Fighting simulation system and operation method thereof

Abstract

Provided, according to one embodiment of the present application, are a fighting simulation system and an operation method thereof. The system may comprise: at least one lidar sensor unit which is installed in a play space of a fighting game and generates point cloud data; a motion tracking unit which generates tracking data for at least a portion of body parts of a first opponent and a second opponent on the basis of first point cloud data corresponding to the first opponent and second point cloud data corresponding to the second opponent, the opponents being positioned in the play space, and the point cloud data being generated through the lidar sensor unit; a strike determination unit which determines the delivery or not of a strike between the first opponent and the second opponent and the strength of the strike on the basis of the tracking data of the motion tracking unit; and a visualization unit which visualizes the delivery or not of the strike and the strength of the strike determined by the strike determination unit as a predetermined image, and superimposes and displays same on a real-time play image of the fighting game of the first opponent and the second opponent.

Description

Fighting battle simulation system and method of operation thereof

[0001] The present application relates to a fighting battle simulation system and a method of operating the same.

[0002] Combat matches consist of two or more athletes participating in a form of combat with specific rules, and attempt to quantitatively determine the winner of the match by applying positive or negative scores to events determined in the match (for example, in boxing, points are awarded to the athlete who loses points, or in Taekwondo, to the athlete who delivers a successful kick to the opponent). While the details of all scoring systems vary, they generally follow the premise that the participant, combatant, or athlete with the higher score at the end of the allotted time is the winner, unless the match is decided by other immediate victory criteria such as a knockout, disqualification, or an "Ippon" in Judo.

[0003] Meanwhile, many combat sports have specific criteria regarding not only what is allowed or disallowed as a scoring move, but also what constitutes an opponent's scoring area. In combat sports that use protective gear (e.g., body guards, chest guards, and trunk guards) (e.g., Taekwondo), colored areas of the protective gear, which often indicate a player's designation by color, can frequently be defined as valid scoring areas.

[0004] Recently, to more accurately measure scores for determining victory or defeat in combat sports, technology has been introduced in which sensors are embedded in the valid scoring areas of protective gear. When an impact exceeding a certain threshold is applied, the sensor detects the impact to determine its validity. However, since the previous method was a simple one that merely verified the validity of a strike via sensor detection to add or subtract points, it had limitations in that it lacked elements to generate audience interest.

[0005] In this regard, a new type of fighting simulation technology is required that can increase audience immersion and interest by applying elements of online games to actual fighting matches.

[0006] The present application aims to provide a fighting battle simulation system and a method of operating the same.

[0007] According to an embodiment of the present application, a fighting battle simulation system is provided. The system may include: at least one LiDAR sensor unit installed in a play space of a fighting battle game and generating point cloud data; a motion tracking unit that generates tracking data for at least a part of the body of a first opponent and a second opponent based on first point cloud data corresponding to a first opponent located in the play space and second point cloud data corresponding to a second opponent generated through the LiDAR sensor unit; a strike determination unit that determines whether there is a strike and the strike intensity between the first opponent and the second opponent based on the tracking data of the motion tracking unit; and a visualization unit that visualizes the whether there is a strike and the strike intensity determined by the strike determination unit as a predetermined image and displays it superimposed on a real-time play video of the fighting battle game between the first opponent and the second opponent.

[0008] Additionally, the tracking data includes data regarding the position, direction of movement, and speed of movement of a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second distalizers, and data regarding the position, direction of movement, and speed of movement of an effective striking part set for each of the first and second distalizers, and the striking determination unit may determine that a strike has occurred on the effective striking part if the striking means part collides with the effective striking part and the collision intensity is greater than or equal to a predetermined threshold.

[0009] In addition, the impact determination unit may determine the impact intensity differently based on the position, direction of movement, and speed of movement of the impact means part, and the position, direction of movement, and speed of movement of the effective impact part.

[0010] In addition, the size of the time window may be 120 seconds, and the overlap ratio of the time window may be 50%.

[0011] In addition, the effective striking area is set to be multiple, and the striking judgment unit applies different weights to the striking intensity according to whether or not a strike occurs for each of the multiple effective striking areas, and the visualization unit can perform the visualization based on the striking intensity to which the weights are applied.

[0012] Additionally, the tracking data includes information regarding the density of the point clouds of the first point cloud data and the second point cloud data for at least some of the body parts, and the hit determination unit can determine, based on the tracking data, that a hit has occurred to the body parts of the first and second electronic devices where the density of the point clouds is greater than or equal to the reference value.

[0013] In addition, the impact judgment unit may determine the impact intensity differently depending on the level of density for the body parts of the first and second electric motors where the density is greater than or equal to the reference value.

[0014] Additionally, the body part includes a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second opponents, and an effective striking part set for each of the first and second opponents, and the striking determination unit can determine that a strike has occurred if the density of the point cloud between the striking means part of one of the first and second opponents and the effective striking part of the opponent opponent is greater than or equal to the reference value.

[0015] In addition, the effective impact area is set to a plurality of places, and the impact judgment unit applies different weights to the impact intensity according to whether or not there is an impact on each of the plurality of effective impact areas, and the visualization unit can perform the visualization based on the impact intensity to which the weights are applied.

[0016] In addition, if the impact judgment unit determines that an impact has occurred, the visualization unit can visualize the image so that a gauge corresponding to the impact intensity decreases in real time from the power gauge of the impacted unit among the first and second units.

[0017] According to an embodiment of the present application, a method of operation of a fighting battle simulation system is provided. The method may include: acquiring first point cloud data corresponding to a first opponent located in the play space and second point cloud data corresponding to a second opponent, generated by at least one LiDAR sensor unit installed in the play space of a fighting battle game; generating tracking data for at least a part of the body parts of the first opponent and the second opponent based on the first point cloud data and the second point cloud data; determining whether there is a hit and the intensity of the hit between the first opponent and the second opponent based on the tracking data; and, if it is determined that a hit has occurred, visualizing the hit status and the intensity of the hit as a predetermined image and displaying it superimposed on a real-time play video of the fighting battle game between the first opponent and the second opponent.

[0018] A computer program is provided according to an embodiment of the present application. The program may be stored on a recording medium to execute a method according to an embodiment of the present application.

[0019] According to the embodiments of the present application, by using a LiDAR sensor to determine whether a hit has occurred and the intensity of the hit, and by visualizing this in real-time in the form of a gauge on the gameplay video of a fighting game, online game elements can be added to the fighting match to increase immersion and interest.

[0020] The effects obtainable from the embodiments of the present application are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present application pertains from the description below.

[0021] A brief description of each drawing is provided to help to better understand the drawings cited in this application.

[0022] FIG. 1 is a block diagram of a fighting battle simulation system according to an embodiment of the present application.

[0023] FIG. 2 is a functional block diagram for explaining the operation of a processor of a computer device that performs a fighting battle simulation according to an embodiment of the present application.

[0024] FIG. 3 is a drawing for explaining a play space for simulating a fighting battle according to an embodiment of the present application.

[0025] FIG. 4 is a diagram illustrating point cloud data generated by detecting a fighting opponent with a LiDAR sensor according to an embodiment of the present application.

[0026] FIG. 5 is a diagram illustrating a screen in which the presence or absence of a hit and the hit intensity are visualized in a fighting battle simulation according to an embodiment of the present application.

[0027] FIG. 6 is a flowchart illustrating the operation method of a fighting battle simulation system according to an embodiment of the present application.

[0028] The technical concept of the present application is subject to various modifications and may have various embodiments, and specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the technical concept of the present application to specific embodiments, and it should be understood that it includes all modifications, equivalents, and substitutions that fall within the scope of the technical concept of the present application.

[0029] In explaining the technical concept of the present application, detailed descriptions of related prior art are omitted if it is determined that such descriptions may unnecessarily obscure the essence of the present application.

[0030] The terms used herein are for describing embodiments and are not intended to limit or / or restrict the present application. Singular expressions include plural expressions unless the context clearly indicates otherwise. Additionally, numbers used herein (e.g., First, Second, etc.) are merely identifiers to distinguish one component from another.

[0031] In this specification, when it is stated that a part is connected to another part, this includes not only cases where they are directly connected, but also cases where they are indirectly connected with other components in between. Furthermore, when it is stated that a part includes a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0032] Furthermore, in this application, the term "or" is intended to mean an implicit "or" rather than an exclusive "or." That is, unless otherwise specified or evident from the context, "X uses A or B" is intended to mean one of the natural implicit substitutions. In other words, if X uses A; if X uses B; or if X uses both A and B, "X uses A or B" may apply to any of these cases. Additionally, the term "and / or" as used herein should be understood to refer to and include all possible combinations of one or more of the enumerated related configurations.

[0033] In addition, terms such as “~part,” “~device,” “~device,” and “~module” described in this application refer to a unit that processes at least one function or operation, and this can be implemented as hardware or software or a combination of hardware and software, such as a processor, microprocessor, microcontroller, CPU (Central Processing Unit), GPU (Graphics Processing Unit), APU (Accelerate Processor Unit), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), etc.

[0034] Furthermore, it is intended to clarify that the classification of the components in this application is merely based on the primary function each component is responsible for. That is, two or more components described below may be combined into a single component, or a single component may be divided into two or more components based on more subdivided functions. Additionally, each component described below may additionally perform some or all of the functions performed by other components in addition to its own primary function, and it is obvious that some of the primary functions performed by each component may be exclusively performed by other components.

[0035]

[0036] The method according to the embodiment of the present application may be performed on a personal computer, workstation, server computer device, etc., equipped with computing power, or on a separate device for this purpose.

[0037] Additionally, the method may be performed on one or more computing devices. For example, at least one step of the method according to an embodiment of the present application may be performed on a client device, and other steps may be performed on a server device. In this case, the client device and the server device may be connected via a network to transmit and receive computation results. Alternatively, the method may be performed by distributed computing technology.

[0038]

[0039] In this specification, the term "artificial intelligence learning model" may be used interchangeably with "artificial intelligence model," "computational model," "machine learning model," etc. An artificial intelligence learning model may be trained by various algorithms, such as, for example, decision tree, random forest, Gaussian naive bayes, k-nearest neighbor, Ada Boost, support vector machine, voting, bagging, neural network, and deep learning. However, it is not limited thereto.

[0040] An artificial intelligence learning model can be trained using at least one of supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning. The training of an artificial intelligence learning model may be a process of applying knowledge to the model to perform a specific action.

[0041] When algorithms such as neural networks or deep learning are applied to an artificial intelligence learning model, the AI ​​learning model may be referred to as a network function. The term "network function" can be used interchangeably with "neural network." A neural network can generally be composed of a set of interconnected computational units referred to as nodes. These nodes may also be referred to as neurons. A neural network is composed of at least one node, and the nodes may be interconnected by one or more links.

[0042] Neural networks may include deep neural networks (DNNs). Deep neural networks may include convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, restricted Boltzmann machines (RBMs), deep belief networks (DBNs), Q networks, U networks, Siamese networks, and Generative Adversarial Networks (GANs), but are not limited to these.

[0043]

[0044] Hereinafter, embodiments of the present application will be described in detail in turn.

[0045]

[0046] FIG. 1 is a block diagram of a fighting battle simulation system according to an embodiment of the present application, and FIG. 2 is a functional block diagram for explaining the operation of a processor of a computer device that performs a fighting battle simulation according to an embodiment of the present application.

[0047] Referring to FIG. 1, the fighting battle simulation system may include at least one LiDAR sensor unit (110, 120) and a computer device (200).

[0048] The LiDAR sensor unit (110, 120) is installed in the play space of a fighting game and can generate point cloud data. A point cloud refers to a set of multiple data points placed in a three-dimensional space, and these points can be combined to represent a three-dimensional shape or object. Specifically, the LiDAR sensor unit (110, 120) generates the coordinates of a three-dimensional point through the direction of light that hits an object and reflects back, and the time it takes for the light to return, and collects these to form point cloud data.

[0049] In an embodiment, the LiDAR sensor unit (110, 120) may generate first point cloud data and second point cloud data, respectively, to detect a first opponent and a second target participating in a fighting battle, and transmit them to a computer device (200). However, this is exemplary, and according to an embodiment, one point cloud data may be generated and transmitted to the computer device (200), and the computer device (200) may be implemented to separate and extract the first point cloud data corresponding to the first opponent and the second point cloud data corresponding to the second opponent.

[0050] The computer device (200) receives point cloud data generated by the lidar sensor unit (110, 120), and based on this, determines whether a strike occurs between the first and second opponents and the intensity thereof, and can visualize it.

[0051] In an embodiment, the computer device (200) may include a communication unit (210), an input unit (220), a memory (230), and a processor (240).

[0052] The communication unit (210) can receive or transmit data from inside or outside. The communication unit (210) may include a wired or wireless communication unit. If the communication unit (210) includes a wired communication unit, the communication unit (210) may include one or more components that enable communication through a Local Area Network (LAN), a Wide Area Network (WAN), a Value Added Network (VAN), a mobile radio communication network, a satellite communication network, and a combination thereof. Additionally, if the communication unit (210) includes a wireless communication unit, the communication unit (210) may transmit or receive data or signals wirelessly using cellular communication, a wireless LAN (e.g., Wi-Fi), etc. In an embodiment, the communication unit (210) may transmit or receive data or signals to and from an external device (particularly, a LiDAR sensor unit (110, 120)) or an external server under the control of a processor (240).

[0053] The input unit (220) can receive various user commands through external operation. To this end, the input unit (220) may include or be connected to one or more input devices. For example, the input unit (220) may receive user commands by being connected to an interface for various inputs, such as a keypad or a mouse. To this end, the input unit (220) may include an interface such as a USB port as well as a Thunderbolt. Additionally, the input unit (220) may receive external user commands by including or being combined with various input devices such as a touchscreen or a button.

[0054] The memory (230) can store programs and / or program instructions for the operation of the processor (240) and can temporarily or permanently store input / output data. The memory (230) may include at least one type of storage medium among flash memory type, hard disk type, multimedia card micro type, card type memory (e.g., SD or XD memory, etc.), RAM, SRAM, ROM, EEPROM, PROM, magnetic memory, magnetic disk, and optical disk.

[0055] Additionally, the memory (230) can store various artificial intelligence learning models, network functions and algorithms, and can store various data, programs (one or more of which are instructions), applications, software, commands, code, etc. for driving and controlling the device (200).

[0056] The processor (240) can control the overall operation of the device (200). The processor (240) can execute one or more programs or software stored in memory (230). The processor (240) may mean a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or a dedicated processor (240) on which the methods according to embodiments of the present application are performed.

[0057] In an embodiment, the processor (240) can perform the functions of a motion tracking unit (241), a hit determination unit (242), and a visualization unit (243) as shown in FIG. 2 by executing at least one program stored in memory (230).

[0058] The motion tracking unit (241) can generate tracking data for the first and second opponents based on point cloud data continuously received over time from the LiDAR sensor unit (110, 120). Specifically, the motion tracking unit (241) can generate tracking data for at least some of the body parts of the first and second opponents based on the first point cloud data corresponding to the first opponent and the second point cloud data corresponding to the second opponent.

[0059] In an embodiment, the tracking data may include data regarding the position, direction of movement, and speed of movement of a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second distal arms, and data regarding the position, direction of movement, and speed of movement of an effective striking part set for each of the first and second distal arms.

[0060] Meanwhile, the striking means part referred to here can be defined as a concept that includes not only the hands, feet, elbows, and knees themselves, but also all equipment worn on those body parts, such as gloves and protective gear. Additionally, the valid striking part refers to a body part where striking is recognized according to the rules of a fighting game, and can be defined as a concept that includes not only the body part itself but also at least a portion of the protective gear worn thereon.

[0061] In an embodiment, the tracking data may include information regarding the density of the point clouds of the first point cloud data and the second point cloud data for at least some parts of the body. Here, density may be a numerical value indicating how much the first point cloud and the second point cloud are distributed within a predetermined unit space.

[0062] In an embodiment, the processor (240) may preprocess point cloud data received from the LiDAR sensor unit (110, 120) before generating tracking data. This preprocessing may include, for example, a process of sampling at least some of the plurality of data points included in the point cloud data.

[0063] In an embodiment, tracking data can be performed through at least one artificial intelligence learning model. The artificial intelligence learning model can be pre-trained based on training data to extract the position, direction of movement, and speed of movement of at least one body part of the first and second antagonists from point cloud data.

[0064] The impact determination unit (242) can determine whether there is an impact and the impact strength between the first and second opponents based on tracking data.

[0065] In the embodiment, the impact determination unit (242) determines that the two have collided (or come into contact) based on the location and direction of movement of the impact means part and the effective impact part, and if the impact intensity calculated based on the direction of movement and the speed of movement is greater than or equal to a predetermined threshold, it can determine that an impact has occurred on the effective impact part.

[0066] Additionally, in the embodiment, the impact determination unit (242) may determine the impact strength differently based on the position, direction of movement, and speed of movement of the impact means part, and the position, direction of movement, and speed of movement of the effective impact part. For example, the impact determination unit (242) may be implemented to assign different impact strengths according to the angle at which the impact means part approaches the effective impact part calculated from information regarding the position and direction of movement, and the approach speed between the impact means part and the effective impact part calculated from information regarding the speed of movement.

[0067] In an embodiment, the impact determination unit (242) can determine whether there is a hit between the first and second opponents based on information regarding the density of the point cloud included in the tracking data. For example, the impact determination unit (242) can determine that a hit has occurred between the body parts of the first and second opponents (i.e., the impact means part and the effective impact part) when the density of the point cloud corresponding to each of the first and second opponents is greater than or equal to a predetermined threshold.

[0068] Additionally, in the embodiment, the body part includes a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second opponents, and an effective striking part set for each of the first and second opponents, and the striking judgment part (242) can determine that a strike has occurred if the density of the point cloud between the striking means part of one of the first and second opponents and the effective striking part of the opponent opponent is greater than or equal to the reference value.

[0069] Additionally, in the embodiment, when the impact judgment unit (242) determines that an impact has occurred, it can determine the impact intensity differently depending on the density of the body part.

[0070] In the embodiment, the effective striking area may be set to multiple. At this time, the striking judgment unit (242) may apply different weights to the striking intensity depending on whether a strike occurs for each of the multiple effective striking areas. For example, when the head area and the chest area are set as effective striking areas, the case where the head area is struck may be configured to have a higher weight assigned to the striking intensity than when the chest area is struck.

[0071] The visualization unit (243) can visualize the presence or absence of a hit and the intensity of the hit determined by the hit judgment unit (242) as a predetermined image and display it superimposed on the real-time gameplay video of the fighting game between the first opponent and the second opponent.

[0072] In an embodiment, when the impact judgment unit (242) determines that an impact has occurred, the visualization unit (243) can visualize an image so that a gauge corresponding to the impact intensity decreases in real time from the power gauge of the first and second opponents that received the impact.

[0073] In addition, in the embodiment, when different weights are applied depending on whether there is a hit in each effective hit area, the visualization unit (243) can perform visualization by applying the corresponding weight to the hit intensity. That is, for example, if the head area is hit, and a weight twice that of the chest area is applied, the gauge can also be visualized to decrease further by the amount of the weight reflected.

[0074] The configuration of the system and device (200) shown in FIGS. 1 and 2 is exemplary, and various configurations may be applied according to the embodiments of the present application.

[0075]

[0076] FIG. 3 is a drawing for explaining a play space for simulating a fighting battle according to an embodiment of the present application, and FIG. 4 is a drawing for explaining point cloud data generated by detecting a fighting opponent with a LiDAR sensor according to an embodiment of the present application.

[0077] Referring to FIG. 3, a first opponent (10) and a second opponent (20), who are participants in a battle, are positioned in a play space where a fighting battle game is performed, and a plurality of LiDAR sensor units (110, 120) may be installed to detect the position, movement, etc. of the first opponent (10) and the second opponent (20) within the play space.

[0078] Point cloud data generated by the LiDAR sensor unit (110, 120) can be illustrated as in FIG. 4, and the data may include first point cloud data for a first counter-electron (10) located in a three-dimensional space (i.e., play space) and second point cloud data for a second counter-electron (20).

[0079]

[0080] FIG. 5 is a diagram illustrating a screen in which the presence or absence of a hit and the hit intensity are visualized in a fighting battle simulation according to an embodiment of the present application.

[0081] As described above, the computer device (200) generates tracking data by tracking the location, movement, etc. of at least some of the body parts of the first counter-electronic device (10) and the second counter-electronic device (20) based on point cloud data, and determines whether there is an impact and the intensity of the impact between the first counter-electronic device (10) and the second counter-electronic device (20) based on this.

[0082] The occurrence of such a hit and the intensity of the hit can be visualized through the health gauge images (510, 520) corresponding to the first anti-tank (10) and the second anti-tank (20), as illustrated in FIG. 5. For example, if it is determined that the first anti-tank (10) has hit the effective hit area of ​​the second anti-tank (20), the health gauge (520) of the second anti-tank (20) can be implemented to decrease by an amount corresponding to the intensity of the hit. Meanwhile, different weights may be applied to each effective hit area, and these weights may be reflected in the gauge that decreases upon hitting.

[0083] The computer device (200) can display changes in the health gauge images (510, 520) resulting from the hit by overlapping them with the real-time gameplay video of the fighting game.

[0084]

[0085] FIG. 6 is a flowchart illustrating the operation method of a fighting battle simulation system according to an embodiment of the present application.

[0086] In step S610, the computer device (200) can obtain first point cloud data corresponding to a first opponent located in the play space generated by the lidar sensor unit and second point cloud data corresponding to a second opponent.

[0087] Subsequently, in step S620, the computer device (200) may generate tracking data for at least some of the body parts of the first and second opponents based on the first point cloud data and the second point cloud data. Here, the body parts may include a striking means part and an effective striking part.

[0088] In an embodiment, the tracking data may include data regarding the position, direction of movement, and speed of movement of a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second distal arms, and data regarding the position, direction of movement, and speed of movement of an effective striking part set for each of the first and second distal arms.

[0089] Additionally, in the embodiments, the tracking data may include information regarding the density of the point clouds of the first point cloud data and the second point cloud data for at least some of the body parts.

[0090] Subsequently, in step S630, the computer device (200) can determine whether there is a hit and the strength of the hit between the first and second opponents based on tracking data.

[0091] For example, the computer device (200) may determine whether there is a hit and the impact strength based on the location, direction of movement, and speed of movement of the impact means part and the effective impact part of each of the first and second counter-electronics, or determine whether there is a hit and the impact strength based on the density of the point clouds of the first and second counter-electronics.

[0092] In step S640, when a hit occurs, the computer device (200) can visualize whether a hit occurred and the intensity of the hit as a predetermined image and display it superimposed on the real-time gameplay video of the fighting game between the first opponent and the second opponent.

[0093] In an embodiment, when it is determined that a strike has occurred, the computer device (200) can visualize an image so that a gauge corresponding to the strike intensity decreases in real time from the power gauge of the first and second opponents that received the strike.

[0094] The method (600) illustrated in FIG. 6 is exemplary, and various configurations may be applied according to embodiments of the present application.

[0095]

[0096] The method according to an embodiment of the present application may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the present application or may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0097] Additionally, the method according to the disclosed embodiments may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product.

[0098] A computer program product may include a software program and a computer-readable storage medium on which the software program is stored. For example, a computer program product may include a product in the form of a software program (e.g., a downloadable app) that is electronically distributed through a manufacturer of an electronic device or an electronic market (e.g., Google Play Store, App Store). For electronic distribution, at least a portion of the software program may be stored on a storage medium or temporarily created. In this case, the storage medium may be a server of the manufacturer, a server of the electronic market, or a storage medium of a relay server that temporarily stores the software program.

[0099] A computer program product may include a storage medium of a server or a storage medium of a client device in a system composed of a server and a client device. Alternatively, if there is a third device (e.g., a smartphone) that communicates with the server or the client device, the computer program product may include a storage medium of the third device. Alternatively, the computer program product may include the S / W program itself that is transmitted from the server to the client device or the third device, or transmitted from the third device to the client device.

[0100] In this case, one of the server, the client device, and the third device may execute the computer program product to perform the method according to the disclosed embodiments. Alternatively, two or more of the server, the client device, and the third device may execute the computer program product to perform the method according to the disclosed embodiments in a distributed manner.

[0101] For example, a server (e.g., a cloud server or an artificial intelligence server, etc.) can execute a computer program product stored on the server to control a client device connected to the server in communication to perform a method according to the disclosed embodiments.

[0102]

[0103] Although the embodiments have been described in detail above, the scope of the present application is not limited thereto, and various modifications and improvements by those skilled in the art using the basic concept of the present application as defined in the following claims also fall within the scope of the present application.

Claims

1. As a fighting simulation system, At least one LiDAR sensor unit installed in the play space of a fighting game and generating point cloud data; A motion tracking unit that generates tracking data for at least a portion of the body parts of the first opponent and the second opponent based on first point cloud data corresponding to the first opponent located in the play space generated through the lidar sensor unit and second point cloud data corresponding to the second opponent; A strike determination unit that determines whether there is a strike and the strike intensity between the first and second electrodes based on the tracking data of the motion tracking unit; and A system comprising a visualization unit that visualizes the presence or absence of a hit and the intensity of the hit determined by the hit determination unit as a predetermined image and displays it superimposed on a real-time gameplay video of the fighting game between the first opponent and the second opponent.

2. In Paragraph 1, The tracking data includes data regarding the position, direction of movement, and speed of movement of a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second distal arms, and data regarding the position, direction of movement, and speed of movement of an effective striking part set for each of the first and second distal arms. The above-described impact determination unit determines that an impact has occurred on the effective impact area when the impact means part collides with the effective impact area and the collision intensity is greater than or equal to a predetermined threshold.

3. In Paragraph 2, The above-mentioned impact determination unit is a system that determines the impact intensity differently based on the position, direction of movement, and speed of movement of the impact means part, and the position, direction of movement, and speed of movement of the effective impact part.

4. In Paragraph 3, The above effective striking areas are set in multiple places, and The above-mentioned impact determination unit applies different weights to the impact intensity according to whether or not there is an impact on each of the plurality of effective impact areas, and A system in which the visualization unit performs the visualization based on the impact intensity to which the weight is applied.

5. In Paragraph 1, The above tracking data is, It includes information on the density of the point clouds of the first point cloud data and the second point cloud data for at least some of the above body parts, The above-described impact determination unit determines, based on the above-described tracking data, that an impact has occurred on the body parts of the first and second opponents where the density of the point cloud is greater than or equal to the above-described threshold.

6. In Paragraph 5, The above-mentioned impact judgment unit is a system that determines the impact intensity differently according to the level of density for the body parts of the first and second transducers in which the density is greater than or equal to the above-mentioned standard value.

7. In Paragraph 6, The above body part includes a striking means part comprising at least one of the hand, foot, elbow, and knee of each of the first and second greater trouser and the second greater trouser, and an effective striking part set for each of the first and second greater trouser, and The above-described strike determination unit determines that a strike has occurred if the density of the point cloud between the striking means portion of one of the first and second counter-counters and the effective striking portion of the opponent counter-counter is greater than or equal to the above reference value.

8. In Paragraph 7, The above effective striking areas are set in multiple places, and The above-mentioned impact determination unit applies different weights to the impact intensity according to whether or not there is an impact on each of the plurality of effective impact areas, and A system in which the visualization unit performs the visualization based on the impact intensity to which the weight is applied.

9. In Paragraph 1, If the above-mentioned impact judgment unit determines that an impact has occurred, The above visualization unit is, A system for visualizing the image such that a gauge corresponding to the impact intensity decreases in real time from the power gauge of the first and second counterweights that received the impact.

10. As a method of operation of a fighting battle simulation system, A step of acquiring first point cloud data corresponding to a first opponent located in the play space and second point cloud data corresponding to a second opponent, generated by at least one LiDAR sensor unit installed in the play space of a fighting game; A step of generating tracking data for at least some of the body parts of the first and second anteromates based on the first point cloud data and the second point cloud data; A step of determining the presence or absence of impact and the impact intensity between the first and second transducers based on the tracking data above; and A method comprising the step of, when it is determined that a hit has occurred, visualizing the hit status and the hit intensity as a predetermined image and displaying it superimposed on the real-time gameplay video of the fighting game between the first opponent and the second opponent.

11. A computer program stored on a recording medium to execute the method according to paragraph 10.

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