CN116650953A - Somatosensory tennis game method based on units engine - Google Patents

Somatosensory tennis game method based on units engine Download PDF

Info

Publication number
CN116650953A
CN116650953A CN202310661671.1A CN202310661671A CN116650953A CN 116650953 A CN116650953 A CN 116650953A CN 202310661671 A CN202310661671 A CN 202310661671A CN 116650953 A CN116650953 A CN 116650953A
Authority
CN
China
Prior art keywords
similarity
somatosensory
curve
game
current curve
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310661671.1A
Other languages
Chinese (zh)
Inventor
张帅豪
李俊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Shimi Network Technology Co ltd
Original Assignee
Shenzhen Shimi Network Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Shimi Network Technology Co ltd filed Critical Shenzhen Shimi Network Technology Co ltd
Priority to CN202310661671.1A priority Critical patent/CN116650953A/en
Publication of CN116650953A publication Critical patent/CN116650953A/en
Pending legal-status Critical Current

Links

Classifications

    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/40—Processing input control signals of video game devices, e.g. signals generated by the player or derived from the environment
    • A63F13/42—Processing input control signals of video game devices, e.g. signals generated by the player or derived from the environment by mapping the input signals into game commands, e.g. mapping the displacement of a stylus on a touch screen to the steering angle of a virtual vehicle
    • A63F13/428—Processing input control signals of video game devices, e.g. signals generated by the player or derived from the environment by mapping the input signals into game commands, e.g. mapping the displacement of a stylus on a touch screen to the steering angle of a virtual vehicle involving motion or position input signals, e.g. signals representing the rotation of an input controller or a player's arm motions sensed by accelerometers or gyroscopes
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/20—Input arrangements for video game devices
    • A63F13/21—Input arrangements for video game devices characterised by their sensors, purposes or types
    • A63F13/211—Input arrangements for video game devices characterised by their sensors, purposes or types using inertial sensors, e.g. accelerometers or gyroscopes
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/20—Input arrangements for video game devices
    • A63F13/21—Input arrangements for video game devices characterised by their sensors, purposes or types
    • A63F13/212—Input arrangements for video game devices characterised by their sensors, purposes or types using sensors worn by the player, e.g. for measuring heart beat or leg activity
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/55—Controlling game characters or game objects based on the game progress
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/60—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor
    • A63F13/67—Generating or modifying game content before or while executing the game program, e.g. authoring tools specially adapted for game development or game-integrated level editor adaptively or by learning from player actions, e.g. skill level adjustment or by storing successful combat sequences for re-use
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
    • A63F13/80—Special adaptations for executing a specific game genre or game mode
    • A63F13/812—Ball games, e.g. soccer or baseball
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/10—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by input arrangements for converting player-generated signals into game device control signals
    • A63F2300/1012—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by input arrangements for converting player-generated signals into game device control signals involving biosensors worn by the player, e.g. for measuring heart beat, limb activity
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/10—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by input arrangements for converting player-generated signals into game device control signals
    • A63F2300/105—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by input arrangements for converting player-generated signals into game device control signals using inertial sensors, e.g. accelerometers, gyroscopes
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/60—Methods for processing data by generating or executing the game program
    • A63F2300/6027—Methods for processing data by generating or executing the game program using adaptive systems learning from user actions, e.g. for skill level adjustment
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/60—Methods for processing data by generating or executing the game program
    • A63F2300/6045—Methods for processing data by generating or executing the game program for mapping control signals received from the input arrangement into game commands
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
    • A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
    • A63F2300/80—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game specially adapted for executing a specific type of game
    • A63F2300/8011—Ball

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • Cardiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The invention discloses a body feeling tennis game method, a device, equipment and a computer readable storage medium based on a unit engine, wherein the method comprises the following steps: after the somatosensory game is started, acquiring gyroscope data from the bound somatosensory equipment; generating a current curve of the angle of the somatosensory equipment according to the gyroscope data; calculating the similarity between the current curve and a preset sample curve; judging whether the player finishes the standard batting action according to the similarity; if yes, the game role is controlled to execute batting operation. The body feeling tennis game method based on the units engine has the advantages of high motion recognition precision, strong generalization and the like.

Description

Somatosensory tennis game method based on units engine
Technical Field
The present invention relates to the field of motion sensing game technologies, and in particular, to a motion sensing tennis game method, device, apparatus and computer readable storage medium based on a unit engine.
Background
Somatosensory games are a way of playing a game by capturing physical actions of a user to control the behavior of a character and progress of the game.
There are two main fluid sensation schemes on the market:
1. based on a Kinetic architecture, the amplitude and the direction of motion are judged by using a time slot depth image and a human skeleton through a curve point model. 2. Based on the machine learning model, a model such as a support vector machine is trained by using gyroscope data, and actions of a user are recognized through the action recognition model.
Both of these schemes have drawbacks:
1. based on the scheme of the Kinetic architecture, generalization performance is limited because different human body structures are greatly different. 2. Based on the scheme of the machine learning model, the recognition accuracy is not high, because gyroscopes have the problem of linear drift, and different gyroscopes have different drift degrees.
Disclosure of Invention
The embodiment of the application provides a body feeling tennis game method based on a unit engine, aiming at improving the accuracy and generalization of batting action identification in the body feeling tennis game.
In order to achieve the above object, an embodiment of the present application provides a somatosensory tennis game method based on a unit engine, including:
after the somatosensory game is started, acquiring gyroscope data from the bound somatosensory equipment;
generating a current curve of the angle of the somatosensory equipment according to the gyroscope data;
calculating the similarity between the current curve and a preset sample curve;
judging whether the player finishes the standard batting action according to the similarity;
if yes, the game role is controlled to execute batting operation.
In an embodiment, generating a current curve of the angle of the somatosensory device over time from the gyroscope data comprises:
Generating a grid coordinate system formed by a plurality of grid units and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
calculating an angle value of the virtual rigid body in each time step according to the gyroscope data;
updating the position of the virtual rigid body on the grid coordinate system according to the angle value, and recording the coordinate value of a grid unit through which the virtual rigid body passes;
and generating a current curve of the somatosensory equipment according to the recorded coordinate values.
In one embodiment, generating a current curve of the somatosensory device from the recorded coordinate values comprises:
taking the current moment as the end point of the batting action interval;
taking the historical moment which is set with the time interval from the current moment as the starting point of the batting action interval;
and generating the current curve according to the coordinate data from the starting point to the ending point.
In one embodiment, the similarity between the current curve and a preset sample curve is calculated according to the friendship distance.
In an embodiment, before calculating the similarity between the current curve and the preset sample curve, the method further comprises:
confirming the batting direction of the current batting action according to the gyroscope data;
And selecting a plurality of sample curves from a preset sample curve library according to the ball striking direction to serve as preset sample curves.
In one embodiment, determining whether the player has completed a standard batting action based on the similarity includes:
meanwhile, calculating the similarity between the current curve and a plurality of preset sample curves to obtain a plurality of similarities;
if any one of the plurality of similarities is greater than the preset threshold, determining that the user has completed a standard batting action.
In one embodiment, determining whether the player has completed a standard tennis action based on the similarity includes:
normalizing the similarity;
comparing the similarity after normalization treatment with a preset threshold value;
if the normalized similarity is greater than a preset threshold, judging that the user finishes the standard batting action.
In order to achieve the above object, an embodiment of the present application further provides a motion-sensing tennis game device based on a unit engine, including:
the acquisition module is used for acquiring gyroscope data from the bound somatosensory equipment after the somatosensory game is started;
the generation module is used for generating a current curve of the angle of the somatosensory equipment along with the time change according to the gyroscope data;
the calculation module is used for calculating the similarity between the current curve and a preset sample curve;
The judging module is used for judging whether the player finishes the standard batting action according to the similarity;
and the execution module is used for controlling the game character to execute the batting operation after judging that the player completes the standard batting action.
To achieve the above objective, an embodiment of the present application further provides a motion-sensing tennis game device based on a unit engine, which includes a memory, a processor, and a motion-sensing tennis game program based on the unit engine stored in the memory and executable on the processor, wherein the motion-sensing tennis game method based on the unit engine is implemented when the processor executes the motion-sensing tennis game program based on the unit engine.
To achieve the above object, an embodiment of the present application further provides a computer readable storage medium, where a unit engine-based somatosensory tennis game program is stored, where the unit engine-based somatosensory tennis game program, when executed by a processor, implements the unit engine-based somatosensory tennis game method according to any one of the above embodiments.
It can be understood that in the body feeling tennis game method based on the unit engine, the current curve of the angle of the body feeling device, which changes along with time, is generated through the gyroscope data, and then the similarity between the current curve and the sample curve is compared to judge whether the player completes the standard batting action, wherein the angle change curve of the body feeling device reflects the action characteristics of the body of the user to a certain extent, and whether the user completes the standard batting action can be judged more accurately through comparing the similarity between the current curve and the preset sample curve. Moreover, the method for identifying the angle change curve can be applied to various batting actions, and is not limited to specific hardware equipment. As long as proper gyroscope data is available, the method can be implemented in the Unity engine, so that the method has better generalization. Further, by adjusting the threshold value of the similarity, the sensitivity of the recognition can be controlled. According to actual demands, parameters can be adjusted to adapt to the batting action performances of different users. Compared with the traditional motion recognition mode of the motion sensing game, the motion sensing tennis game method based on the unit engine has the advantages of being high in motion recognition precision, high in generalization and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of one embodiment of a unit-based motion sensing tennis game apparatus of the present invention;
FIG. 2 is a flowchart of a method for playing a motion-induced tennis ball based on a unit engine according to an embodiment of the present invention;
FIG. 3 is a block diagram of a motion sensing tennis game device based on a unit engine according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In order that the above-described aspects may be better understood, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. And the use of "first," "second," and "third," etc. do not denote any order, and the terms may be construed as names.
As shown in fig. 1, fig. 1 is a schematic structural diagram of a server 1 (also called a body feeling tennis game device based on a unit engine) of a hardware running environment according to an embodiment of the present invention.
The server provided by the embodiment of the invention is equipment with display function, such as 'Internet of things equipment', intelligent air conditioner with networking function, intelligent electric lamp, intelligent power supply, AR/VR equipment with networking function, intelligent sound box, automatic driving automobile, PC, intelligent mobile phone, tablet personal computer, electronic book reader, portable computer and the like.
As shown in fig. 1, the server 1 includes: memory 11, processor 12 and network interface 13.
The memory 11 includes at least one type of readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the server 1, such as a hard disk of the server 1. The memory 11 may in other embodiments also be an external storage device of the server 1, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the server 1.
Further, the memory 11 may also include an internal storage unit of the server 1 as well as an external storage device. The memory 11 may be used not only for storing application software installed in the server 1 and various types of data, such as codes of the units engine-based motion sensing tennis game program 10, but also for temporarily storing data that has been output or is to be output.
The processor 12 may in some embodiments be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor or other data processing chip for running program code or processing data stored in the memory 11, for example executing a units engine based somatosensory tennis game program 10 or the like.
The network interface 13 may optionally comprise a standard wired interface, a wireless interface (e.g. WI-FI interface), typically used to establish a communication connection between the server 1 and other electronic devices.
The network may be the internet, a cloud network, a wireless fidelity (Wi-Fi) network, a Personal Area Network (PAN), a Local Area Network (LAN), and/or a Metropolitan Area Network (MAN). Various devices in a network environment may be configured to connect to a communication network according to various wired and wireless communication protocols. Examples of such wired and wireless communication protocols may include, but are not limited to, at least one of the following: transmission control protocol and internet protocol (TCP/IP), user Datagram Protocol (UDP), hypertext transfer protocol (HTTP), file Transfer Protocol (FTP), zigBee, EDGE, IEEE 802.11, light fidelity (Li-Fi), 802.16, IEEE 802.11s, IEEE 802.11g, multi-hop communications, wireless Access Points (APs), device-to-device communications, cellular communication protocol and/or bluetooth (bluetooth) communication protocol, or combinations thereof.
Optionally, the server may further comprise a user interface, which may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or a display unit, for displaying information processed in the server 1 and for displaying a visual user interface.
Fig. 1 shows only a server 1 having components 11-13 and a units engine based motion sensing tennis game program 10, it will be understood by those skilled in the art that the structure shown in fig. 1 is not limiting of the server 1 and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
In this embodiment, the processor 12 may be configured to call a unit engine-based somatosensory tennis game program stored in the memory 11, and perform the following operations:
after the somatosensory game is started, acquiring gyroscope data from the bound somatosensory equipment;
generating a current curve of the angle of the somatosensory equipment according to the gyroscope data;
calculating the similarity between the current curve and a preset sample curve;
judging whether the player finishes the standard batting action according to the similarity;
if yes, the game role is controlled to execute batting operation.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
generating a grid coordinate system formed by a plurality of grid units and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
Calculating an angle value of the virtual rigid body in each time step according to the gyroscope data;
updating the position of the virtual rigid body on the grid coordinate system according to the angle value, and recording the coordinate value of a grid unit through which the virtual rigid body passes;
and generating a current curve of the somatosensory equipment according to the recorded coordinate values.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
taking the current moment as the end point of the batting action interval;
taking the historical moment which is set with the time interval from the current moment as the starting point of the batting action interval;
and generating the current curve according to the coordinate data from the starting point to the ending point.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
and calculating the similarity between the current curve and a preset sample curve according to the Frechet distance.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
Confirming the batting direction of the current batting action according to the gyroscope data;
and selecting a plurality of sample curves from a preset sample curve library according to the ball striking direction to serve as preset sample curves.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
meanwhile, calculating the similarity between the current curve and a plurality of preset sample curves to obtain a plurality of similarities;
if any one of the plurality of similarities is greater than the preset threshold, determining that the user has completed a standard batting action.
In one embodiment, processor 12 may be configured to invoke a units engine based somatosensory tennis game program stored in memory 11 and perform the following operations:
normalizing the similarity;
comparing the similarity after normalization treatment with a preset threshold value;
if the normalized similarity is greater than a preset threshold, judging that the user finishes the standard batting action.
Based on the hardware architecture of the body feeling tennis game device based on the units engine, the embodiment of the body feeling tennis game method based on the units engine is provided. The invention discloses a body feeling tennis game method based on a unit engine, which aims to improve accuracy and generalization of batting action identification in body feeling tennis games.
Referring to fig. 2, fig. 2 is a diagram showing an embodiment of a unit-based motion sensing tennis game method according to the present application, wherein the unit-based motion sensing tennis game method comprises the following steps:
s10, after the somatosensory game is started, acquiring gyroscope data from the bound somatosensory equipment.
Wherein, the somatosensory game is a somatosensory tennis game. The somatosensory tennis game means that tennis actions can be performed
The somatosensory game can be a web-based web game, an html 5-based applet, or an independently running app.
Somatosensory devices are a class of devices used to capture, recognize and translate physical actions of players. They typically include sensors, controllers, and associated hardware components, intended for use in conjunction with interactive experience techniques such as electronic games, virtual reality, augmented reality, and the like. In the technical scheme of the application, the somatosensory equipment collects somatosensory data of a user, wherein the somatosensory data comprises three-axis angular velocity data and three-axis acceleration data.
Alternatively, the somatosensory device adopted in the technical scheme of the application comprises, but is not limited to, a mobile phone with a gyroscope, a bracelet, a watch, a ring, a handle, a wrist strap and the like.
Further, the gyroscope measures the direction and angular velocity of the device by sensing the force and acceleration of rotation and rotation to output gyroscope data. Gyroscopes typically provide a data output in three axes (X, Y, Z). For each axis, the gyroscope will provide a continuously varying value indicative of the rotational rate or angular change in that axis. These values are typically expressed in units of angular velocity (e.g., degrees/second) or units of angle (e.g., degrees).
Alternatively, the connection between the motion sensing device and the game terminal can be realized by USB, bluetooth or 2.4G, and the game terminal is a terminal running motion sensing game, and can be a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palm machine, or a fixed terminal such as a desktop computer, a home host machine, etc.
After the motion sensing game is started, the game terminal may slave motion sensing device gyroscope data based on a connection protocol with the motion sensing device.
S20, generating a current curve of the angle of the somatosensory device according to the gyroscope data.
Specifically, the gyroscope data can be converted into an angle value of the somatosensory device through a rotation matrix method, a quaternion algorithm method and the like, and then a current curve of the angle value of the somatosensory device changing along with time is calculated based on a mapping relation between the angle value and a time sequence.
In this case, the generated curve may be smoothed in order to improve the accuracy and stability of the curve. Common smoothing methods include techniques such as sliding window averaging, kalman filtering, or spline interpolation. These methods can help remove noise or drift in the gyroscope data, making the curve smoother and more reliable.
It should be noted that when converting gyroscope data, we can perform preprocessing such as filtering, interpolation, normalization, etc. on the data to improve the quality and usability of the data.
S30, calculating the similarity between the current curve and a preset sample curve.
Wherein, the similarity is a measurement index for measuring the similarity or the proximity degree between the current curve and the sample curve. Since the current curve and the sample curve are mathematical expressions of the current hitting action and the preset standard hitting action of the user, respectively, the similarity is used to represent the similarity degree between the current hitting action of the user and the preset standard hitting action in the technical scheme of the application.
Further, the sample curve is a set of predefined standard motion curves for comparison and similarity calculation with the actual generated current curve. They represent a desired, standard performance of the action. The sample curve can be recorded by collecting action data of professionals or learned by using a machine learning algorithm.
Alternatively, the similarity between the current curve and the sample curve may be calculated by measuring the fraiche distance, euclidean distance, cosine similarity, pearson correlation coefficient, and the like.
S40, judging whether the player finishes the standard batting action according to the similarity.
Specifically, after the similarity between the current curve and the preset sample curve is obtained, it can be determined whether the player has completed the standard batting action by comparing the similarity with the preset threshold. Specifically, if the similarity between the current curve and the sample curve exceeds a threshold, the player is considered to have completed a standard batting action. Otherwise, it is determined that the player does not complete the standard striking motion.
It should be noted that the preset threshold may be adjusted according to the actual game requirement and design, which is not particularly limited by the present application.
It can be appreciated that the angle change curve of the somatosensory device reflects the action characteristics of the user body to a certain extent, and by comparing the similarity between the current curve and the preset sample curve, whether the user has completed the standard batting action can be more accurately judged. Moreover, the method for identifying the angle change curve can be applied to various batting actions, and is not limited to specific hardware equipment. As long as proper gyroscope data is available, the method can be implemented in the Unity engine, so that the method has better generalization. Further, by adjusting the threshold value of the similarity, the sensitivity of the recognition can be controlled. According to actual demands, parameters can be adjusted to adapt to the batting action performances of different users.
And S50, if yes, controlling the game character to execute batting operation.
Where a game character refers to a virtual character that is controlled by a player in a game, which may be generated by default by the system or may be customized by the player.
Specifically, after it is determined that the player has completed the standard batting action, the batting operation can be simulated by changing the position, speed, animation, etc. of the game character.
It can be understood that in the body feeling tennis game method based on the unit engine, the current curve of the angle of the body feeling device, which changes along with time, is generated through the gyroscope data, and then the similarity between the current curve and the sample curve is compared to judge whether the player completes the standard batting action, wherein the angle change curve of the body feeling device reflects the action characteristics of the body of the user to a certain extent, and whether the user completes the standard batting action can be judged more accurately through comparing the similarity between the current curve and the preset sample curve. Moreover, the method for identifying the angle change curve can be applied to various batting actions, and is not limited to specific hardware equipment. As long as proper gyroscope data is available, the method can be implemented in the Unity engine, so that the method has better generalization. Further, by adjusting the threshold value of the similarity, the sensitivity of the recognition can be controlled. According to actual demands, parameters can be adjusted to adapt to the batting action performances of different users. Compared with the traditional motion recognition mode of the motion sensing game, the motion sensing tennis game method based on the unit engine has the advantages of being high in motion recognition precision, high in generalization and the like.
In some embodiments, generating a current curve of the angle of the somatosensory device over time from the gyroscope data comprises:
s21, generating a grid coordinate system formed by a plurality of grid units and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game.
The grid coordinate system is a coordinate system, which is generally composed of a plurality of grid cells, for representing a position and locating an object in a two-dimensional or three-dimensional space. Each grid cell has a unique coordinate value for determining its position in the grid coordinate system. By using a grid coordinate system, the space can be divided into discrete grid cells, each cell having a well-defined position. Such discrete representations may be used to track the position, path, and proximity of objects, etc. The grid coordinate system may be represented and stored on the gaming terminal in a two-dimensional array or other data structure.
Specifically, after the motion sensing game is started, a grid coordinate system can be constructed based on preset initialization parameters, and the grid map can be a two-dimensional coordinate system or a three-dimensional coordinate system. It should be noted that, according to the preset initialization parameters, the size of each grid cell and the coordinate value of each grid cell are determined while generating the grid coordinate system.
Further, a rigid body refers to an object having a fixed shape and mass in the physical world, and not being deformed or bent. The virtual rigid body is then a virtual model with corresponding physical properties. In the technical scheme of the application, the virtual rigid body is used for recording the position of the somatosensory equipment in the grid coordinate system.
S22, calculating the angle value of the virtual rigid body in each time step according to the gyroscope data.
Where Time Step (Time Step) refers to the Time interval represented by each Step during the simulation or emulation. It determines how often the simulation or emulation system updates state and calculations at each time step. In a virtual environment or game, the time step is typically a fixed time interval, such as a time per frame.
In particular, the gyroscope data provides information about the rotation and tilt of the somatosensory device. By processing these data, the angle values of the virtual rigid body at different points in time can be calculated.
In particular, the angle value of the virtual rigid body within each time step may be calculated by a method of integrating the gyroscope data.
S23, updating the position of the virtual rigid body on the grid map according to the angle value, and recording coordinate values of grid cells through which the virtual rigid body passes.
Specifically, an angle data structure may be created to store coordinate data of grid cells through which the virtual rigid body passes, and the coordinate data may be represented using data structures such as an array, a list, a matrix, and the like. In the game process, the coordinate values of the grid units where the virtual rigid bodies are located can be recorded into an angle data structure according to the time sequence to serve as angle change data of the somatosensory equipment in space.
S24, generating a current curve of the somatosensory equipment according to the recorded coordinate values.
Specifically, a current curve of the somatosensory device is generated from the recorded trajectory data. This may be achieved by processing and analyzing the curve data, such as by smoothing, interpolation or curve fitting. The current curve generated may be used to determine the actions of the player and to control the movement of the game object.
It will be appreciated that the above scheme may convert a continuous sequence of coordinates into a discrete sequence of grid cells by representing the angle change data of the somatosensory device as processed grid coordinates. In this way, small changes between adjacent coordinates in the middle are removed, so that redundancy and repetition of data can be reduced, representation and storage of the data are optimized, and calculation efficiency of angle changes can be improved.
In some embodiments, generating a current profile of the somatosensory device from the recorded coordinate values comprises:
s241, taking the current moment as the end point of the batting action interval;
s242, taking a historical time which is set with a time interval from the current time as a starting point of a batting action interval;
s243, generating the current curve according to the coordinate data from the starting point to the ending point.
Here, the start point-to-end point coordinate data refers to coordinate data of a time stamp between the start point time and the end point time.
Specifically, the data from the start point to the end point may be differenced by an interpolation algorithm to generate an angle change curve of the somatosensory device. Among these, interpolation algorithms are one method for estimating unknown data points between known data points. It determines the value of an unknown data point by calculation and inference based on the relationship between known data points. Interpolation algorithms can create continuous and smooth functions or curves between data points to estimate data values at locations outside of the data points.
Alternatively, a current curve of the somatosensory device may be generated using a difference algorithm such as linear interpolation, bezier curve interpolation, spline interpolation, or the like.
Illustratively, when the current curve is generated by linear interpolation, the following steps may be used:
1. traversing time range: each preset time step is traversed from a start time to an end time according to a time range of the known profile data.
2. Searching adjacent data points: the two nearest known data points are found before and after the current point in time. These data points will serve as the basis for the linear differences.
3. Calculating weights: and calculating the weight of each adjacent data point according to the time difference between the current time point and the adjacent data point. The weights may be calculated by a linear interpolation formula, such as using the inverse of the time difference as the weight.
4. Calculating the position: and calculating the position corresponding to the current time point according to the position and the weight of the adjacent data points by using a linear interpolation formula. The linear interpolation formula is: current position= (1-weight) previous position + weight next position.
5. Recording track data: and recording the current time point and the calculated position as one track data point into the generated track data set.
6. Repeating steps 1-5 until the complete time range is traversed.
The track data generated after the traversing is completed is a curve generated by the linear difference value.
It will be appreciated that the function of determining the start and end points of a batting action interval is to define a complete batting action time interval on which to base the action recognition and determination. By the arrangement, the movement of the player can be divided into discrete batting action units, so that the subsequent action recognition and analysis are convenient. And by selecting different set time lengths, the method can be quickly adapted to different game difficulties and grades so as to improve the flexibility of identifying the batting actions.
In some embodiments, the similarity between the current curve and a preset sample curve is calculated from the friendship distance.
Among these, the friendship distance is a measure of similarity between two curves, which takes into account the shape and order between the curves.
In some embodiments, calculating the friendship distance of the current curve from a preset sample curve comprises:
s31, respectively discretizing the current curve and the preset sample curve into a plurality of key points.
In particular, discretization may represent continuous curve data as a series of discrete keypoints or sampling points. The discretization process may be performed by selecting sampling at equal intervals, or adaptively selecting sampling points according to the curvature of the curve, or the like.
Further, the key point may be a specific time point on the curve, or a point having a significant meaning on the curve, such as an inflection point or an extreme point. It should be noted that each key point contains position coordinates, which may be two-dimensional coordinates or three-dimensional coordinates, and time stamp information, which may be time relative to the starting point of the curve or time from the starting point of the game.
S32, mapping the current curve and the preset sample curve to the same interval by adopting a re-parameterization function according to the time stamp of the key point.
Wherein the re-parameterized function is a function that converts the original data into a new parameterized representation. In the technical scheme of the application, the re-parameterized function is used for mapping the current curve and the sample curve to the same interval so as to compare and calculate the distance.
Specifically, the current curve and the sample curve are mapped to the same interval using a re-parameterized function according to the time stamps of the keypoints. The purpose of this is to ensure that the two curves are comparable in the time dimension so that the subsequent distance calculation is more accurate.
For example, mapping the current curve and the preset sample curve to the same interval using the re-parameterized function may be achieved by:
1. Determining a time interval: a uniform time interval is determined for use as the target interval for the mapping. This may be any selected time range, for example [0,1].
2. Extracting time information: and acquiring the timestamp information of the key points in the current curve and the sample curve. The time stamp may represent a time relative to the start of the curve or a time relative to the start of the game.
3. Standardized timestamp: for each key point's timestamp, it is normalized to the target time interval. This can be achieved by linear transformation or interpolation methods.
4. Application mapping: the time stamps in the original curve data are replaced with standardized time stamps. Thus, the current curve and the sample curve are mapped into the same time interval.
S33, calculating Euclidean distances of the current curve and the preset sample curve under each corresponding key point.
Among these, euclidean distance is a common distance metric used to measure the difference between two vectors.
Specifically, the distance between two key points can be calculated by a euclidean distance calculation formula.
S34, selecting the maximum distance as the French distance.
Specifically, the maximum distance is selected from euclidean distances of all the key points as the furcher distance.
It is worth noting that if the number of data points of the current curve and the sample curve are not identical, an interpolation algorithm may be used to align them. For example, a linear interpolation or spline interpolation method may be used to match the number of data points for the two curves.
It will be appreciated that the friendship distance considers the similarity of the entire curve, not just the similarity of a single point or local area. This enables it to more fully evaluate the differences between the curves and provide a more accurate similarity measure. Furthermore, the French distance is a mathematically well-defined measure with good properties and demonstrable mathematical properties. This makes it more reliable and trustworthy in calculating and comparing similarities. Furthermore, the French distance can be calculated by different algorithms and techniques, and thus has high expansibility.
It should be noted that the calculated furthermost distance may be directly used as the similarity, or a normalized function or conversion formula may be used to map the obtained furthermost distance value into the range of the similarity. For example, the similarity may be expressed using a ratio of 1 minus the distance value.
In some embodiments, before calculating the similarity between the current curve and the preset sample curve, the method further comprises:
S110, confirming the batting direction of the current batting action according to the gyroscope data.
Specifically, the motion direction information of the user can be acquired using the gyroscope data. According to the rotation rate or the angle change in the gyroscope data, the user can judge the batting directions of batting leftwards, rightwards, forward batting and the like.
S120, selecting a plurality of sample curves from a preset sample curve library according to the ball striking direction to serve as preset sample curves.
Specifically, according to the determined batting direction, a sample curve corresponding to the direction is selected from a sample curve library prepared in advance as a preset sample curve. The sample curve library may contain sample curves for various ball striking directions to cover different action situations.
It will be appreciated that selecting an appropriate sample profile may better match and compare with the actual striking motion of the user, thereby improving the accuracy and reliability of the determination.
In some embodiments, determining whether the player has completed a standard batting action based on the similarity includes:
s41, simultaneously calculating the similarity between the current curve and a plurality of preset sample curves to obtain a plurality of similarities;
s42, if any one of the similarity is larger than the preset threshold, judging that the user finishes the standard batting action.
Specifically, when determining whether the player has completed a standard batting action, the plurality of similarities may be compared to a preset threshold. If any of the plurality of similarities is greater than a preset threshold, it is determined that the player has completed a standard batting action. This means that the current curve has a high similarity to the shape and motion characteristics of the at least one sample curve, meeting the standard ball striking action requirements.
It will be appreciated that different persons may have different exercise habits and body structures, and thus a single sample curve may not cover all situations. By adopting a plurality of sample curves at the same time, different types and changing translation actions can be considered, and the adaptability to different users is improved. Furthermore, a single sample curve may be sensitive to noise, errors, or variations in certain conditions. By using multiple sample curves, the effects of outlier data or errors can be reduced, increasing the robustness and stability of the algorithm. And, through calculating the similarity of current curve and a plurality of sample curves, the evaluation result of a plurality of sample curves can be considered comprehensively. The comprehensive judgment can reduce the possibility of misjudgment and improve the accuracy and reliability of judgment.
In some embodiments, determining whether the player has completed a standard tennis action based on the similarity includes:
s51, carrying out normalization processing on the similarity;
s52, comparing the similarity after normalization processing with a preset threshold;
and S53, if the normalized similarity is larger than a preset threshold, judging that the user finishes the standard batting action.
Specifically, the normalization process may be accomplished by:
1. determining the maximum value and the minimum value of the similarity: first, the maximum and minimum values of the similarity calculation need to be determined. This may be determined by the maximum and minimum similarity in the sample dataset, or set according to the specific needs of the problem.
2. Linear normalization of similarity: linear normalization is a commonly used normalization method that can linearly map similarity values to a specified range, such as [0,1] or [ -1,1].
For the range [0,1], the formula can be used: normalized similarity= (original similarity-minimum similarity)/(maximum similarity-minimum similarity);
for the range [ -1,1], the formula can be used: normalized similarity = 2 ((original similarity-minimum similarity)/(maximum similarity-minimum similarity)) -1;
The original similarity is a calculated similarity value.
It can be appreciated that by normalizing the similarity, the dimensional influence of the similarity value can be eliminated, and the similarity value is ensured to be within a certain range, so that the similarity value is more interpretable and comparable. Therefore, the similarity degree of the current curve and the preset sample curve can be judged more conveniently, and corresponding action judgment can be carried out according to the requirement.
In addition, referring to fig. 3, an embodiment of the present invention further provides a unit-engine-based somatosensory tennis game apparatus, where the unit-engine-based somatosensory tennis game apparatus includes:
an acquisition module 110, configured to acquire gyroscope data from the bound somatosensory device after the somatosensory game is started;
a generating module 120, configured to generate a current curve of the angle of the somatosensory device according to the gyroscope data;
the calculating module 130 is configured to calculate a similarity between the current curve and a preset sample curve;
a judging module 140, configured to judge whether the player completes the standard batting action according to the similarity;
and the execution module 150 is used for controlling the game role to execute the batting operation after judging that the player completes the standard batting action.
The steps implemented by each functional module of the unit-based motion sensing tennis game device may refer to each embodiment of the unit-based motion sensing tennis game method according to the present invention, and will not be described herein.
In addition, the embodiment of the invention also provides a computer readable storage medium, which can be any one or any combination of a plurality of hard disk, a multimedia card, an SD card, a flash memory card, an SMC, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory and the like. The computer readable storage medium includes the motion-based tennis game program 10, and the embodiment of the computer readable storage medium of the present invention is substantially the same as the motion-based tennis game method and the embodiment of the server 1, and will not be described herein.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims (10)

1. A method of a somatosensory tennis game based on a units engine, comprising:
After the somatosensory game is started, acquiring gyroscope data from the bound somatosensory equipment;
generating a current curve of the angle of the somatosensory equipment according to the gyroscope data;
calculating the similarity between the current curve and a preset sample curve;
judging whether the player finishes the standard batting action according to the similarity;
if yes, the game role is controlled to execute batting operation.
2. The method for a unit engine-based motion sensing tennis game according to claim 1, wherein generating a current curve of an angle of a motion sensing device with time from the gyro data comprises:
generating a grid coordinate system formed by a plurality of grid units and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
calculating an angle value of the virtual rigid body in each time step according to the gyroscope data;
updating the position of the virtual rigid body on the grid coordinate system according to the angle value, and recording the coordinate value of a grid unit through which the virtual rigid body passes;
and generating a current curve of the somatosensory equipment according to the recorded coordinate values.
3. The method for a unit-based motion sensing tennis game according to claim 2, wherein generating a current curve of the motion sensing device according to the recorded coordinate values comprises:
Taking the current moment as the end point of the batting action interval;
taking the historical moment which is set with the time interval from the current moment as the starting point of the batting action interval;
and generating the current curve according to the coordinate data from the starting point to the ending point.
4. The method for a unit-based motion-induced tennis game according to claim 1, wherein the similarity between the current curve and a preset sample curve is calculated according to the friechet distance.
5. The method for a unit-based motion-induced tennis game according to claim 4, wherein before calculating the similarity between the current curve and the preset sample curve, the method further comprises:
confirming the batting direction of the current batting action according to the gyroscope data;
and selecting a plurality of sample curves from a preset sample curve library according to the ball striking direction to serve as preset sample curves.
6. The method for a unit-based motion sensing tennis game according to claim 5, wherein determining whether the player has completed the standard batting action based on the similarity comprises:
meanwhile, calculating the similarity between the current curve and a plurality of preset sample curves to obtain a plurality of similarities;
If any one of the plurality of similarities is greater than the preset threshold, determining that the user has completed a standard batting action.
7. The method for motion sensing running game of unit engine according to claim 6, wherein determining whether the player has completed the standard tennis motion based on the similarity comprises:
normalizing the similarity;
comparing the similarity after normalization treatment with a preset threshold value;
if the normalized similarity is greater than a preset threshold, judging that the user finishes the standard batting action.
8. A unity engine-based motion sensing tennis game apparatus comprising:
the acquisition module is used for acquiring gyroscope data from the bound somatosensory equipment after the somatosensory game is started;
the generation module is used for generating a current curve of the angle of the somatosensory equipment along with the time change according to the gyroscope data;
the calculation module is used for calculating the similarity between the current curve and a preset sample curve;
the judging module is used for judging whether the player finishes the standard batting action according to the similarity;
and the execution module is used for controlling the game character to execute the batting operation after judging that the player completes the standard batting action.
9. A unit engine based motion sensing tennis game apparatus comprising a memory, a processor and a unit engine based motion sensing tennis game program stored on the memory and executable on the processor, wherein the processor implements the unit engine based motion sensing tennis game method of any one of claims 1-7 when executing the unit engine based motion sensing tennis game program.
10. A computer readable storage medium, wherein a units engine based somatosensory tennis game program is stored on the computer readable storage medium, which when executed by a processor implements the units engine based somatosensory tennis game method according to any one of claims 1-7.
CN202310661671.1A 2023-06-05 2023-06-05 Somatosensory tennis game method based on units engine Pending CN116650953A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310661671.1A CN116650953A (en) 2023-06-05 2023-06-05 Somatosensory tennis game method based on units engine

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310661671.1A CN116650953A (en) 2023-06-05 2023-06-05 Somatosensory tennis game method based on units engine

Publications (1)

Publication Number Publication Date
CN116650953A true CN116650953A (en) 2023-08-29

Family

ID=87709365

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310661671.1A Pending CN116650953A (en) 2023-06-05 2023-06-05 Somatosensory tennis game method based on units engine

Country Status (1)

Country Link
CN (1) CN116650953A (en)

Similar Documents

Publication Publication Date Title
US10671842B2 (en) Methods of determining handedness for virtual controllers
US20130010071A1 (en) Methods and systems for mapping pointing device on depth map
US9144744B2 (en) Locating and orienting device in space
US20140009384A1 (en) Methods and systems for determining location of handheld device within 3d environment
CN105229666A (en) Motion analysis in 3D rendering
KR102241414B1 (en) Electronic device for providing a feedback for a specivic motion using a machine learning model a and machine learning model and method for operating thereof
KR101959840B1 (en) Method and program for making order choice model
CN114949839A (en) Swimming posture-based motion sensing game method
KR20210054349A (en) Method for predicting clinical functional assessment scale using feature values derived by upper limb movement of patients
CN108051001A (en) A kind of robot movement control method, system and inertia sensing control device
CN116650953A (en) Somatosensory tennis game method based on units engine
CN116637363A (en) Somatosensory game method based on units engine
JP2018015436A (en) Analyzer for behavior of hitting tool
KR101962045B1 (en) Apparatus and method for testing 3-dimensional position
CN116637361A (en) Body feeling boxing game method based on units engine
US20220223065A1 (en) Robot control system for coding education
KR101869304B1 (en) System, method and program for recognizing sign language
CN116637362A (en) Somatosensory running game method based on units engine
CN116637359A (en) Somatosensory jump game method based on units engine
CN117504294A (en) Method for realizing somatosensory basketball game based on function fitting
CN117379791A (en) Somatosensory game method for realizing beating action recognition based on function fitting
CN116637360A (en) Motion sensing table tennis game method based on function fitting
CN114202799A (en) Method and device for determining change speed of controlled object, electronic equipment and storage medium
CN113706606A (en) Method and device for determining position coordinates of spaced gestures
CN116889729A (en) Motion sensing boxing game method based on function fitting

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination