CN116650952A - Somatosensory skiing game method based on function fitting - Google Patents

Somatosensory skiing game method based on function fitting Download PDF

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Publication number
CN116650952A
CN116650952A CN202310658248.6A CN202310658248A CN116650952A CN 116650952 A CN116650952 A CN 116650952A CN 202310658248 A CN202310658248 A CN 202310658248A CN 116650952 A CN116650952 A CN 116650952A
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Prior art keywords
skiing
function
somatosensory
data
fitting
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Inventor
张可
黄鹏飞
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Shenzhen Shimi Network Technology Co ltd
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Shenzhen Shimi Network Technology Co ltd
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Priority to CN202310658248.6A priority Critical patent/CN116650952A/en
Publication of CN116650952A publication Critical patent/CN116650952A/en
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    • 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
    • A63F13/807—Gliding or sliding on surfaces, e.g. using skis, skates or boards
    • 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
    • A63F2300/8041—Skating using skis, skates or board

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  • 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)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a somatosensory skiing game method, a device, equipment and a computer readable storage medium based on function fitting, wherein the method comprises the following steps: after the somatosensory skiing game is started, somatosensory data are acquired from the bound somatosensory equipment; fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user; identifying skiing actions completed by a user according to the sliding action function; and controlling the game character to execute skiing operation according to the skiing action completed by the user. The somatosensory skiing game method based on function fitting has the advantages of high motion recognition precision, strong generalization, high flexibility, simplicity, high efficiency and the like.

Description

Somatosensory skiing game method based on function fitting
Technical Field
The invention relates to the technical field of somatosensory games, in particular to a somatosensory skiing game method, a device and equipment based on function fitting and a computer readable storage medium.
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-sensing game 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 track 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 somatosensory skiing game method based on function fitting, which aims to improve the accuracy and generalization of skiing action recognition in somatosensory skiing games.
After the somatosensory skiing game is started, somatosensory data are acquired from the bound somatosensory equipment;
fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user;
identifying skiing actions completed by a user according to the sliding action function;
and controlling the game character to execute skiing operation according to the skiing action completed by the user.
In an embodiment, the somatosensory data includes acceleration data and angular velocity data;
fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user, comprising:
comparing the acceleration data with a first preset threshold;
if the acceleration data is smaller than a first preset threshold value, fitting a skiing overturning action function according to the gyroscope data;
and if the acceleration data is larger than a first preset threshold value, fitting a skiing jump action function according to the acceleration data.
In one embodiment, fitting a ski rollover motion function based on the gyroscope data includes:
generating track data of the motion of the somatosensory device in space according to the gyroscope data;
substituting the track data into a preset polynomial function for fitting to obtain the skiing overturning action function.
In an embodiment, generating trajectory data of motion of the motion sensing device in space from the gyroscope data includes:
generating a grid map composed of a plurality of grid cells and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
updating the position of the virtual rigid body in the grid map according to the gyroscope data;
And recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the virtual rigid body in the grid map as the track data.
In an embodiment, fitting a ski-jump motion function from the acceleration data comprises:
generating speed change data of the speed of the somatosensory equipment along with time according to the acceleration data;
and importing the speed change data into a preset linear function fitting to obtain the skiing jump action function.
In an embodiment, generating speed change data of the speed of the motion sensing device over time according to the acceleration data includes:
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;
updating the position of the virtual rigid body in the grid coordinate system according to the acceleration;
and recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the grid coordinate system as the speed change data.
In an embodiment, identifying the skiing performed by the user according to the sliding motion function comprises:
Calculating a first similarity between the skiing overturn motion function and a preset skiing overturn motion function;
calculating the second similarity of the skiing jump action function and the preset skiing jump action function;
if the first similarity is larger than a second preset threshold value, judging that the user finishes the skiing overturning action;
and if the second similarity is larger than a third preset threshold value, judging that the user adds the skiing jumping action.
In order to achieve the above object, an embodiment of the present application further provides a somatosensory skiing game device implemented based on function fitting, including:
the acquisition module is used for acquiring somatosensory data from the bound somatosensory equipment after the somatosensory skiing game is started;
the fitting module is used for fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user;
the identification module is used for identifying the skiing actions completed by the user according to the sliding action function;
and the execution module is used for controlling the game character to execute skiing operation according to the skiing action completed by the user.
To achieve the above objective, an embodiment of the present application further provides a somatosensory ski game device implemented based on function fitting, including a memory, a processor, and a somatosensory ski game program implemented based on function fitting stored on the memory and executable on the processor, where the processor implements the somatosensory ski game method implemented based on function fitting according to any one of the above when executing the somatosensory ski game program implemented based on function fitting.
To achieve the above object, an embodiment of the present application further provides a computer readable storage medium, where a somatosensory skiing game program implemented based on function fitting is stored, and when the somatosensory skiing game program implemented based on function fitting is executed by a processor, the somatosensory skiing game method implemented based on function fitting as described in any one of the above is implemented.
It can be understood that according to the somatosensory skiing game method based on function fitting, the skiing action function is obtained by fitting the somatosensory trajectory data, and finally the skiing action type of the user is identified based on the skiing action function and the game character is controlled to execute corresponding skiing action operation. By fitting the function, details and characteristics of the skiing action can be accurately captured, so that the real skiing action characteristics are reflected more accurately, and the accuracy of action recognition is improved. On the other hand, the universal action mode and rule can be learned from the sample data through function fitting, so that the identification of new skiing actions is realized, and the generalization of the identification of the skiing action types is improved. In addition, the function fitting method can select different function forms according to actual requirements to model the skiing action. The flexibility enables the function fitting method to adapt to different types of skiing actions, and has high adaptability and expansibility. In addition, the calculation and classification of the skiing action function can be completed in a short time, and the game running efficiency is improved. Compared with the traditional somatosensory game scheme, the somatosensory skiing game method has the advantages of high motion recognition precision, strong generalization, high flexibility, simplicity, high efficiency 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 motion sensing ski game device implemented based on function fitting in accordance with the present invention;
FIG. 2 is a flow chart of an embodiment of a somatosensory skiing game method based on function fitting according to the present invention;
FIG. 3 is a block diagram of one embodiment of a motion sensing ski game device based on a function fit implementation 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 somatosensory skiing game device implemented based on function fitting) 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 to store application software installed in the server 1 and various types of data, such as codes of the somatosensory ski game program 10 implemented based on function fitting, but also to temporarily store 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 motion sensing ski game program 10 implemented based on function fitting, etc.
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 with components 11-13 and a somatosensory ski game program 10 implemented based on function fitting, it will be understood by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation 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 somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
after the somatosensory skiing game is started, somatosensory data are acquired from the bound somatosensory equipment;
fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user;
identifying skiing actions completed by a user according to the sliding action function;
and controlling the game character to execute skiing operation according to the skiing action completed by the user.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
comparing the acceleration data with a first preset threshold;
if the acceleration data is smaller than a first preset threshold value, fitting a skiing overturning action function according to the gyroscope data;
And if the acceleration data is larger than a first preset threshold value, fitting a skiing jump action function according to the acceleration data.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
generating track data of the motion of the somatosensory device in space according to the gyroscope data;
substituting the track data into a preset polynomial function for fitting to obtain the skiing overturning action function.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
generating a grid map composed of a plurality of grid cells and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
updating the position of the virtual rigid body in the grid map according to the gyroscope data;
and recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the virtual rigid body in the grid map as the track data.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
Generating speed change data of the speed of the somatosensory equipment along with time according to the acceleration data;
and importing the speed change data into a preset linear function fitting to obtain the skiing jump action function.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the 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;
updating the position of the virtual rigid body in the grid coordinate system according to the acceleration;
and recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the grid coordinate system as the speed change data.
In one embodiment, the processor 12 may be configured to call a somatosensory ski game program based on a function fit implementation stored in the memory 11, and perform the following operations:
calculating a first similarity between the skiing overturn motion function and a preset skiing overturn motion function;
calculating the second similarity of the skiing jump action function and the preset skiing jump action function;
If the first similarity is larger than a second preset threshold value, judging that the user finishes the skiing overturning action;
and if the second similarity is larger than a third preset threshold value, judging that the user adds the skiing jumping action.
Based on the hardware architecture of the somatosensory skiing game equipment realized based on function fitting, the embodiment of the somatosensory skiing game method realized based on function fitting is provided. The invention discloses a somatosensory skiing game method based on function fitting, which aims to improve accuracy and generalization of skiing action recognition in somatosensory skiing games.
Referring to fig. 2, fig. 2 is an embodiment of a somatosensory skiing game method implemented based on function fitting according to the present invention, the somatosensory skiing game method implemented based on function fitting includes the following steps:
and S10, after the somatosensory skiing game is started, acquiring somatosensory data from the bound somatosensory equipment.
Wherein the somatosensory game is a somatosensory skiing game which is a virtual reality game based on somatosensory technology, and the player can participate in skiing experience in a real mode by using special sensors and devices. In contrast to conventional gamepads or keyboards, a somatosensory skiing game converts the actual actions and gestures of a player into skiing actions in the game by capturing them.
Alternatively, the somatosensory ski game may 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 somatosensory data (Motion Sensing Data) refers to information about human motions and postures collected by somatosensory devices (e.g., accelerometers, gyroscopes, posture sensors, etc.). These data may reflect the physical actions, accelerations, rotations, etc. of the user.
By way of example, the somatosensory data includes acceleration data, angular velocity data, posture data, position data, and the like. The acceleration data is data collected through an accelerometer, represents the acceleration change condition of a user, and can be used for detecting the acceleration, the deceleration, the movement direction and the like of the user. The angular velocity data is data collected by a gyroscope or a rotation sensor, and indicates a change in angular velocity of the user, and can be used to detect operations such as rotation and steering of the user. The posture data is data collected by a posture sensor or other sensors, and represents body posture information of the user, and can be used to detect posture changes of the user, movements of body parts, and the like. The location data is location coordinate data of the user acquired using a Global Positioning System (GPS).
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 somatosensory ski game is initiated, the gaming terminal may slave somatosensory device gyroscope data based on a connection protocol with the somatosensory device.
And S20, fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user.
Wherein the sliding motion function is a mathematical function for representing the current sliding motion of the user. By performing function fitting on the somatosensory data, a function model which can accurately describe the sliding motion of the user can be obtained. The sliding motion function may output a value or a set of values representing a sliding motion characteristic of the user based on the user's somatosensory data input. This function may be a linear function, a non-linear function, or another form of function, depending on the function fitting algorithm used and the desired accuracy of the representation.
Further, the function fitting is to compare the somatosensory data with the function model, and select the most suitable function parameters so as to minimize the error between the function model and the actual data. Common function fitting algorithms include least squares, curve fitting, polynomial fitting, and the like.
The selection and fitting of the sliding motion function may be designed according to the specific somatosensory ski game requirements. For example, a function may be fitted to represent the user's sliding speed and sliding direction based on the user's acceleration and angular velocity data; or based on the user's body posture data, fitting a function to represent the user's body tilt angle and posture change.
It will be appreciated that by means of the sliding action function, the sliding action of the user can be accurately identified and mapped to the game character for performing the corresponding skiing operation. The function fitting method can achieve accurate capture and feedback of actual skiing actions of users, and immersion and interactivity of games are improved.
S30, identifying the skiing actions completed by the user according to the sliding action function.
In the sense of a body, the skiing action refers to various actions and sequences of actions during the simulated skiing performed by the user. These actions may simulate various action elements in real skiing, such as steering, acceleration, deceleration, jumping, etc.
Illustratively, in the solution of the present application, the somatosensory ski game may comprise at least one of the following skiing actions: steering, acceleration, deceleration, turning, and jumping.
Specifically, in order to identify the skiing performed by the user based on the skiing function, some threshold value or range may be set to determine the skiing performed by the user based on the specific skiing game requirements. Or designing an action classifier or usage rules to determine the specific type of skiing action performed by the user based on different skiing action functions and game requirements. For example, whether the user is steering, decelerating, or controlling a jump is determined based on the change in acceleration and angular velocity.
It will be appreciated that the identification of the type of skiing action is performed using a function fit, in one aspect, the function fit method may model and describe the user's skiing action based on actual skiing trajectory data. By fitting the function, details and characteristics of the skiing action, including starting point, end point, trajectory shape, speed change, etc., can be accurately captured. Compared with other sensors or methods based on rules, the function fitting reflects the real skiing action characteristics more accurately, and the accuracy of action recognition is improved.
On the other hand, the function fitting method can obtain a general skiing function model through fitting based on the collected multiple groups of sample data. The model can be used for identifying skiing actions of different users and under different scenes, and has certain generalization capability. Through function fitting, a universally applicable action mode and rule can be learned from sample data, and the identification of a new skiing action is realized. The generalization of the method enables the function fitting method to have strong adaptability and practicability.
In addition, the function fitting method can select different function forms according to actual requirements to model the skiing action. According to the specific case, polynomial functions, trigonometric functions, gaussian functions, etc. may be selected to fit the ski trajectory data. The flexibility enables the function fitting method to adapt to different types of skiing actions, and has high adaptability and expansibility. And the function fitting method can be used for quickly calculating and deducing, so that the action recognition can be applied in a real-time scene. The calculation and classification of the skiing function can be completed in a short time, and the running efficiency of the game is improved.
S40, controlling the game role to execute skiing operation according to the skiing action completed by the user.
Specifically, in a somatosensory ski game, there is a corresponding game operation instruction for each type of skiing action. For example, for a rolling skiing action, the game character may be controlled to tilt according to the identified direction; for acceleration and deceleration skiing actions, the speed of the game character may be increased or decreased accordingly; for jumping skiing actions, the game role can be controlled to jump; for the overturn skiing action, the game character is controlled to take off and overturn in the air.
The specific control mode and operation details can be adjusted and realized according to the characteristics of the game design and development platform.
Based on the above, after the type of skiing action performed by the user is determined, the corresponding instruction can be transmitted to the game character for execution according to the game operation instruction corresponding to the identified action type. This may be accomplished through interaction with a game engine or controller, such as by way of a programming interface, controller input, or the like, that communicates instructions to the gaming system. Thus, the user can perform the reproduction of the skiing operation.
It can be understood that according to the somatosensory skiing game method based on function fitting, the skiing action function is obtained by fitting the somatosensory trajectory data, and finally the skiing action type of the user is identified based on the skiing action function and the game character is controlled to execute corresponding skiing action operation. By fitting the function, details and characteristics of the skiing action can be accurately captured, so that the real skiing action characteristics are reflected more accurately, and the accuracy of action recognition is improved. On the other hand, the universal action mode and rule can be learned from the sample data through function fitting, so that the identification of new skiing actions is realized, and the generalization of the identification of the skiing action types is improved. In addition, the function fitting method can select different function forms according to actual requirements to model the skiing action. The flexibility enables the function fitting method to adapt to different types of skiing actions, and has high adaptability and expansibility. In addition, the calculation and classification of the skiing action function can be completed in a short time, and the game running efficiency is improved. Compared with the traditional somatosensory game scheme, the somatosensory skiing game method has the advantages of high motion recognition precision, strong generalization, high flexibility, simplicity, high efficiency and the like.
In some embodiments, fitting the somatosensory data to obtain a ski action function representing a current sliding action of the user comprises:
s21, comparing the acceleration data with a first preset threshold value.
Specifically, the collected acceleration data is compared to a first preset threshold value prior to fitting the ski action function. If the acceleration data is smaller than the first preset threshold value, executing step S22; if the acceleration data is greater than the first preset threshold, step S23 is performed.
And S22, if the acceleration data is smaller than a first preset threshold value, fitting a skiing overturning action function according to the gyroscope data.
In particular, if the acceleration data is less than a first preset threshold, it is indicated that the user's skiing action may be a roll-over action. In this case, the gyroscope data may be used to fit a ski rollover motion function. The gyroscope data may provide information about the user's rotation. By inputting the gyroscope data into the fitting algorithm, a skiing rollover motion function may be obtained that is representative of the current rollover motion characteristics of the user.
S23, if the acceleration data is larger than a first preset threshold value, fitting a skiing jump action function according to the acceleration data.
Specifically, if the acceleration data is equal to or greater than a first preset threshold, it is indicated that the user's skiing action may be a jumping action. In this case, the acceleration data may be used to fit a ski-jump motion function. The acceleration data may provide information about the user acceleration change. By inputting the acceleration data into the fitting algorithm, a ski jump function can be obtained that is representative of the current jump motion characteristics of the user.
Based on the above steps, the user's skiing action is classified into two different types by comparing the acceleration data with a first preset threshold value: a flipping motion and a jumping motion. This allows classifying the user's actions more accurately, providing finer action recognition.
In addition, for the overturning action, the rotation information of the user can be better captured by using the gyroscope data; for jumping actions, the acceleration data may be used to more accurately reflect the acceleration changes of the user. In this way, fitting can be performed by using different data sources according to different action types, thereby helping to improve the accuracy and reliability of the skiing action function.
It is worth noting that different skiing action types and user requirements can be flexibly adapted by setting threshold values and using different fitting algorithms. The method can be extended to more types of skiing actions and adjusted and optimized according to actual conditions.
In some embodiments, fitting a ski rollover motion function from the gyroscope data includes:
s221, generating track data of the motion of the somatosensory device in space according to the gyroscope data.
Wherein the trajectory data is used to record the motion trajectory of the somatosensory device in space to represent the skiing action trajectory of the user.
Specifically, the gyroscope data may be converted into spatial coordinate values by a rotation matrix, a quaternion algorithm, or the like, and the spatial coordinate values are mapped with a time sequence to generate trajectory data of the somatosensory device in space.
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.
S222, substituting the track data into a preset polynomial function for fitting to obtain the skiing overturning action function.
Specifically, the predetermined polynomial function is a cubic polynomial function. The predetermined cubic polynomial function is a mathematical function model selected according to specific somatosensory skiing game requirements and designs, which is essentially a mathematical representation of skiing actions. That is, the skiing function obtained by fitting the trajectory data of the somatosensory device is a mathematical representation of the current skiing action of the user.
It will be appreciated that the cubic polynomial function has a smoothing characteristic that helps reduce the effects of noise and oscillations in the beat data, thereby minimizing the effects of gyroscope drift on motion recognition accuracy. Thus, although the drift degree of different gyroscopes can be different, the overall trend of the gyroscope data can be approximately captured by fitting the cubic polynomial function, so that the data change in a smaller range can obtain a better fitting effect. Therefore, the influence of different gyroscope drift degrees can be balanced to a certain extent through the fitting of the cubic polynomial function, and the recognition accuracy is improved.
Meanwhile, the cubic polynomial function can adapt to different types of swing actions and flexibly fit various shapes and curves. This enables it to handle variations in different swing motions, such as swings of different speed, angle or force. The coefficients and parameters of the functions are adjusted, so that the method can adapt to different types of swing actions, and the generalization and accuracy of recognition are improved.
In addition, the method of cubic polynomial function fitting is computationally simple and efficient as compared to more complex nonlinear functions or machine learning models. It does not need a lot of training data and complex training process, nor complex parameter tuning. This makes the third order polynomial function fit easier to implement and apply, reducing the complexity of processing gyroscope data.
In some embodiments, generating trajectory data of motion of the somatosensory device in space from the gyroscope data comprises:
s110, generating a grid map 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.
Among these, the grid map is an image representation method that divides a space into regular grid cells. It divides the entire space into discrete small areas, each of which is referred to as a grid cell, which may be square, rectangular or other shape. Each grid cell has a unique identifier and coordinates that represent its location throughout the map. In the technical scheme of the application, the grid map is used for representing the layout of the game scene. Each grid cell may correspond to a region or grid of fixed size for recording the position of the virtual rigid body in the game.
Specifically, after the somatosensory skiing game is started, a grid map can be constructed based on preset initialization parameters, and the grid map can be a two-dimensional map (such as a plane map) or a three-dimensional map (such as a stereoscopic scene). 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 map.
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 moving track of the somatosensory equipment in the grid map.
S120, updating the position of the virtual rigid body in the grid map according to the gyroscope data.
Specifically, the gyroscope data can be converted into coordinate values of the grid map by a motion equation, an integral method (such as an euler method or a Longer-Kutta method) and the like, so as to update the position of the virtual rigid body in the grid map.
And S130, recording coordinate data of grid cells passing through in the moving process of the virtual rigid body in the grid map as the track data.
Specifically, a data structure may be created to store coordinate data of grid cells through which the virtual rigid body passes, and the trajectory data may be represented using data structures such as arrays, lists, matrices, and the like. In the game process, the coordinate values of the grid unit where the virtual rigid body is located can be recorded into a track data structure according to the time sequence to be used as track data of the somatosensory equipment in the space.
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 trajectory 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 a motion track can be improved.
In some embodiments, the expression of the preset cubic polynomial function is as follows:
y＝ax 3 +bx 2 +cx+d；
in the formula, a, b, c, d are fitting parameters required by the fitting function respectively.
Specifically, x represents the x-axis coordinates of the grid cells in the grid map, y represents the y-axis coordinates of the grid cells in the grid map, and a, b, c, d is the corresponding coefficient and constant.
It should be noted that the design of the present application is not limited thereto, and in other embodiments, the cubic polynomial function can be set as y=a (x-h)/(3+k, y=a (x-h) ≡ 3+b (x-h) ≡ 2+c (x-h) +d, y=a (x-h) (x-p) (x-q), etc.
In some embodiments, fitting the trajectory data to a preset cubic polynomial function to obtain a swing function includes:
s210, constructing a two-dimensional matrix X according to the X-axis coordinates and the degree of a polynomial function in the coordinate data.
Specifically, assuming that there are n coordinate data points, the size of matrix X is n× (number +1). Wherein each row corresponds to an x-axis coordinate and each column corresponds to a polynomial function of degree.
For example, for a cubic polynomial function, if there are 3 coordinate data points (X1, X2, X3), then the matrix X can be expressed as:
X＝[
[x1^3,x1^2,x1,1],
[x2^3,x2^2,x2,1],
[x3^3,x3^2,x3,1]
]。
s220, constructing a one-dimensional matrix Y according to the Y-axis coordinates in the coordinate data.
Specifically, the matrix Y has a size of n×1, where each row corresponds to one Y-axis coordinate.
For example, the Y-axis coordinates (Y1, Y2, Y3) corresponding to the three coordinate data points described above, the matrix Y may be expressed as:
Y＝[
[y1],
[y2],
[y3]
]。
s230, calculating a transposed matrix XT of the matrix X.
Specifically, the size of XT is (number of times +1) ×n.
S240, calculating a product matrix XTX of the matrix XT and the matrix X.
Specifically, xtx=xt×x.
And S250, solving a linear equation XTX multiplied by C=XTY to obtain a one-dimensional matrix C, wherein the one-dimensional matrix C represents coefficients of a polynomial function, namely fitting parameters to be solved.
Specifically, c=inv (XTX) ×xt×y, where inv (XTX) represents the inverse matrix of XTX.
And S260, outputting the swing function according to the matrix C.
Specifically, the swing function may be expressed as: y=C0 x 3+C1 x 2+C2 x+C3. Wherein, C0, C1, C2, C3 are each elements of matrix C.
It will be appreciated that by the above steps S210-S260, fitting to a cubic polynomial function can be achieved with the least squares method.
In some embodiments, fitting a ski-jump motion function from the acceleration data comprises:
s310, generating speed change data of the speed change of the somatosensory equipment along with time according to the acceleration data.
In particular, the change in speed of the motion sensing device over time may be calculated by integrating the acceleration, which will produce a time series of speed data indicative of the change in speed of the motion sensing device.
In some embodiments, generating speed change data for a speed change of the motion sensing device over time from the acceleration data comprises:
s311, generating a grid coordinate system formed by a plurality of grid units and a virtual rigid body matched with the somatosensory equipment on the game terminal for executing the somatosensory game.
Specifically, on a game terminal that executes a motion sensing game, a grid coordinate system composed of a plurality of grid cells is created. At the same time, a virtual rigid body is created that matches the somatosensory device, which will be used to simulate the movement of the somatosensory device in the game space.
S312, updating the position of the virtual rigid body in the grid coordinate system according to the acceleration.
Specifically, the acceleration data provides acceleration change information of the somatosensory device in various directions. The acceleration data may be converted to velocity data by integration or other numerical methods and used to update the position of the virtual rigid body in the grid coordinate system.
And S313, recording coordinate data of grid cells passing through in the process of moving the virtual rigid body in the grid coordinate system as the speed change data.
Specifically, during the movement of the virtual rigid body, coordinate data of the grid cell through which the virtual rigid body passes is recorded. Coordinates of a grid cell where the virtual rigid body is currently located are recorded every time the virtual rigid body crosses a boundary of one grid cell. These coordinate data will be used as speed change data, representing information of the speed of the motion sensing device over time.
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 speed 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 a motion track can be improved.
S320, importing the speed change data into a preset linear function fitting to obtain the skiing jump action function.
The expression of the preset linear function is, for example,: y=ax+b; wherein y is a coordinate value in the y-axis direction in the grid coordinate system; x is a coordinate value in the x-axis direction in the grid coordinate system; a and b are fitting parameters to be solved.
Specifically, a and b represent the slope and intercept, respectively, of the linear function described above.
Specifically, the generated speed change data is imported into a preset linear function, and a fitting algorithm is used for fitting the data. The fitting algorithm can find the best linear relationship according to the distribution of the data points and generate a skiing jump action function.
It will be appreciated that the linear function y=ax+b is a simple and intuitive linear function expression that is easy to understand and implement. Meanwhile, due to the simple characteristic, the method can be quickly calculated in practical application, so that fitting efficiency is improved. Furthermore, the slope parameter a reflects the degree of inclination of the fitting line, and the intercept parameter b represents the intersection of the fitting line with the coordinate axis. The values of these parameters can be used to interpret the fitting results so that the current skiing jump can be visually represented.
Of course, the design of the present application is not limited thereto, and in other embodiments, other linear functions may be used as the preset linear function, such as y=mx; y=a o +a 1 x 1 +a 2 x 2 +...+a n x n ；y＝a 0 +a 1 x 1 +a 2 x 1 2 +...+a n x 1 n Etc.
Alternatively, a predetermined linear function may be fitted by a least square method, and the required fitting parameters a and b may be found by a minimum fit.
Specifically, the steps of fitting a preset linear function by the least square method and calculating the fitting parameters a and b are specifically as follows:
(1) Calculating the mean value of the independent variable x and the dependent variable y in the speed change data respectively expressed asAnd->
(2) Calculating the deviation between each data sample point and the mean value, respectively expressed asAnd
(3) Calculating the slope:
(4) Calculating intercept:
it will be appreciated that linear functions generally have relatively stable properties over a range. Thus, although acceleration data provided by different somatosensory devices may have a certain degree of error or drift, the fitting of the linear function can approximately capture the overall trend of the acceleration data, so that the data change in a smaller range can obtain a better fitting effect. Therefore, the influence of the drift degrees of different somatosensory devices can be balanced to a certain extent through linear function fitting, and the recognition accuracy is improved.
Moreover, the linear function fitting method is simple and efficient to calculate relative to more complex nonlinear functions or machine learning models. It does not need a lot of training data and complex training process, nor complex parameter tuning. This makes the linear function fit easier to implement and apply, reducing the complexity of processing gyroscope data.
In addition, different data sets and action types can be quickly adapted by adjusting a preset linear function, so that the adaptability of the somatosensory skiing game to different users can be improved, and the action recognition scheme has stronger generalization.
It should be noted that the design of the present application is not limited thereto, and in other embodiments, the preset linear function may be fitted by a gradient descent method, a maximum likelihood method, or the like.
It is also worth noting that in other embodiments, other more complex functional or nonlinear regression methods may be tried to better fit the characteristics and patterns of the swing.
In some embodiments, identifying a skiing action performed by a user from the sliding action function comprises:
s31, calculating the first similarity between the skiing overturn motion function and a preset skiing overturn motion function.
S32, calculating the second similarity between the skiing jump action function and the preset skiing jump action function;
s33, if the first similarity is larger than a second preset threshold value, judging that the user finishes the skiing overturning action;
and S34, if the second similarity is larger than a third preset threshold value, judging that the user performs skiing jumping operation.
Specifically, the similarity between the ski turning action function and the preset ski turning action function can be obtained by calculating the cosine similarity or euclidean distance between the ski turning action function of the user and the preset ski turning action function. Similarly, the similarity degree between the skiing overturn action function of the user and the preset skiing overturn action function can be obtained by calculating the cosine similarity or Euclidean distance and the like of the skiing jump action function of the user and the preset skiing jump action function.
For example, to calculate the Euclidean distance between the user's skiing roll-over action function and the preset skiing roll-over action function, the following steps may be performed:
step 1, acquiring a skiing turning action function and a preset skiing turning action function of a user.
And 2, ensuring that the dimensions of the two functions are the same. If the representation of the function is in vector form, it is ensured that the dimensions of the two vectors are identical. If the representation of the functions is in other forms (e.g., curves, polynomials, etc.), it is necessary to transform them into the same dimensional representation.
Step 3, subtracting corresponding components: and subtracting each component in the preset skiing turnover action function from the corresponding component in the skiing turnover action function of the user to obtain a difference vector.
Step 4, squaring each component of the difference vector: each component in the difference vector is squared.
And 5, summing the square results: and (3) summing the square results in the step (4) to obtain a sum.
Step 6, taking square root of the sum: and (5) performing square root operation on the sum in the step 5 to obtain the final Euclidean distance.
Therefore, the similarity degree between the skiing overturn action function of the user and the preset skiing overturn action function can be measured by calculating the Euclidean distance. The smaller the Euclidean distance, the smaller the difference between the two functions, and the higher the degree of similarity.
It can be understood that the second preset threshold value and the third preset threshold value are set to be used for judging whether the user finishes the skiing overturning action and the skiing jumping action respectively, so that different preset threshold values can be set according to different pertinence of the sliding action types, and the accuracy of action recognition can be improved. And different thresholds are set for different actions, and the judging conditions of the actions can be adjusted according to specific requirements and application scenes so as to adapt to different users.
In addition, referring to fig. 3, an embodiment of the present invention further proposes a somatosensory skiing game device implemented based on function fitting, the somatosensory skiing game device implemented based on function fitting comprising:
an acquisition module 110, configured to acquire somatosensory data from the bound somatosensory device after the somatosensory skiing game is started;
a fitting module 120, configured to fit the somatosensory data to obtain a skiing action function representing a current sliding action of the user;
an identification module 130, configured to identify a skiing action performed by the user according to the sliding action function;
and the execution module 140 is used for controlling the game character to execute skiing operation according to the skiing action completed by the user.
The steps implemented by the functional modules of the somatosensory ski game device based on function fitting may refer to various embodiments of the somatosensory ski game method based on function fitting according to the present invention, and are not 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 somatosensory ski game program 10 implemented based on function fitting, and the specific embodiment of the computer readable storage medium of the present invention is substantially the same as the specific embodiment of the somatosensory ski game method and the specific embodiment of the server 1 implemented based on function fitting, 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 somatosensory skiing game method based on function fitting, comprising:
after the somatosensory skiing game is started, somatosensory data are acquired from the bound somatosensory equipment;
fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user;
identifying skiing actions completed by a user according to the sliding action function;
and controlling the game character to execute skiing operation according to the skiing action completed by the user.
2. A method of motion sensing skiing game based on a function fit implementation as claimed in claim 1, wherein the motion sensing data comprises acceleration data and angular velocity data;
fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user, comprising:
comparing the acceleration data with a first preset threshold;
if the acceleration data is smaller than a first preset threshold value, fitting a skiing overturning action function according to the gyroscope data;
And if the acceleration data is larger than a first preset threshold value, fitting a skiing jump action function according to the acceleration data.
3. A method of motion sensing skiing game based on a function fit implementation as claimed in claim 2, wherein fitting a skiing rollover action function from the gyroscope data comprises:
generating track data of the motion of the somatosensory device in space according to the gyroscope data;
substituting the track data into a preset polynomial function for fitting to obtain the skiing overturning action function.
4. A somatosensory ski game method based on a function fit implementation according to claim 3, wherein generating trajectory data of motion of a somatosensory device in space from the gyroscope data comprises:
generating a grid map composed of a plurality of grid cells and a virtual rigid body matched with the somatosensory equipment on a game terminal for executing the somatosensory game;
updating the position of the virtual rigid body in the grid map according to the gyroscope data;
and recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the virtual rigid body in the grid map as the track data.
5. A method of motion sensing skiing game based on a function fit implementation as claimed in claim 2, wherein fitting a skiing jump motion function from the acceleration data comprises:
generating speed change data of the speed of the somatosensory equipment along with time according to the acceleration data;
and importing the speed change data into a preset linear function fitting to obtain the skiing jump action function.
6. The method of motion sensing skiing game implemented based on function fitting of claim 5, wherein generating speed change data of speed of the motion sensing device over time from the acceleration 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;
updating the position of the virtual rigid body in the grid coordinate system according to the acceleration;
and recording coordinate data of grid cells passed by the virtual rigid body in the moving process of the grid coordinate system as the speed change data.
7. A method of motion sensing skiing game based on a function fit implementation as claimed in claim 2, wherein identifying skiing performed by a user from the sliding motion function comprises:
Calculating a first similarity between the skiing overturn motion function and a preset skiing overturn motion function;
calculating the second similarity of the skiing jump action function and the preset skiing jump action function;
if the first similarity is larger than a second preset threshold value, judging that the user finishes the skiing overturning action;
and if the second similarity is larger than a third preset threshold value, judging that the user adds the skiing jumping action.
8. A somatosensory ski game device implemented based on function fitting, comprising:
the acquisition module is used for acquiring somatosensory data from the bound somatosensory equipment after the somatosensory skiing game is started;
the fitting module is used for fitting the somatosensory data to obtain a skiing action function representing the current sliding action of the user;
the identification module is used for identifying the skiing actions completed by the user according to the sliding action function;
and the execution module is used for controlling the game character to execute skiing operation according to the skiing action completed by the user.
9. A somatosensory ski game device implemented based on function fitting, comprising a memory, a processor and a somatosensory ski game program implemented based on function fitting stored on the memory and executable on the processor, the processor implementing a somatosensory ski game method implemented based on function fitting as claimed in any one of claims 1 to 7 when executing the somatosensory ski game program implemented based on function fitting.
10. A computer readable storage medium, wherein a somatosensory ski game program based on function fitting is stored on the computer readable storage medium, and when the somatosensory ski game program based on function fitting is executed by a processor, the somatosensory ski game method based on function fitting according to any one of claims 1-7 is realized.
CN202310658248.6A 2023-06-05 2023-06-05 Somatosensory skiing game method based on function fitting Pending CN116650952A (en)

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