• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    Method and computer program of automatic arbitration. The proposed arbitration method includes acquiring data (30) through a network of sensors (10) relative to several game elements (40) simultaneously; analyzing the acquired data (30) by detecting the presence of data groups (31) relating to game elements (40) and identifying the game element (40) to which they correspond; detecting game events (50) of various game elements (40) and detecting game landmarks by automatically detecting a sequence of game events (50) by triggering a notification signal (21). (Machine-translation by Google Translate, not legally binding)
    公开号:ES2680393A1
    申请号:ES201730234
    申请日:2017-02-23
    公开日:2018-09-06
    发明作者:Javier SIMON VILAR
    申请人:Foxtenn Bgreen SL；
    IPC主号:
    专利说明:

    METHOD AND PROGRAM OF AUTOMATIC ARBITRATION COMPUTER Field of the technique The present invention concerns an automatic arbitration method, or arbitration aid, implemented by at least one sensor network including laser sensors and at least one control device with ability to analyze the data sequences obtained from said sensor network, allowing the grouping of the data sequences into data sets and assigning them to a game element, mobile or fixed, to which the data sequences refer, identified from said analysis. The analysis of the data sets also allows identifying game events of each game element by generating a temporary record that can serve as an arbitration aid or that automatically detects sequences of game events identifying game milestones.
    State of the art
    Some methods, computer programs and automatic arbitration assistance systems are known in the state of the art. Document US20150018990A1 captures images via video cameras that
    later it analyzes detecting different objects and detecting different events related to said objects, creating a statistic. However, this document does not describe the detection of sequences of events that determine a game milestone, if the use of remote position sensors that offer information on the three-dimensional shape of the captured objects or information on their position that allows to detect moments of impact between said elements with sufficient precision to determine whether or not the events detected occur simultaneously or in a specific order that determines a game milestone.
    WO2016157152 describes a system that, by analyzing visual information obtained from cameras, allows to determine the three-dimensional position of a ball and of some players present in the playing area, as well as to calculate the trajectory of said ball by determining the point of impact between the ball and the player, as well as the point of impact of the ball on the playing area. However, this document does not anticipate the breakdown of the information captured by differentiating between the different game elements present in the captured images, nor the detection of milestones defined by a sequence of events, nor the use of precise position detection systems such as
    scanning lasers, radars, or three-dimensional video sensors. Document US7796162 describes the use of video cameras, which may optionally also incorporate a laser sensor, for the detection of the movement of game elements, but in no case proposes the use of position sensors that provide information indicative of the three-dimensional shape of the analyzed game element, neither the detection of game events nor game milestones composed of a specific sequence of game events.
    Document CN105536233 describes the installation of laser emitters and cameras around a game area, however it also requires the installation of sensors, emitters and laser reflectors on a belt that players place. The described system does not propose the automatic detection of game events or game milestones defined by sequences of game events.
    Finally, document ES2427489, of the same inventor, describes the use of laser scanners to make a prediction of a ball trajectory, and by means of video sensors capturing images of the impact of said ball in the impact zone to allow an arbitrator to determine if The ball is in or out of that line. However, said system does not describe the automatic detection of a game milestone defined by a sequence of game events, as it would be in this case to determine when the ball has hit the ground and if the ball is inside or outside the line of said game. moment, along with other possible previous events. Said document also does not anticipate disaggregating the information obtained by the sensors in different data groups, each one related to a game element to be analyzed, since only the analysis of the ball's trajectory is considered.
    Brief Description of the Invention The present invention concerns an automatic arbitration method, a computer program that implements said method, and may even concern a system in which to implement said method. The aforementioned method, system or program does not require the installation of sensors or reflectors or emitters of any kind on the players present in the game area, which could interfere with their freedom of movement or induce injuries.
    The present invention allows analyzing the development of a game or sport in a playing field by automatically detecting game events and game milestones relevant to the development of said game produced in relation to game elements.
    Non-limiting examples of such game or sport may be team sports such as football, football, rugby, basketball, baseball, cricket, hockey, volleyball, handball, water polo, or one player's sports against another player, such as tennis, table tennis , paddle, pediment, athletics sports such as racing, jumping, throwing, or sports with quality assessment in the accuracy of the development of routines, such as rhythmic gymnastics, trampoline jumping, synchronized swimming, rings, bars, colt, etc. Even other disciplines such as bowling, figure skating or ballroom dancing may be able to implement this method.
    It will be understood that the aforementioned game elements refer to those elements involved in the game. Examples of such game elements can be, in a non-limiting way, a ball, a racket, a bat, a net, but also the players and the different parts of their body, thus a player's foot will be considered game elements, a hand, an elbow, a head, the torso, etc. Static elements can also be considered game elements, such as a goalpost mast, a basket hoop, etc. Preferably, data relating to at least two mobile game elements will be analyzed.
    The aforementioned game events detected by the present invention refer to relevant acts that occur at a certain time during game development, and which may be indicative of a game milestone if they occur in correspondence with other game events, either simultaneously or later.
    The examples of such game events can be very varied, and depend heavily on the game or sport analyzed, however for clarity purposes some non-limiting examples of possible game events detected are listed, such as contact between a foot, a hand, a racket or a bat with a ball, the contact between a foot and the ground, the relative position between two game elements, such as between the most advanced body part of two runners, or between a attacker and a defender, or even the relative position between two parts of the same player's body, such as the aligned position of the gymnast's arms. The relative position between game elements and limits of the game area can also be considered game events.
    A game milestone will however be determined by a set of game events. Examples of game milestones will be for example a valid goal, a null goal, a valid basketball, a null basketball, a triple, an offside, a penalty, an out of band, a foul kick
    or null criminal, etc. These game milestones will or will not be determined based on a succession of detected game events. For example, in the context of a football match, an offside game will require detecting the ball chute game event by the midfielder and the detection of the defense overtaking game event with respect to the attacker, and the order of said two game events will determine the offside game milestone, a valid goal will be detected when the game event of the entry of the ball into the goal occurs and there are no previous game events that determine an offside game , penalty, out of band, etc. In basketball, a game event will be the jump of the player with the ball in his hand outside the triple line, and another game event will be the entry of the ball into the hoop, then detecting a triple game milestone.
    Thus, the present invention concerns, according to a first aspect, a method implemented by means of a system that includes at least:
     a network of sensors that include remote position sensors arranged around a game area and directed towards game elements within said game area;
     at least one control device equipped with a memory and capable of
    calculation for the analysis of the information obtained from the sensor network; Such remote position sensors will be understood to be sensors capable of obtaining position information of a game element remotely, from outside the game area.
    Said at least one control device will be for example a programmable logic controller, a computer, or the like, said control device being able to be local or remote with respect to said sensor network, said at least one control device receiving the data acquired by said sensor network through a data connection that can also be wireless.
    The proposed method includes the following stages: through said sensor network:
    a) acquire data relating to several game elements simultaneously, said data including position, time, and information indicative of the three-dimensional form of the game elements;
    and through an analysis of the acquired data executed by the at least one control device through the application of analysis algorithms:
    b) analyze the data obtained from each individual sensor by detecting the presence of data groups related to game elements and identifying the game element to which said data groups correspond, matching said data groups related to the same game element ;
    c) grouping in a temporary sequence all the data groups provided by different sensors corresponding to the same game element in temporary coordination;
    d) detect game events of several game elements in several time sequences of data groups by:
     the detection of changes in position, shape, speed and / or trajectory of the game elements in the time sequences of data groups;
     the detection of interference or correlation between different game elements in the time sequences of data groups;
    or a combination thereof, e) detecting game milestones by automatically detecting sequences of game events, simultaneous or consecutive, coinciding with sequences of game events pre-stored in memory corresponding to possible game milestones, triggering a notification signal Thus, during step a) of the method, data relating to the different game elements existing in the game area are captured, preferably obtaining data from each individual game element simultaneously from at least several remote position sensors placed in different positions around the game area, thus allowing data on each game element to be obtained from different angles
    simultaneously preventing a game element from preventing the capture of data from another game element by hiding it from a remote position sensor. Preferably data will be obtained from all existing game elements in the area
    of game.
    During step b) the data obtained from each individual sensor is analyzed and data groups are identified relative to a single game element among the data obtained from said sensor. For example, a sensor can obtain simultaneous data from several game elements, for example from several players close to each other, or from various parts of the body of the same player such as his feet, knees and hands, or a ball and a foot, etc., the analysis of step b) makes it possible to discern from all the data obtained by said individual sensor the groups of data that refer to each of said different game elements, and allows to identify which game element they refer to. That is to say that step b) allows to isolate, among all the data obtained, those data constituting a group of data obtained from a single game element, and also allows to identify which game element they correspond to, for example by identifying if they are a group of data relating to a ball, a bat, a racket, a foot of a defender, etc.
    As an example, during said stage b) two scanning lasers and two cameras each obtain data from the different game elements related to two players and a ball, that is to say four feet, four hands, two torsos, two heads, and the aforementioned ball, from different points. During stage b) said game elements are detected and identified and the data groups of each game element obtained by each of the sensors are isolated, that is to say, what data obtained refers to the right foot of the first player is detected, what data refer to the ball, etc.
    Said detection and identification can be carried out, for example, by detecting the shape of said game elements by analyzing the position data of a point mesh of each game element, which provides three-dimensional information thereof, said detected form. it can be compared to a pre-stored record, that is, for example, it can be detected that a spherical element is the ball. Alternatively, such identification can be obtained by a two-dimensional color and shape analysis of the images obtained by the cameras, for example if it is round and white is the ball. This analysis can also identify if a player is from one team or another, and therefore identifying their game elements, such as the feet, depending on the color of their clothing. Another alternative is the detection of characteristic movements of said game element, for example that of the steps of the feet. A game element can also be detected by being different from the data obtained at another time in that same position, or by being different from the background of the game area.
    Stage c) groups all the data groups obtained from different sensors of the sensor network and identified as relative to the same game element, creating time sequences of data groups, each time sequence relating to a single game element, coordinating said groups of data obtained from different sensors in time, obtaining a record of all the groups of data acquired simultaneously referred to the same game element. This makes it possible to coordinate the data acquired from different angles, or even the data acquired by sensors of different nature, which are proposed to be integrated into the sensor network.
    Stage d) allows to detect game events, for example that a foot has touched a ball
    or the ground, that the ball has touched a racket, a bat or a midfield net, or that a game element is ahead of another game element, such as a runner advancing another runner, or a defense ahead of an attacker, other examples of game events may refer to the same player's game elements, for example, to detect when both arms of the same player are cross-aligned, this being an important game event for example in gymnastics with rings
    Said detection of stage d) is carried out by detecting changes in position, shape, speed and / or trajectory of the game elements in the time sequences of data groups, that is, detecting changes in their movement or indicative form, for example, that a Game item has come into contact with another game item that has modified its movement or shape. Alternatively or in addition, said detection of step d) is produced by detecting interference or correlation between different game elements in the time sequences of data groups, that is, by detecting when the positional information of a game element interferes with the positional information of another game element, thus detecting an impact between them, or detecting when the positional information of a game element acquires a pre-established relative position with respect to another game element, said pre-established relative position being preferably selected from a list of possible positions Relative stored in memory.
    As a result of said detection of game events, a record of game events with assigned temporal information is obtained, that is, a record of what important acts, called game events, have occurred in the game area, and when these game events have occurred. happened. This allows automatic identification of game milestones during stage e), said game milestones being detected when there is a sequence of simultaneous game events or in a certain order. These game milestones will correspond to the
    arbitral decisions to judge by the proposed method. As an example, a milestone may be to determine an offside in football. For the purpose of determining said game milestone, the proposed method shall detect the game event of the attacking ball's exit, detect the game event of the advancement of the most advanced body part of the most advanced attacker, discarding the arms , regarding the most backward defense in the playing area. The succession of these two game events in an order determines the offside game milestone, but in the reverse order it would not correspond to an offside game milestone. In addition, more game events can be taken into account to determine said offside game milestone, such as if the ball leaves the goalkeeper's foot on the goal kick, or a player from the corner on a kick-off. corner, cases in which there is no offside.
    It will be understood that this is only an example and that the proposed method can be applied by an expert to a multitude of different games and to a multitude of possible different game milestones within each game without a detailed description of each case being necessary in this document. .
    Another intended embodiment proposes that said detection of game events of step d) be carried out as a result of a start trigger, and is carried out within a time frame containing a fraction of the time sequences of data groups, wherein said Start trigger provides a temporary reference that defines the time frame on which the detection is performed.
    In other words, the search for the game event is only executed in response to a start trigger that provides a time frame on which to perform the detection, allowing further analysis resources to be optimized.
    Said start trigger may be, for example:
     a manual detection of a possible game milestone introduced into the system by an operator, said possible game milestone being produced within said time frame indicated by said operator;
     a manual detection of a game event introduced into the system by an operator, said game event being produced at a time of the game indicated by said operator defining said time frame, said game event being manually detected used in said stage e ) detection of game milestones;
     the automatic detection of a relevant sound through at least one microphone integrated in the sensor network by means of sound recognition analysis on the data acquired by said microphone; or
     the automatic detection of a game milestone through said stage e), said
    game milestone indicative of another possible game milestone. The detection of a possible game milestone indicates the system the time frame in which to execute the analysis in search of game events that subsequently determine a game milestone, thus allowing to optimize the analysis resources. An operator may indicate that within a time frame there has been, for example in the case of football, an offside, a goal, an out of band, a foul, a penalty, hands, etc. In the case of other sports such as tennis, other possible game milestones can also be indicated, such as a lack of foot (foot fault in English), incorrect kick, etc.
    The manual detection of a game event by an operator determines the existence of a game event at a specific time in the game, which triggers the automatic search for other game events within a time frame related to that moment for detection. of game milestones by analyzing the combination of the game event detected manually with the game events detected automatically. Said manual detection can be carried out, for example, by a slow-motion review of images captured by a camera integrated in the sensor network.
    According to another embodiment, the system automatically searches for, from a manually detected game event, other game events related to said manually detected game event through a shared milestone. That is, for example in the case of football, when an operator manually determines the exact moment in which the ball separates from the attacking player's foot to make a pass, the system analyzes the data obtained from the sensor network in that same moment to determine if the other game event that would determine a game milestone corresponding to an offside occurs, said other game event being the presence of an attacking player more advanced than the most backward of the defenses.
    The mentioned sound detected can be for example an impact sound, such as the sound of a bat or a racket hitting a ball, or it may be the sound of a referee's whistle. In this case, the whistle whistle would perform the analysis and allow the said arbitrator to advise, corroborate or deny in a few seconds.
    Finally, the previous detection by the system of a game milestone may be indicative of an additional game milestone related by said previously detected game milestone, which triggers an additional search for other game events by said step d), incorporated in stage e) for the detection of additional game milestones. For example, a game milestone can be the detection of a pass between two players of the same team, and this can trigger the search for other game events that allow to check if said pass has been regulatory, for example by looking for the relative position of the players. players at the time of the pass in order to automatically determine whether or not there was an offside, or another foul contrary to the rules of the game analyzed.
    Preferably the first execution of stage d), whose results determine the detection of a game milestone in stage e), is performed in search of game events of a first group of game events. Once said game milestone indicative of another possible game milestone is detected, the additional execution of step d) is performed in search of game events selected from a second group of game events, selected in relation to the possible game milestone indicated for the game milestone already detected.
    Alternatively to the realization of said detection as a result of a start trigger, the detection of game events of step d) will be performed in real time on all time sequences of data groups.
    Another embodiment proposes that step d) be executed in real time looking for a game event selected from a first group of game events and where the detection of a game event of said first group of game events triggers an execution as trigger additional stage d) in a time frame related to said game event of the first group detected in search of a game event of a second group of game events being all the game events detected used in stage e). For example, a game event of the first group may be the entry of a ball into a scoring zone such as a goal, a basketball basket, or the entry of a ball into an area outside the field of play, the impact of a ball over a certain game element, etc. From said detection of game events of the first group another more detailed search of other game events of the second group is executed, for example game events that require greater calculation capacity for its search, within a time frame defined by said Game event of the first group. This embodiment allows to optimize the system calculation resources by searching for game events of the second group only when a first detection of game events of the first group indicates the possible presence or relevance of the events
    of play of the second group. According to another embodiment of the present invention, step d) also includes the detection of interference between data groups of a game element and pre-stored game zone limits, also detecting game events that are incorporated into the detection of game milestones of stage e). That is, for example, the detection that a ball has crossed an out-of-band line or a midfield, or area, or goal line will be determined by comparing the position data of the game element with said pre-stored record. of the limits of the playing area, being in this embodiment said limits not necessarily detected through the data obtained from the sensor network, but entered into the memory before the start of the game, simplifying part of the task of analyzing the data obtained by the sensor network. It will be understood that the position of said limits of the playing area will correspond to the position of the lines drawn on the ground and that they indicate some limits related to game milestones, such as the limit where a player can be, or a ball, as in the case of the lines of band judge in football or tennis, or a limit that determines a different score such as the triple line in basketball.
    Additionally, it is proposed that the notification signal be transmitted by wireless means to a mobile receiver. For example it can be transmitted to a smart watch, mobile phone, tablet or similar of the referee, providing additional information for decision making. Alternatively, said notification signal may be a visual or acoustic signal emitted in the form of a warning or warning, or a signal stored in a notification signal register.
    These remote position sensors can be selected from:
     laser sensors, for example scanning laser sensors, of pulses for the simultaneous detection of the position of multiple points, or of a single fixed beam to measure the distance between a point and the laser emitter;
    Radars;
     flight time video sensors that obtain position information by calculating the time it takes for a light emitted to bounce and be captured by said video sensor;
     three-dimensional video sensors composed of several video cameras separated by a defined distance known as the position information automatically inferred by the discrepancies between the images captured by
    said several cameras. Said remote position sensors offer information indicative of the three-dimensional shape of the game elements thanks to a matrix of position measurements at different points, the position being all the aforementioned points determined at the same time, or at successive almost simultaneous moments, with temporary differences less than the tenth of a second.
    Said position information indicative of the three-dimensional form will allow to recognize the shape of each game element, and to know its position and its displacement over time.
    Each of the two video cameras that make up a three-dimensional video sensors will capture different images from different points of view, and the treatment and comparison of said images captured by a three-dimensional recognition computer program will allow to calculate the position of each of the game elements captured in the images by measuring the differences between both images.
    Additionally or alternatively it is proposed that said sensor network also includes sensors selected from:
     video cameras, where during said stage b) an analysis of shape and / or color recognition is performed on the data acquired by said video cameras;
     at least one microphone, wherein during said stage b) a sound recognition analysis is performed on the data acquired by said microphone for the detection of relevant sounds, indicative of a game event;
     sensors integrated in the game elements, such as position sensors, accelerometers, inclinometers, whether integrated into parts of the players, such as bracelets, boots, belts, etc., whether in the ball if it exists, or other elements of I play mobiles like bats, rackets, etc. or static, like poles. All those sensors integrated in mobile game elements must include a wireless information transmitter to communicate the information obtained to the system.
    Such sensors will not offer position information, but may provide other information complementary to the position information obtained from the remote position sensors, such as chromatic information of the game elements obtained by the video cameras, or sound information indicative of a game event obtained through microphones.
    The aforementioned video cameras and the three-dimensional video sensors described above can be the same sensor that offers both position information and color information.
    The detection of game events of step d) is preferably performed on the time sequences of data groups in search of patterns matching a pattern record of possible game events pre-stored in memory. That is to say, within a temporal sequence of data groups relative to a game element already identified in stage b), patterns that reveal a game event are searched, said pattern search being carried out in relation to a registration of possible patterns. Game events pre-stored in the memory of at least one control device. Thus, the detection of a pattern in the data groups equivalent to a possible game event pattern determines the existence of a game event in said data group, and therefore the existence of a game event related to said element. of play at a certain time.
    According to another preferred embodiment, the detection of a game event contained in the pattern register of possible game events acts as a trigger for a search for additional related game events through a game milestone shared with said detected game event, being the patterns of said additional game events detected in comparison to a pattern record of possible additional game events, and said search for additional game events being performed within a time frame containing a fraction of the time sequences of data groups at less simultaneous to the trigger.
    That is, once a game event is detected, other additional game events are determined that are related to said game event detected through a shared game milestone, for example the detection of the game event of the kick of a penalty in football. will be related to the game event of the non-entry of other players in the area until after said kick is made. Therefore, after the detection of the first game event, a specific search of the other additional game events related to the first one is performed within a time frame defined by said initial game event, said time frame being at least partially retrospective, containing groups of data prior to the initial game event.
    This allows to optimize analysis resources allowing to perform a first search of game events and only after the detection of any of said game events proceed to search for other additional game events but only within the defined time frame.
    It is also proposed to generate, for each game element detected in the game area, statistical data related to said game element obtained from the game events detected related to said game element. This allows to automatically generate statistics relating to each game element, or groups of game elements, which can be useful both at the informational level and at the level of analysis to improve the performance of the athletes present in the game area.
    Preferably said statistical data is transmitted in real time to a remote storage device, for example a sportsbook server, sports journalists or commentators, sports media, such as televisions, radios
    or newspapers, etc.Game events and / or game milestones detected can feed in real time a
    augmented reality system that superimposes visual information related to said game events and / or said game milestones on real images of the game area. In other words, said game events and / or detected game milestones can feed into
    real time an augmented reality system that superimposes visual information related to said game events and / or game milestones on real images of the game area captured through cameras integrated in the sensor network. Examples of possible data fed by said augmented reality system can be: information on the time of possession of a player's ball, fouls committed or received, time played, the number of passes made or received, the number of goal shots, etc.
    Said analysis of step b) is preferably performed on the data captured by the sensor network in search of patterns coinciding with a record of some patterns of possible game elements pre-stored in the memory, said record may contain shape patterns. , color and / or position of possible game elements.
    That is to say, the recognition of the groups of captured data relative to a game element and indicative of what game element is performed by analyzing said data in search of patterns matching a pattern register of possible pre-stored game elements, preferably detecting shape, color and / or position of said game elements.
    By way of example, it can be indicated that all data relating to a spherical object will be indicative of a group of data relating to a game element identified as a ball. Likewise, the shape of a bat or racket will be characteristic and identifiable, even the shape of a boot, hand, or head will be easily recognizable. Even the shape of a number printed on the player's shirt can be recognized by the proposed method for the identification of said individual player as a game element or as a set of multiple game elements including his feet, knees, hands, elbows, shoulders, head, torso, etc.
    The chromatic information can be of help for the identification, for example the white color of the ball will help its detection, or the color of the clothes of the players or the referee can be used by the system to discern between them.
    Also the position information can be used for the detection and recognition of the game elements. For example, players' feet will usually be near or above the ground.
    In some sports such as baseball each player has an assigned position within the playing area, such as the pitcher, the receiver, the first base, the second base, etc., therefore the detection of a group of data within a of these positions will undoubtedly correspond to an element of play related to each of said players, thus facilitating their recognition.
    It is also proposed that during the analysis of step b) a detection of groups of data relative to a game element be performed in the data coming from a remote position sensor, and where the position information of said game element obtained of said remote position sensor is compared with the existing position information in the data of the other remote position sensors detecting a spatio-temporal coincidence between said compared data, assigning said detection of data groups relative to a game element to all the data groups of all remote position sensors with spatio-temporal matching.
    That is to say that the detection of a game element in a data group from among the data coming from an individual remote position sensor is automatically used to assign other data groups obtained from other sensors to that same game element if there is space correspondence -Time between these groups of data from different sensors. In other words, if two remote position sensors detect position data in the same space and time, and the analysis of the data of one of the remote position sensors determines that said data is a group of data relative to for example a ball , the data of the other sensors obtained from that same space and time will also correspond to data of said ball, without the need for an additional analysis of said data.
    It is also contemplated that said analysis of stage b) is performed on data obtained at different times, and that the detection of a game element at a time be used to perform the detection of said game element at different times, by monitoring of the position of said game element. That is to say, the detection of a game element at one time makes detection at other later or previous moments unnecessary, being able to track the trajectory of said game element from the moment in which its identification has been made maintaining the identification without requiring additional analysis while the detection of its trajectory is maintained through the analysis of the data obtained, said monitoring of the trajectory being a much simpler calculation than the identification of the game element and therefore optimizing the resources.
    A second aspect of the present invention concerns a computer program that includes code instructions that when executed in a computer system, provided with at least one control device with a memory and with computing capacity, implement the method of any of claims 1 to 14 described in relation to the first aspect of the present invention.
    Preferably said code instructions include analysis algorithms configured to analyze the data obtained from each individual sensor by detecting the presence of data groups relating to game elements and identifying the game element to which said data groups correspond, matching said groups of data referring to the same element of the game, grouping in a temporary sequence all the groups of data provided by different sensors corresponding to the same element of the game in temporal coordination.
    Said analysis algorithms are preferably also configured to detect game events of several game elements in various time sequences of data groups by:
     the detection of changes in position, shape, speed and / or trajectory of the game elements in the time sequences of data groups;
     the detection of interference or correlation between different game elements in the time sequences of data groups;
    or a combination thereof, and
    Said analysis algorithms may be additionally configured to detect game milestones by automatically detecting sequences of simultaneous game events.
    or consecutive, coinciding with sequences of pre-stored game events corresponding to possible game milestones, triggering a notification signal.
    A third aspect of the present invention concerns a system for automatic arbitration that includes at least:
     a network of sensors for obtaining position, time, and information information indicative of the three-dimensional shape of game elements, said network of sensors including remote position sensors arranged around a game area and directed towards elements of game inside said game zone focusing on several game elements simultaneously;
     at least one control device provided with a memory and with calculation capacity for the execution of analysis algorithms on the information obtained from the sensor network;
    wherein said at least one control device constitutes a computer system configured to execute a computer program that includes code instructions that implement the method of any of claims 1 to 14 described in relation to the first aspect of the present invention.
    Preferably said code instructions include analysis algorithms that are configured to analyze the data obtained from each individual sensor by detecting the presence of data groups relating to game elements and identifying the game element to which said data groups correspond, matching said data groups referred to the same game element, grouping in a time sequence all the data groups provided by different sensors corresponding to the same game element in temporary coordination;
    Said analysis algorithms may also be configured to detect game events of various game elements in various time sequences of data groups by:
     the detection of changes in position, shape, speed and / or trajectory of the game elements in the time sequences of data groups;
     the detection of interference or correlation between different game elements in the time sequences of data groups;
    or a combination thereof.
    Said analysis algorithms may be additionally configured to detect game milestones by automatically detecting sequences of simultaneous game events.
    or consecutive, coinciding with sequences of pre-stored game events corresponding to possible game milestones, triggering a notification signal.
    It is also proposed that these algorithms be the result of learning algorithms, whether for example through the automatic detection of patterns within a large data source, by techniques known as "big data" or "data mining", or by means of automatic detection of patterns within data provided from examples related to game events or game milestones to be detected, using techniques known as "deep learning". Obviously said feature may also be related to the first and second aspects of the invention.
    The system and the computer program required for the application of the additional features described in relation to the first aspect of the invention, concerning a method, can be obvious to an expert through a configuration of the systems and algorithms described above for the realization of said method, in view of the detailed description of the method described above.
    Other features of the invention will appear in the following detailed description of an exemplary embodiment.
    BRIEF DESCRIPTION OF THE FIGURES The foregoing and other advantages and features will be more fully understood from the following detailed description of an exemplary embodiment with reference to the attached drawings, which should be taken by way of illustration and not limitation, in which:
    Fig. 1 shows a schematic plan view of a playing area which, by way of example, has illustrated a basketball court with its corresponding limits, containing several game elements corresponding to five players of each team, a ball and two baskets, around said play area, a sensor network composed of twelve remote position sensors and a microphone arranged around the game area, oriented inwards inside the game area, are also schematically illustrated, indicating in line discontinues the zone controlled by each individual sensor;
    Fig. 2 schematically shows part of step b) applied to data indicative of the three-dimensional shape of the game elements, exemplified here in the form of an image that is assumed to be three-dimensional, in which said image contains various game elements and it is analyzed and broken down into groups of data assigned to each of said game elements;
    Fig. 3 shows the same as Fig. 2 but applied to data obtained through another
    sensor, showing different game elements; Fig. 4 schematically shows the steps c), d) and e), showing how the data sequences are put into temporal correlation and how game events are detected corresponding to each of the analyzed game elements, and how said game events are arranged in a sequence that allows you to identify game milestones;
    Fig. 5 shows how other additional data are also analyzed in search of game events, in this example audio data captured by the microphone of the sensor network is analyzed by detecting the presence of an audio pattern corresponding to a game event that in this example is the sound of the siren of the end of the time of possession;
    Fig. 6 shows how said game event detected in the microphone data is mapped to the other data streams allowing other additional game milestones to be detected.
    Detailed description of an exemplary embodiment The attached figures show exemplary non-limiting examples of the present invention.
    Fig. 1 shows a play area 1 corresponding to a basketball court. It will be understood that any other playground 1 may be used in its place, such as football, football, baseball, cricket, handball, hockey, volleyball, tennis, paddle, or athletic, jumping, throwing, gymnastics, or jump pools, synchronized swimming, etc.
    The play area 1 shown is surrounded by a network of sensors 10 that integrates thirteen individual sensors 11 of which eight are remote position sensors 12 and one is a microphone 13. Obviously the number and position of the individual sensors 11 can be another without this substantially affecting the present invention. Said remote position sensors 12 may be for example scanning laser sensors, high precision radar sensors, or three-dimensional video sensors, the use of scanning laser sensors being the preferred embodiment.
    Although the data 30 obtained by said remote position sensors are data indicative of the three-dimensional shape of the game elements, that is, three-dimensional information. In the following figures, these three-dimensional data obtained in the form of a two-dimensional image have been shown in a simplified manner to facilitate its understanding.
    Fig. 2 shows, in a first box, a two-dimensional representation of the data 30 obtained at a given time by one of the remote position sensors 12, said data 30 containing information relating to three game elements 40 corresponding to the right hand of a first player, the left hand of a second player and the ball.
    Said data 30 is supplied to at least one control device 20 which, by applying analysis algorithms, analyzes said data 30 by detecting the presence of data groups 31 relative to individual game elements 40 and identifying the game element 40 to which said data groups 31 correspond. In the present example, said analysis allows to automatically identify the data groups 31 corresponding to each of the aforementioned three game elements 40, for example by an analysis of the shape of each of said elements. of game 40 that allow identifying the characteristic shape of a hand and a ball, as well as distinguishing which player corresponds to that hand thanks to the recognition of the color of the player's shirt and / or the number and / or name printed on said shirt , or other distinctive morphological characteristics of each individual player, such as their height, hairstyle or hair color c characteristic, etc.
    All the aforementioned data groups 31 referred to the same game element 40 are then mapped, which will mainly correspond to data groups 31 of the same game element 40 obtained from different individual sensors 11, being part of the redundant information , for example the position information, which allows to identify said correspondence facilitating said operation and avoiding having to perform an automatic identification of all the data of each of the individual sensors 11 since an identification in the data of an individual sensor 11 allows, by means of said correspondence, avoid having to perform said identification with the data of the remaining individual sensors 11.
    Fig. 3 shows an operation equivalent to that shown in Fig. 2 but applied to other data 30 relating to other game elements 40 obtained by another remote position sensor 12. In this case the game elements 40 identified are the feet right and left of the first player and the triple line.
    Alternatively, the position of the triple line boundary may be pre-stored in memory, making it unnecessary to detect and identify said line in the data 30 obtained from the sensor network 10.
    Fig. 4 shows the three time sequences of data groups 31 obtained from the analysis shown in Fig. 2 correlated, represented here in the form of a newly integrated two-dimensional image, and how said time sequences contain information of different successive moments. of the game, which here has been simplified as four sequential images. The analysis carried out by said at least one control device 20 by means of the application of analysis algorithms allows to identify the moment in which the ball separates from the hand of the first player; thus determining that at the moment three a first game event 50 occurs.
    In an equivalent manner, the three time sequences of data groups 31 obtained from the analysis shown in Fig. 3 have also been correlated with each other and in temporary coordination with the remaining time sequences. His analysis determines that at the moment four the right foot of the first player steps on the triple line, thus determining that this is a second game event 50.
    Therefore, it can be determined that the throwing of the ball has taken place, on the part of the first player, before said first player stepped on or exceeded the triple line, since the third moment is before the fourth moment. Therefore it can be concluded that a game milestone has occurred, corresponding to a valid triple launch.
    The analysis in search of the second game event 50 can be triggered as a result of the detection of the first game event 50. That is to say that upon detecting that the ball leaves the hands of the first player the system checks a time frame close to that moment in which search for a game event 50 related to the position of your feet, thus detecting the second game event 50.
    The first game event 50 detected, corresponding to the separation of the ball from the player's hands, can also be searched by the system as an automatic response to a starting trigger, for example the entry of the ball into the basket. Said game event 50 of hitting the ball can trigger the search for the moment in which the ball leaves the player's hands retroactively and one also looking for the event of the player's feet stepping on or overcoming the triple line. Once both game events have been detected, as a result of the detection of the entry of the ball into the basket, the sequence in which said game events 50 have occurred to determine if there has been a triple game milestone has been verified.
    On the contrary, the system can search in real time all game events 50
    possible simultaneously, detecting them while they happen.An audio data stream is shown in Fig. 5 as an acoustic waveformcaptured by a microphone 13 integral to the sensor network 10.
    The analysis of said audio data 30 allows to detect a sound identified as the siren of the end of the possession time, by detecting a pattern in the acoustic wave coinciding with a pre-stored pattern of the sound of said siren, so that determine that this is a third game event 50 that happens in a fourth moment.
    In Fig. 6 the same analysis is performed as in Fig. 4 but adding the audio data shown in Fig. 5, each time fraction of said data 30 being coordinated with the time fraction of the remaining data 30.
    As a result, the method detects a triple shooting game milestone thanks to the detection of the launch in the third previous moment both at the end of the possession time and to exceed the triple line, both events occurred in the fourth moment. All of this determines a valid triple shooting game milestone.
    A further detection of a fourth game event corresponding to the entry of the ball into the basket would determine a triple basket game milestone as the triple shot is valid.
    As will be evident, the measurement of possession time can also be carried out by the proposed automatic arbitration method, so that the detection of the game event 50 of the end of the possession time could be performed internally as an additional game event 50.
    Many other examples could be exposed, for example the valid launch of a foul in football without the barrier players leaving their position early, or a valid penalty shot also in football without any player entering the area ahead of time, or in tennis a valid kick-off without the player stepping on the line before hitting the ball, etc.
    In other embodiments the detection of game events 50 can be determined for example by detecting a sharp change in the trajectory or speed of a game element, if for example a ball suddenly changes its trajectory or speed is indicative that another game element 40 has hit her, or has touched the ground. In the same way a bat or racket will also see its trajectory or speed altered when hitting the ball. Said impact could also produce an alteration of the shape of the game element 40, for example a ball could temporarily lose its spherical shape during the impact.
    In addition, the proposed method allows to know the position of each game element 40 through the captured data groups 31, thus in case two game elements 40 come into contact with said position data of the corresponding data groups 31 they will become at least partially coincident, thus demonstrating that such contact has occurred and the game event 50 is detected.
    Some game events do not require contact between different game elements 40. For example, the offside of football requires a relative position between the most advanced part of the body of two players in relation to the field, excluding the arms, a case similar to the arrival at the finish line of the races. In other sports the measurement of the relative position between two parts of the same player's body may be relevant, such as in gymnastics disciplines. In all these cases, said game event 50 will be determined by analyzing the position data contained in the corresponding data groups 31 of the time sequences of each game element 40, analyzing their relative positions, their correlations or their interferences.
    The detection of a game milestone will trigger a notification signal 21 that will preferably be transmitted by wireless means to a mobile receiver 22 such as a tablet, phone or smart watch in the hands of an arbitrator.
    It will be understood that the different parts constituting the invention described in one embodiment may be freely combined with the parts described in other different embodiments even if said combination has not been explicitly described, provided there is no harm in the combination.
    The following are other examples of realization related to the automatic detection of game milestones corresponding to an offside game in a football match, shown in Fig. 7.
    According to one embodiment, the system analyzes the captured data 30 by detecting the presence of data relating to the different game elements 40 and identifying them, which in this case will correspond to the different parts of the bodies of the attacking and defending players as well as the ball, breaking said data 30 into data groups 31 and grouping the data groups 31 relative to the same game element 40 obtained from different individual sensors 11 in the same time sequence.
    The system constantly analyzes the data groups 31 looking for at least one game event 50 of starting the ball pass, a game event of receiving the ball pass, and a game event of anti-regulatory position of each of the attacking players with respect to the most backward defense. The game milestone corresponding to the offside will be determined if the game events corresponding to a player's anti-regulatory position (called out of positional play), at the start of the pass, and the reception of said pass are detected in this order. pass by said player in an anti-regulatory position, or if it is determined that at the time of the start of the pass the player who will receive said pass is in an anti-regulatory position.
    In the example shown in Fig. 7 it can be seen how at the moment 2 the ball separates from the foot of the player who starts the pass, determining at that moment a game event 50 corresponding to a start of the ball pass has occurred. It is also determined that at a time before the moment 2 and after the moment 1 an attacking player advances with the end of his foot the position of the most backward defense player, determining an anti-regulatory position of said player before the start of the pass of the ball. Finally, in a memento 4 a game event 50 is detected corresponding to a reception of the ball pass by the attacking player who has been determined to be in an anti-regulatory position previously. Therefore the detected game events are, in chronological order, a player in an anti-regulatory position, a start of a pass, and a reception of the pass by said player in an anti-regulatory position, which determines a game milestone corresponding to an offside, which is automatically notified by the system by means of an alarm signal, for example transmitted to a
    smart watch of the referee. According to an alternative embodiment, at least one game event 50 of beginning of the ball pass and one game event 50 of reception of the ball pass will be automatically searched in the time sequences, but not a game event 50 of each antiregulatory position of each of the attacking players with respect to the most backward defense.
    The detection of a game event 50 of the start of the ball pass and of a game event 50 of reception of the subsequent ball pass will be identified by the system as a game milestone corresponding to a pass.
    The system will be configured so that the detection of a game milestone corresponding to a pass is a trigger for the verification of the existence or not of an offside, so that detection of a game milestone corresponding to a pass triggers the analysis of the relative position of the player receiving the pass with respect to the most backward defense at the instant of the first detected game event 50 corresponding to the start of the pass, thus detecting if there is another game event 50 corresponding to the attacker's anti-regulation position with respect to the defense in that moment, thus determining the existence or not of a game milestone corresponding to an offside. This realization requires less calculation capacity, since only the relative position of an attacking player must be detected with respect to the most backward defense when he receives the pass and only at a certain moment.
    Another intended embodiment for the detection of an offside is that an operator indicates to the system a time frame of reference within which it is suspected that there has been an offside, for example a time frame between moments 1 and 4, and the system applies any one of the two alternative methods of analysis described above but only with respect to the data contained within said time frame, thus achieving a greater optimization of the available calculation resources.
    Alternatively, said operator can determine, by means of a slow-motion examination of images captured by a camera integrated in the sensor network 10, the exact moment at which the game event 50 corresponding to the start of the pass occurs, that is to say the moment in which that the ball leaves the foot of the attacking player, which in the example shown in Fig. 7 corresponds to moment 2. Once the existence of a triggering game event 50 corresponding to a start of the ball pass is determined manually, the system automatically determines by analyzing the data 30 captured in search of game events 50 the game event 50 corresponding to the reception of the pass, thus determining which is the player receiving said pass, and the game event 50 corresponding to the position anti-regulation or not of said player receiving the pass at the time of the game event 50 corresponding to the start of the determined ball pass or manually, that is to say if said player was in an antiregulatory position at the time of said start of the ball pass, thus automatically determining whether or not there was a milestone corresponding to an offside.
    Similarly, the system can be used for the automatic detection of a correct launch of a foul, detecting at least 50 game events relative to the start of the throw, when the ball leaves the player's foot, and relative to the position of the players of the defense at least 9,15m away from the point of the ball throwing, and can also perform a search for other game events such as the entry of the ball into the goal, or the contact of the ball with another player other than the thrower of the fault, etc. Said gaming events 50 detected can be detected in real time, or within a time frame indicated by an operator, or one of them being manually detected by an operator, or its search being initiated following a trigger. In this case, the trigger could be, for example, the detection, by means of a microphone 13 integrated in the sensor network 10, of the referee's whistle sound indicating that the launch can be made.
    Likewise, the system can be used for the automatic detection of a correct penalty kick, detecting game events 50 relative to the start of the penalty kick, when the ball leaves the player's foot, relative to the goalkeeper's position on the goal line. goal, relative to the position of the other players outside the area, and relative to the entry of the ball into the goal. Said game events 50 detected can be detected in real time, or within a time frame indicated by an operator, one of them being manually detected by an operator, or its search being initiated following a trigger.
    Obviously the proposed method and system can be applied to other sports and to the detection of other different game landmarks. For example in tennis, a game milestone related to a lack of foot, known as foot fault, shown in Fig. 8, can be detected by detecting game events 50 relative to the start of the throwing throw, when the ball is separates from the racket, and relative to the position of the feet of the player making the throw in relation to the baseline of the track. If the entry of one of the player's feet is detected within the playing area before the start of the throwing throw is determined that there is a game milestone corresponding to a lack of foot, otherwise a milestone is determined. valid serve throw. Said gaming events 50 detected can be detected in real time, or within a time frame indicated by an operator, one of them being manually detected by an operator, or being its
    5 search started following a trigger. In the example shown in Fig. 8, the system automatically detects a game event 50 corresponding to an entry of a player's foot into the playing area, stepping on the baseline, at time 3, simultaneously with the impact of the ball on the racket. However, the corresponding game event 50 at the start of the service, when the ball is separated from the racket, does not occur until now 4. Therefore, it is automatically determined that there is a game milestone corresponding to a lack of foot, being therefore a null serve.
    权利要求:
    Claims (19)
    [1]
    1. Automatic arbitration method implemented through a system that integrates at least:
     a network of sensors (10) formed by individual sensors (11) that include remote position sensors (12) arranged around a game area (1) and directed towards game elements inside said game zone;
     at least one control device (20) provided with a memory and with calculation capacity for the analysis of the information obtained from the sensor network (10); characterized in that said method includes the following steps: by means of said sensor network (10): a) acquiring data (30) related to several game elements (40) simultaneously,
    said data including position, time information;
    and by an analysis of the acquired data executed by the at least one device of
    control (20) by applying analysis algorithms:
    b) analyze the data (30) acquired by each individual sensor (11) by detecting the presence of data groups (31) related to game elements (40) and identifying the game element (40) to which said data groups correspond (30), matching said groups of data (30) referring to the same element of the game (40);
    c) grouping in a time sequence all the data groups provided by different individual sensors (11) corresponding to the same game element (40) in temporary coordination;
    d) detecting game events (50) of various game elements (40) in various time sequences of data groups (31) by:
     the detection of changes in position, shape, speed and / or trajectory of the game elements (40) in the time sequences of data groups (31); or
     the detection of interference or correlation between different game elements (40) in the time sequences of data groups (31); or a combination thereof, and e) detecting game milestones by automatically detecting sequences of game events (50), simultaneous or consecutive, coinciding with sequences of
    Game events (50) pre-stored in memory corresponding to possible game milestones related to pre-stored game rules or with circumstances predefined by the user, triggering a notification signal (21).
    [2]
    2.  Method according to claim 1, wherein the detection of game events (50) of step d) is carried out as a result of a start detonator, and is performed within a time frame containing a fraction of the time sequences of groups of data (31), wherein said start trigger provides a time reference defining the time frame on which the detection is performed.
    [3]
    3.  Method according to claim 2 wherein said start trigger is:
     a manual detection of a possible game milestone introduced into the system by an operator, said possible game milestone being produced within said time frame indicated by said operator;
     a manual detection of a game event (50) introduced into the system by an operator, said game event (50) being produced at a time of the game indicated by said operator defining said time frame, said game event being ( 50) manually detected used in said step e) of detection of game milestones;
     automatic detection of a relevant sound through at least one microphone
    (13) integrated in the sensor network (10) by sound recognition analysis of the data acquired by said microphone (13); or
     the automatic detection of a game milestone through said stage e), said game milestone being indicative of another possible game milestone.
    [4]
    Four.  Method according to claim 1 wherein the detection of game events (50) of step d) is performed in real time on all time sequences of data groups (31).
    [5]
    5.  Method according to claim 1 wherein step d) is executed in real time searching for a game event selected from a first group of game events and wherein the detection of a game event from said first group of game events triggers
    as triggering an additional execution of stage d) in a time frame related to said game event of the first group detected in search of a game event of a second group of game events being all detected game events used in the stage and).
    [6]
    6.  Method according to any one of the preceding claims, wherein step d) further includes the detection of interference between data groups (31) of a game element (40) and limits (2) of the game area (1) pre-stored, also detecting game events (50) that are incorporated in the detection of game milestones of stage e).
    [7]
    7.  Method according to any one of the preceding claims, wherein the notification signal is transmitted by wireless means to a mobile receiver (22).
    [8]
    8.  Method according to any one of the preceding claims, wherein said remote position sensors (12) are selected from:
     laser sensors;
    Radars;
     flight time video sensors;
     three-dimensional video sensors composed of several video cameras separated by a defined distance known as the position information automatically inferred by the discrepancies between the images captured by said various cameras;
    [9]
    9. Method according to any one of the preceding claims, wherein said sensor network (10) further includes individual sensors (11) selected from:
     video cameras, wherein during said stage b) an analysis of shape and / or color recognition is performed on the data (30) acquired by said video cameras;
     at least one microphone (13), wherein during said step b) an analysis of sound recognition is performed on the data acquired by said microphone
    (13) for the detection of relevant sounds, indicative of a game event (50);
     sensors integrated in the game elements (40).
    [10]
    10.  Method according to any one of the preceding claims, wherein the detection of game events (50) of step d) is performed on the time sequences of data groups (31) in search of patterns coinciding with a registration of patterns of possible game events pre-stored in memory.
    [11]
    eleven.  Method according to any one of the preceding claims, wherein for each game element (40) detected in the game area (1) statistical data related to said game element (40) obtained from the game events is generated
    (50) detected related to said game element (40).
    [12]
    12.  Method according to claim 11 wherein said statistical data is transmitted in real time to a remote storage device.
    [13]
    13.  Method according to any one of the preceding claims, wherein the game events (50) and / or the game milestones detected feed in real time an augmented reality system that superimposes visual information related to said game events (50) and / or said game milestones on real images of the game area.
    [14]
    14.  Method according to any one of the preceding claims, wherein:
     said analysis of stage b) is performed on the data in search of patterns matching a pattern register of possible pre-stored game elements in memory; or
     said analysis of stage b) is performed on the data in search of patterns coinciding with a register of patterns of possible pre-stored game elements in memory, which contains patterns of shape, color and / or position of possible game elements.
    [15]
    fifteen.  Method according to any one of the preceding claims wherein during the analysis of step b) a detection of groups of data (31) relative to a
    game element (40) in the data from a remote position sensor (12), and wherein the position information of said game element (40) obtained from said remote position sensor (12) is compared with the information of existing position in the data of the other remote position sensors (12) detecting a spatio-temporal coincidence between said compared data, assigning said detection of data groups (31) relative to a game element (40) to all groups of data (31) of all remote position sensors (12) with space-time matching.
    [16]
    16.  Method according to any one of the preceding claims, wherein said analysis of step b) is performed on data obtained at different times, and wherein the detection of a game element (40) at a time is used to perform the detection of said game element (40) at different times, by monitoring the position of said game element (40).
    [17]
    17.  Method according to any one of the preceding claims, wherein said step a) further includes acquiring data (30) relative to several game elements (40) simultaneously, said data including information indicative of the three-dimensional shape of the game elements (40) .
    [18]
    18.  Computer program that includes code instructions that when executed in a computer system, provided with at least one control device (20) with a memory and with computing capacity, implement the method of any of claims 1 to 17.
    [19]
    19.  Computer program according to claim 18 wherein said computer program includes algorithms for automatic analysis of the data captured by the sensor network resulting from learning algorithms.
    DRAWINGS
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    同族专利:
    公开号 | 公开日
    US20200054930A1|2020-02-20|
    WO2018154162A1|2018-08-30|
    ES2680393B1|2019-09-09|
    EP3588377A1|2020-01-01|
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    ES201730234A|ES2680393B1|2017-02-23|2017-02-23|METHOD AND PROGRAM OF AUTOMATIC ARBITRATION COMPUTER|ES201730234A| ES2680393B1|2017-02-23|2017-02-23|METHOD AND PROGRAM OF AUTOMATIC ARBITRATION COMPUTER|
    US16/487,532| US20200054930A1|2017-02-23|2018-02-21|Method, system and computer program for automatic refereeing|
    PCT/ES2018/070124| WO2018154162A1|2017-02-23|2018-02-21|Method, system and computer program for automatic refereeing|
    EP18721426.7A| EP3588377A1|2017-02-23|2018-02-21|Method, system and computer program for automatic refereeing|
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