towards a reference point  2166  on the arc  2165 ′. The scaled stadium is represented by the arc  2165  which is scaled up from arc  2165 ′. The perceived pitcher thus does not appear taller than he actually is. Each step from ( 2210 ) to ( 2240 ) may be repeated in real-time for consistency with movement of the user&#39;s eyes. As a result, the pitcher&#39;s avatar is being anchored and scaled in real-time based on batter&#39;s eye position, so from the batter&#39;s perspective, the pitcher is perceived to be on the pitcher&#39;s mound pitching the ball, and the ball release point from the video pitcher exactly matches the actual pitch release point from the pitch database throughout the entire pitch, given that the batter stays within a reasonable range from the home plate. Also the stadium is being scaled in real-time based on batter&#39;s eye position, so from the batter&#39;s point of view, the pitcher is perceived to be in accordance to his actual body height relative to the size of the stadium. 
     The exemplary process  2200  may need to handle a special case which is caused by the lack of variations in the height of pitch release points (such variation is depicted in  FIG. 40 ). Hypothetically if only one pitch release point at a specific height is available from a particular pitcher&#39;s video database, assuming it happens to be a relatively low release point (for example one similar to  2150   a ), when a particular pitch performed by this particular pitcher with a relatively high release point is being simulated, this may cause the process  2200  to scale up the video pitcher so much that he becomes out of proportion. To prevent this issue, the exemplary process  2200  is designed to limit the scaling of the video pitcher (and also the corresponding scaling of the stadium) in a way that the overall virtual reality scene looks natural. The exemplary process  2200  may alter the actual pitch release point  2155  for a particular pitch in order to match the release point  2155 ′ from the scaled video pitcher that is already scaled at the scaling limit. A drawback is that the system may not able to utilize the pitch data 100% original due to said shifting of pitch release height, however an option is added where the batter may filter out pitches with such shifts, to be able to utilize 100% original pitch data. 
     The system may also use computer generated (CG) pitcher avatars that are animated (also known as key-framed) either manually or using motion capture data. Unlike the pitch avatar described in process  2200 , CG avatar is geometrically modeled in three dimensional space with articulated bones and body joints. Such CG avatars may eliminate the need for matching the perspective of the batter. In such case, CG avatar may be anchored directly on top of the pitching mound with pivot foot placed on pitcher&#39;s plate. The CG avatar may be scaled so that the pitch release point from the animated pitch sequence exactly matches the release point from the actual ball release point  2155 . The pitch motion of the CG avatar may also be slightly altered using an algorithm known as Inverse Kinematics (IK), where the joint angles of the CG avatar&#39;s arm and/or body may be mathematically computed in a way that to control end-effector (in this case the pitch&#39;s hand) to reach any feasible location within the three dimensional space, specifically in this case control the CG avatar&#39;s hand to reach exactly the actual pitch release point  2155 , without the need to alter the scaling of the said CG avatar nor the stadium. The drawbacks of using CG avatar may include the following. The CG avatar and associated variation of animated pitch sequences may be very difficult to acquire, which may pose a huge challenge when deploying such baseball virtual reality training system where large quantity and variations of CG pitchers and animated pitch sequences are required; the fidelity of the CG avatars as well as the pitch motions may be subpar compared to pitchers simulated using video sources. 
     Referring now to  FIG. 49 , a process  2300  for simulating a pitched ball flight trajectory in a virtual reality scene is shown according to an exemplary embodiment. Pitch flight parameters are loaded ( 2310 ) in from a database that stores pitching data associated with a selected pitcher. With the virtual pitcher having performed his motion and delivery, a pitch timer may be started ( 2320 ) at the exact moment when the ball is released from the pitcher&#39;s hand, which is associated with the flight time of a virtual pitch. During display of the simulated pitch and its flight path, the simulated baseball&#39;s position along the trajectory and its rotational property (shown by position of the seams) may be updated ( 2340 ). A determination ( 2350 ) may be made whether a user&#39;s batting swing made virtual contact with the simulated pitch. If the user missed, the process determines ( 2360 ) whether the pitch (flight path) has terminated. If the user makes contact, a second timer may be started ( 2370 ) tracking the length of time a hit ball has been travelling in flight. Some embodiments may calculate the trajectory, exit velocity, exit angle and distance of a simulated hit depending on the pitch speed, pitch spin, speed of the swing, angle of swing attack, and position of the bat barrel where contact occurred. A determination ( 2380 ) may be made on whether the flight of the hit ball&#39;s timer has elapsed. If so, the flight path of the hit ball may be updated ( 2390 ) for position and rotation until an affirmative determination ( 2395 ) is achieved that the hit ball&#39;s flight timer has ended. 
       FIGS. 44-47  show schematics for determining whether a user makes contact with a simulated pitch. In some embodiments, a real bat  2104  may be used and retrofitted with tracking markers. Elements designated by a numeral and (′) represent the position of the element shown in shadow lines which is at a later point in time (either at the point of impact or post-miss) than the position of an element using a regular numbered call out. As shown in  FIG. 47  the swing plane may be tracked using high speed tracking cameras (for example camera(s)  2140  of  FIG. 50 ). The bat swing is captured using a high-speed motion capture system running at  330  frames per second or higher. At each frame, the system checks for bat-ball impact. Between two consecutive frames, the valid hitting zone on the bat sweeps over a plane, in the shape of a “trapezoid” (see  FIGS. 45-47 ) while the ball travels along an approximated “line segment” towards the home plate. The tracking system introduces a small but consistent bat tracking latency (which may be measured in advance). To compensate for this latency, the bat swing may be predicted based on previous frames tracking data so that the tracked bat (used for bat-ball impact detection) may be made to swing slightly ahead of itself. A different approach to compensate for the said tracking latency is that the system may apply the tracking latency on the pitch ball flight simulation so that the simulated pitch ball (used for bat-ball impact detection) may travel slightly ahead of time. Because the entire ball pitch flight can be simulated in advance using the pitch parameters retrieved from database, the second approach may be simpler to implement, and it may also be more accurate than the first approach. 
     Referring to  FIG. 47  a bat-ball collision detection algorithm #1 detects the scenario of possible impact. At each frame, the system calculates the minimal distance between the “trapezoid” and the “line segment”. If the minimal distance is less than the sum of the radius of the ball and the radius of the bat, it indicates a possible bat-ball impact, but requires further calculation to confirm; if the minimal distance is larger than the sum of the two, the bat does not make contact with the ball. 
     Referring to  FIG. 47  bat-ball collision detection algorithm #2. When a possible bat-ball impact is detected, the system may use a continuous collision detection algorithm to further confirm the impact. Using the tracked bat data from current frame (t) ( FIG. 46 ) and previous frame (t−Δt) ( FIG. 45 ), the system calculates the speed of the bat. The speed of the pitch ball at current frame (t) is also calculated using the pitch parameters (as previously mentioned, the tracking latency may be applied to the timing of the ball). The system may perform an iterative procedure where it slowly advances the time t+Δt, calculates the position of the bat and the position of the ball based on their speeds at time (t), then calculates the minimal distance between the central axis of the bat and the center of the ball, if such minimal distance falls below the sum of the ball radius and the bat radius (at bat intersection), the system may confirm the bat-ball impact actually occurred at time t+Δt. 
     As will be appreciated, such continuous collision detection algorithm (#2) may accurately confirm the bat-ball impact, however it may run slower than collision detection algorithm #1. In order to achieve the fastest bat tracking result and low-latency immersive virtual reality experience, the system may be designed to run algorithm #1 by default to achieve maximum frame rate, and switches to algorithm #2 when a possible bat-ball impact needs to be confirmed. Such continuous collision detection algorithm (#2) may calculate the post-impact exit velocity, exit angle, ball trajectory and distance of a simulated hit, based on the pitch speed, pitch spin, speed of the bat swing, angle of swing attack, position of the bat barrel where contact occurred, and the overlap (vertical displacement) between the bat and the ball at contact. Based on the results of the bat-ball impact detection, some embodiments provide an impact sound generated by the sound module  2195  ( FIG. 50 ) when the bat-ball impact is detected. Such sound may be electronically synthesized, for example the system  2100  plays recorded sound effects based on the type of impact through a speaker. Such sound may be generated physically, for example a mechanical trigger is released to hit a wood block in order to generate the sound effect. Such sound may be generated when a mechanical trigger on or inside the bat  2102  is released to hit the bat in order to generate the sound effect as well as causing the bat to vibrate as a form of haptic feedback. The impact sound may vary based on the type of bat, including an impact sound for the wood bat and a different impact sound for a metal bat. The frequency of the impact sound may vary based on the location where the bat barrel made contact with the simulated pitch, and/or the overlap (vertical displacement) between the bat and the simulated ball at contact. An impact sound may be selected for a particular pitch from a pool of impact soundtracks stored in the database or memory storage  2190 , based on various properties for such particular impact, including but not limited to, pitch speed, pitch spin, speed of the bat swing, angle of swing attack, post-impact exit speed and exit angle, position of the bat barrel where contact occurred, the location where the bat barrel made contact with the simulated ball, and the overlap (vertical displacement) between the bat and the simulated ball at contact. 
     Note that the bat-ball impact detection may not real-time, but very close to real-time. The delay may be introduced by the bat tracking latency. The delay may also be introduced by the bat-ball impact collision detection algorithm #2 executed at least 1 frame after the impact. 
     As will be appreciated, a swing plane ( FIG. 44-46 ) from the user&#39;s bat swing may be plotted as an augmented reality overlay inside the virtual environment, along with a virtual baseball as it cut through the strike zone plane. The swing plane may be used to visualize if the batter&#39;s swing was too high, too low or at the correct height. Colors may be applied to swing planes in order to help visualize such location differences from the bat swings. Bat swings and the corresponding pitches may be recorded to help the batter analyze his swing. Replay of a previous bat swing and the corresponding pitch may be activated in slow motion (frame by frame) to analyze for any arbitrary practice recorded. 
       FIGS. 51-57  show screenshots of various training modes and features in exemplary embodiments of a virtual reality system of the present disclosure.  FIG. 51A  shows a process of generating some of the features and should be referenced while viewing the screenshots of embodiments in  FIGS. 51-57 . In general, it should be understood that a user is immersed in the virtual reality embodiment and may be provided with a menu (not shown) to access any of the training modes shown. In addition, the perspective is generally shown from the hypothetical position of the user as a batter in an area adjacent a home plate  5150 . Some embodiments may not necessarily display a replication of a home plate and may use some other marker  5150  for the user to identify the area where the pitch will travel through. However, the user is free to move around the area and may for example, view a thrown virtual pitch from directly behind home plate  5150  (for example, from a catcher&#39;s perspective). Thus, as may be appreciated, one may in addition to training their batting skill, train their skills as a catcher by using one or more of the training modes to train their visual acumen for receiving a pitch. 
     Referring now to  FIG. 51A , the user may select one of the training modes: pitch identification, occlusion, or swing decision. It should be understood that other training modes may be included. 
     Pitch Identification 
     In the pitch identification mode, the system generally provides the user replication of pitches from which the user is to identify the pitch type. In some embodiments, a specific pitcher may be selected. The pitching data associated with the selected pitcher may include only certain pitch types. When selected, the pitching data (including pitch types, speed for pitch type, and release point for pitch type) may be loaded into the virtual reality replication engine. The pitch types (depending on the pitcher file selected) may include for example, four seam fastball, two seam fastball, changeup, curveball, slider, sinker, or any other pitch type that has been recorded for a pitcher. In some embodiments, the user may select which areas of the strike zone the user wants the pitches restricted to passing through. 
     During training, the system generates one of the pitcher&#39;s pitch types. In some embodiments, the pitch type selected may be randomized. In some embodiments, the pitch type replicated may be based on a frequency of user as determined from the pitcher&#39;s pitching history. 
     When the virtual pitch is replicated, the user may track the digital baseball along its entire path (trajectory  5200 ); from the release point, all the way through the strike zone plane, and beyond. Once the thrown virtual pitch has been replicated, the user may be provided a pointer tool  5600  to identify from a visible menu  5250  a guess as to what type of pitch was thrown. See  FIG. 52 . In some embodiments, a replicated virtual strike zone plane  5050  or array may be displayed adjacent the virtual home plate (for example, above the plate and anywhere from the pitcher-side front edge to the catcher-side back point of the plate). See for example,  FIGS. 54-56 . In some embodiments, the user may also be provided a pointer  5600  to select a location in the virtual strike zone that represents a guess of where the pitch passed through. See  FIG. 56 . It should be noted that the system may purposely replicate pitches that fall outside the strike zone and the user is tasked to accurately identify when and where this occurs. 
     In some embodiments, a pitch type may have data associated with a seam pattern that is shown during the replicated trajectory of a thrown virtual pitch. The user may train to recognize the seam pattern and trajectory of the pitch type as a visual cue. Some embodiments may include a sound file based on the pitch type so that different pitches sound differently, which provides another cue for the user to train to recognize different pitches. 
     The system may determine whether the user selected the correct pitch type. In an exemplary embodiment, the trajectory of the thrown virtual pitch may be displayed after the user pitch type selection so that the user may review the actual trajectory  5200 . The actual pitch type may be displayed. if the user was incorrect in guessing the pitch type, a visual cue may be displayed. For example, the pitch trajectory  5200  may be displayed in a first color (green) for correct answers or the pitch trajectory may be displayed in a second color (for example, red) for incorrect answers. See for example,  FIG. 55  which shows a correctly guessed pitch type. Some embodiments may display markers representing the guessed location of the pitch at the strike zone plane and the actual location. For example, the guessed location may be shown as a virtual baseball  5020  in a first color or in a different graphical representation than the replicated thrown virtual pitch at the actual location. The digital baseball  5010  at the actual location may be shown simultaneously with the trajectory graphic passing through and beyond the strike zone plane graphical representation  5050 . See  FIG. 55 . The system may determine a difference in the distance between the guessed location of the pitch at the strike zone plane and the actual location. The difference may be displayed in a visible graphic  5700  representing pitch location for example as shown in  FIG. 57 . Some embodiments may display the difference in distance simultaneously with the relative position of the guessed location and actual location. 
     Occlusion 
     Some embodiments may include a feature for training the recognition of a pitch for pitch type and trajectory by occluding the thrown virtual pitch trajectory after the replicated release point. “Occlusion” as used herein may refer to closing off the visual path of a virtually replicated pitch in its trajectory toward the user. Referring to  FIG. 51 , some embodiments may generate a virtual frame  5100  or wall that is displayed in between the virtual pitcher and the home plate area. When the occlusion training is selected, the system may operate similar to the pitch recognition system described above. For example, the same visual and audio cues for pitch replication described above may be incorporated into the occlusion mode described herein. The user will be presented a replicated pitch, however, the user will train to recognize the characteristics of the pitch without seeing the digital baseball travel its entire path. In general, at some point during the baseball&#39;s trajectory, the virtual baseball disappears. 
     In operation, the user may set the distance from the pitcher (or the user/home plate area) the occlusion frame will be positioned. Some embodiments may begin at a default location closer to the user (which means more of the baseball&#39;s trajectory will be displayed). Some embodiments may re-position the virtual frame  5100  closer to the virtual pitcher after every pitch to decrease the field of view and increase the difficulty of pitch recognition. When the pitch is replicated, the user may see the baseball at the release point and for some distance after the release. The digital baseball and its trajectory are blocked at the point of occlusion intermediate the virtual pitcher and the batting area. For example, the pitch may appear in flight and then as the digital baseball appears that it will travel through the virtual frame  5100 , the digital baseball disappears from view. The user must use their pitch recognition skill to: identify the pitch type (for example, from visual cues such as seam pattern rotation, release point, initial trajectory, sound, and any other cues) and its overall trajectory.  FIG. 51  shows a thrown virtual pitch that has been blocked from view after its release from the virtual pitcher. The system may receive a user selection (guess) of the pitch type. In some embodiments, the user may point to or determine whether the pitch was in the strike.  FIG. 52  shows the system displaying the full pitch trajectory through the strike zone after the user&#39;s guess (pointer  5600  selecting a fastball), the user&#39;s pitch type selection (as a correct guess) and a speed of the pitch. 
     Swing Decision 
     In another training mode, the user may practice their decision-making skill related to determining which pitches to swing at. The process for replicating a virtual pitch is similar to the processes described above. The same visual and audio cues for pitch replication described above may be incorporated into the swing decision mode described herein. In embodiments training swing decision making, the user is presented with a thrown virtual pitch. While the pitch is travelling along its trajectory  5200 , the user may activate a trigger function indicating the act of swinging a virtual bat. Embodiments may not necessarily require the trigger function to represent the timing of the swing. For example, the trigger function may represent when the user recognizes that the pitch will be in the strike zone so that they would theoretically start their swing movement. The system may determine at what distance  5320  from the strike zone (or from the release point, the point of reference being arbitrary) the user triggered the decision. Some embodiments may determine an optimal distance  5310  (or distance range) for the decision to be made. The optimal distance  5310  may be based on for example, the speed of the pitch and/or the pitch type. Some embodiments may generate a display showing whether the user&#39;s decision to swing was correct. See for example,  FIG. 53  and  FIG. 54 . The results may also display the optimal decision distance  5330  and the user&#39;s decision distance  5340  so that the user can see whether they are recognizing their decision to swing fast enough or too late. 
     Although the invention has been discussed with reference to specific embodiments, it is apparent and should be understood that the concept can be otherwise embodied to achieve the advantages discussed. The preferred embodiments above have been described primarily as simulated environments for sports training of athletes. In this regard, the foregoing description of the simulated environments is presented for purposes of illustration and description. Furthermore, the description is not intended to limit the invention to the form disclosed herein. Accordingly, variants and modifications consistent with the following teachings, skill, and knowledge of the relevant art, are within the scope of the present invention. The embodiments described herein are further intended to explain modes known for practicing the invention disclosed herewith and to enable others skilled in the art to utilize the invention in equivalent, or alternative embodiments and with various modifications considered necessary by the particular application(s) or use(s) of the present invention. 
     Unless specifically stated otherwise, it shall be understood that disclosure employing the terms “processing,” “computing,” “determining,” “calculating,” “receiving images,” “acquiring,” “generating,” “performing” and others refer to a data processing system or other electronic device manipulating or transforming data within the device memories or controllers into other data within the system memories or registers. 
     One or more embodiments may be implemented in computer software firmware, hardware, digital electronic circuitry, and computer program products which may be one or more modules of computer instructions encoded on a computer readable medium for execution by or to control the operation of a data processing system. The computer readable medium may be a machine readable storage substrate, flash memory, hybrid types of memory, a memory device, a machine readable storage device, random access memory (“RAM”), read-only memory (“ROM”), a magnetic medium such as a hard-drive or floppy disk, an optical medium such as a CD-ROM or a DVR, or in combination for example. A computer readable medium may reside in or within a single computer program product such as a CD, a hard-drive, or computer system, or may reside within different computer program products within a system or network. The computer readable medium can store software programs that are executable by the processor  2032  and may include operating systems, applications, and related program code. The machine readable non-transitory medium storing executable program instructions which, when executed, will cause a data processing system to perform the methods described herein. When applicable, the ordering of the various steps described herein may be changed, combined into composite steps, or separated into sub-steps to provide the features described herein. 
     Computer programs such as a program, software, software application, code, or script may be written in any computer programming language including conventional technologies, object oriented technologies, interpreted or compiled languages, and can be a module, component, or function. Computer programs may be executed in one or more processors or computer systems.