KR101678136B1 - Method for training using movement trajectory analysis and apparatus therefor - Google Patents

Abstract

A training method and apparatus using motion trajectory analysis are disclosed. A training method according to the present invention includes the steps of acquiring image information for a first moving object from at least one image sensing means, acquiring a first motion locus and a first motion velocity of a first moving object in image information, Extracting a plurality of feature points representing motion of the first moving object in the motion locus, and determining mathematical modeling information on the first motion locus based on the feature points. According to the present invention, it is possible to provide a realistic training environment through the pitching of the same trajectory as the pitch of the actual pitcher to the user.

Description

TECHNICAL FIELD [0001] The present invention relates to a training method and apparatus using motion trajectory analysis,

The present invention relates to a training method, and more particularly, to a method and apparatus for analyzing and tracing a motion trajectory of a moving object.

A pitching machine is a pitching machine that puts a baseball in a spinning wheel at a high speed, and the baseball ball gets kinetic energy from the spinning wheels and makes it fly faster. Such an automatic pitching device is used for batting and catching training of baseball players. In addition, it is housed in a facility such as a screen baseball field, and is used for enjoying leisure activities by the general public.

In addition, facilities providing a realistic training environment using an automatic pitching device and related research are becoming active. In recent years, a method has been used in which a position sensor is mounted on a wearable display device for outputting different images to both eyes of a user, and a realistic three-dimensional image outputted according to the direction of rotation of the user's eyes is output.

The automatic pitcher was able to throw only a fastball at an early stage, but according to the development of technology, it is possible to throw a pitch such as a curve or a slider that a real pitcher can throw. It is not unreasonable to enjoy baseball players' general batting practice or the leisure activities of the general public.

However, a method or device for analyzing the trajectory of the ball actually thrown by the pitcher and then pitching it as it is has not been developed yet. Therefore, there is a problem that the training method using the currently used automatic pitching device can not provide a training environment specialized in pitching of actual pitcher.

In order to overcome the above-described problems, an object of the present invention is to provide a method of analyzing a trajectory of a ball to be pitched by an actual pitcher.

Another object of the present invention is to provide an apparatus for analyzing and tracing a trajectory of a ball to be pitched by an actual pitcher.

According to another aspect of the present invention, there is provided a training method using motion trajectory analysis, the training method comprising: Obtaining a first motion locus and a first motion velocity of the first moving object from the acquired image information, extracting a plurality of minutiae points representing the motion of the first moving object in the first motion locus And determining mathematical modeling information for the first motion locus based on the feature points.

The step of determining the mathematical modeling information may include acquiring positional information of each feature point included in the plurality of feature points, expressing the first motion locus based on the acquired positional information of the feature points, And calculating the mathematical expression as the mathematical modeling information for the first motion locus.

Here, the plurality of feature points may include a first point at which movement of the first moving object is started, at least one second point along a predetermined time interval from the first point, and a third point at which the movement of the first moving object ends Point.

The training method using the motion trajectory analysis may further include a step of determining the mathematical modeling information and then controlling the pitching of the second moving object to correspond to the first motion trajectory based on the mathematical modeling information .

Here, the step of controlling the pitching of the second moving object may include the step of, based on the mathematical modeling information, generating a second motion locus that is the same as the first motion locus and a second motion locus that is the same as the first motion velocity, Can be controlled.

The training method using the motion trajectory analysis may further include the step of controlling the output of the motion image of the second moving object so as to correspond to the first motion trajectory based on the mathematical modeling information after determining the mathematical modeling information can do.

Here, the step of controlling the output of the motion image of the second moving object may include a step of generating a second motion locus that is the same as the first motion locus based on the mathematical modeling information, and a second motion locus The output of the motion image of the second moving object can be controlled.

According to another aspect of the present invention, there is provided a training apparatus using motion trajectory analysis according to an embodiment of the present invention. The training apparatus includes a processor and a memory in which at least one program instruction executed through the processor is stored, One command program may include acquiring image information for the first moving object from at least one image capturing means, acquiring the first motion locus and the first motion velocity of the first moving object in the acquired image information, Extracting a plurality of feature points representing the motion of the first moving object in the first motion locus, and determining mathematical modeling information for the first motion locus based on the minutiae points.

The step of determining the mathematical modeling information may include acquiring positional information of each feature point included in the plurality of feature points, expressing the first motion locus based on the acquired positional information of the feature points, And calculating the mathematical expression as the mathematical modeling information for the first motion locus.

Here, the plurality of feature points may include a first point at which movement of the first moving object is started, at least one second point along a predetermined time interval from the first point, and a third point at which the movement of the first moving object ends Point.

The at least one program command may further include determining the mathematical modeling information and then controlling the pitching of the second moving object to correspond to the first motion locus based on the mathematical modeling information.

Here, the step of controlling the pitching of the second moving object may include the step of, based on the mathematical modeling information, generating a second motion locus that is the same as the first motion locus and a second locus of motion of the second moving object The pitching can be controlled.

Here, the at least one program command may further include, after determining the mathematical modeling information, controlling the output of the motion image of the second moving object to correspond to the first motion locus based on the mathematical modeling information have.

Here, the step of controlling the output of the motion image of the second moving object may include a step of generating a second motion locus that is the same as the first motion locus based on the mathematical modeling information, and a second motion locus The output of the motion image of the second moving object can be controlled.

According to the training method using the motion trajectory analysis as described above, the user can perform the batting training in a realistic training environment through the pitching of the same trajectory as the pitch of the actual pitcher.

1 is a conceptual diagram illustrating a training system using motion locus analysis according to an embodiment of the present invention.
2 is a flowchart illustrating a training method using motion locus analysis according to an embodiment of the present invention.
3 is a flowchart illustrating a training method using motion trajectory analysis according to another embodiment of the present invention.
FIG. 4 shows an embodiment of an image output from the training method using the motion locus analysis shown in FIG.
5 is a block diagram illustrating one embodiment of a training device for performing the methods according to the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail.

It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are to be interpreted in an ideal or overly formal sense unless explicitly defined in the present application Do not.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Hereinafter, the same reference numerals will be used for the same constituent elements in the drawings, and redundant explanations for the same constituent elements will be omitted.

FIG. 1 is a conceptual diagram showing a training system using a motion locus analysis according to an embodiment of the present invention. FIG. 2 is a flowchart showing a training method using a motion locus analysis according to an embodiment of the present invention. FIG. 4 shows an example of an image output from the training method using the motion trajectory analysis shown in FIG. 3. FIG. 4 is a flowchart illustrating a training method using motion trajectory analysis according to another embodiment of the present invention.

1 and 2, a training system using motion locus analysis according to the present invention includes a photographing unit 100, a training device 200 and a pitching machine 300 or a video output device 400 .

The training method (hereinafter referred to as 'training method') using the motion trajectory analysis according to the present invention can be performed in the training device 200. In addition, a program for performing the training method may be installed in the photographing means 100, the pitching device 300, or the video output device 400 and executed.

The training apparatus 200 may acquire image information about a moving object from at least one photographing means 100 (S200). Here, the photographing means 100 may mean a camera or a camera system designed for high-speed photographing. For example, the photographing means 100 may refer to a high speed camera.

The photographing means 100 can take a first moving object 20 (which may mean a ball) that is pitched by a pitcher 10. Specifically, the photographing means 100 can photograph the movement of the first moving object 20 which is pitched by the pitcher 10 and moves. The photographing means 100 may be connected to the training device 200 wirelessly or by wire and may transmit the image information of the first moving object 20 obtained through photographing to the training device 200. [ In this way, the training apparatus 200 can acquire image information of the first moving object 20 from the photographing means 100.

Thereafter, the training apparatus 200 may obtain the first motion locus and the first motion velocity of the first moving object 20 from the image information (S210). Here, the training apparatus 200 may mean a terminal or a computer system such as a computer that can use part of a program capable of analyzing image information of the first moving object 20 or data necessary for executing the entire program have.

In addition, the first motion locus of the first moving object 20 may mean a path from the point where the movement of the first moving object 20 starts to the point where the movement ends. The first moving speed of the first moving object 20 may be the speed from the start of movement of the first moving object 20 to the end of the movement.

Thereafter, the training apparatus 200 may extract a plurality of feature points indicating movement of the first moving object 20 in the first motion locus (S220). Here, the plurality of feature points may include a first point at which the movement of the first moving object 20 starts, at least one second point along the predetermined time interval from the first point, And a third point.

Thereafter, the training apparatus 200 may acquire positional information on each of the minutiae included in the extracted minutiae (S230). The training apparatus 200 can assume that the motion section of the first moving object 20 is a three-dimensional space composed of x-axis, y-axis, and z-axis, (x, y, z) of the z axis.

Thereafter, the training apparatus 200 may calculate a mathematical expression representing the first motion locus based on the respective position information (S240). The training apparatus 200 can calculate a formula representing a curve generated by connecting the respective feature points. That is, the calculated equation may mean a mathematical expression representing a curve of a three-dimensional space.

Thereafter, the training apparatus 200 may determine the calculated equation as mathematical modeling information on the first motion locus (S250). That is, the mathematical modeling information may be information on the first motion locus. For example, it may mean a movement path from a first point where the movement of the first moving object 20 starts to a third point where the movement ends.

Thereafter, if the training device 200 is interlocked with the pitching device 300, the training device 200 may determine that the second moving object 30 (i.e., Can be controlled (S260).

Specifically, the training device 200 may transmit mathematical modeling information for the first motion locus determined by the pitcher 300. Thereafter, the pitcher 300 may pitch the second moving object 30 so as to correspond to the first motion locus based on the mathematical modeling information. That is, the pitcher 300 can pitch the second moving object 30 at the second motion velocity equal to the first motion velocity and the second motion locus equal to the first motion locus based on the mathematical modeling information.

3, when the training apparatus 200 is interlocked with the video output apparatus 400, the training apparatus 200 generates a first motion locus corresponding to the first motion locus based on the mathematical modeling information, The output of the motion image can be controlled (S270). Here, the video output device 400 may refer to a display device capable of outputting a video image while the user wears his / her body. For example, the video output device may refer to a personal display device having a form of a spectacle that allows a user to watch an image while wearing his or her body.

Specifically, the training apparatus 200 may transmit mathematical modeling information on the first motion locus determined by the image output apparatus 400. [ Thereafter, the video output apparatus 400 may output the motion image of the second moving object 30 so as to correspond to the first motion locus based on the mathematical modeling information. That is, the image output apparatus 400 outputs a motion image of the second moving object 30, which moves at a second motion velocity equal to the second motion locus and the first motion velocity, which is the same as the first motion locus, based on the mathematical modeling information Can be output.

Referring to FIG. 4, the video output apparatus 400 may output a video that the pitcher throws to the user, for example. At this time, the pitching ball may be pitched at a second motion velocity equal to the first motion locus and at a second motion velocity equal to the first motion velocity.

In addition, the video output apparatus 400 includes a sensor capable of tracking a position or a sensor capable of motion detection, and can output an image in consideration of a motion of a user wearing the video output apparatus 400. For example, when the user turns his or her body to the left side, the user can view the image in the left direction based on the user's viewpoint. When the user turns his / her body to the right side, It is possible to output a possible image.

In addition, the user may use hitting means 410 (i. E., May mean a baseball bat) with a sensor capable of position tracking or a sensor capable of motion sensing. At this time, the video output apparatus 400 can detect the motion of the hitting means 410 through the sensor provided in the hitting means 410, and output an image of the detected motion.

5 is a block diagram illustrating one embodiment of a training device for performing the methods according to the present invention.

Referring to FIG. 5, the training apparatus 200 may include at least one processor 210, a memory 220, and a network interface device 230 for communicating with a network. The training device 200 may further include an input interface device 240, an output interface device 250, a storage device 260, and the like. Each of the components included in the training device 200 may be connected by a bus 270 and communicate with each other.

The processor 210 may execute program commands stored in the memory 220 and / or the storage device 260. The processor 210 may refer to a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor on which the methods according to the present invention are performed. The memory 220 and the storage device 260 may be composed of a volatile storage medium and / or a non-volatile storage medium. For example, memory 220 may be comprised of read only memory (ROM) and / or random access memory (RAM).

At least one program instruction executed via the processor 210 includes obtaining image information for a first moving object from at least one imaging means, generating a first motion locus of the first moving object and a second motion locus of the first moving object, 1 motion velocity, extracting a plurality of feature points representing the motion of the first moving object in the first motion locus, and determining mathematical modeling information on the first motion locus based on the feature points Or the like.

The step of determining mathematical modeling information among the program instructions executed through the processor 210 may include obtaining positional information on each of the minutiae included in the plurality of minutiae, Calculating a mathematical expression representing the first motion locus and determining the calculated mathematical expression as the mathematical modeling information on the first motion locus.

Here, the plurality of feature points include a first point at which the movement of the first moving object starts, at least one second point along the predetermined time interval from the first point, and a third point at which the movement of the first moving object ends .

Here, when the training apparatus 200 is interlocked with the pitching apparatus, at least one program executed through the processor 210 determines mathematical modeling information, and then, based on the mathematical modeling information, corresponds to the first motion locus And controlling the pitching of the second moving object.

That is, the processor 210 may control the pitching of the second moving object at a second motion locus that is the same as the first locus of motion and a second motion velocity that is the same as the first motion locus, based on the mathematical modeling information.

On the other hand, when the training apparatus 200 is linked with the video output apparatus, at least one program executed through the processor 210 determines mathematical modeling information, and then, based on the mathematical modeling information, corresponds to the first motion locus And controlling the output of the motion image of the second moving object.

That is, the processor 210 generates a second motion locus equal to the first motion locus based on the mathematical modeling information, and outputs the motion image of the second motion object moving at a second motion velocity equal to the first motion velocity Can be controlled.

It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined in the appended claims. It will be possible.

10: pitcher
20: first moving object
30: second moving object
100:
200: Training device
300: pitching device
400: Video output device
410: Hitting means

Claims (14)

In a training method performed in a training device,
Acquiring image information about a first moving object from at least one photographing means;
Obtaining a first motion locus and a first motion velocity of the first moving object from the acquired image information;
Extracting a plurality of feature points representing movement of the first moving object in the first motion locus;
Determining mathematical modeling information for the first motion locus based on the minutiae points; And
And controlling the pitching of the second moving object to correspond to the first motion locus based on the mathematical modeling information,
Wherein the training device outputs a motion image of the second moving object in association with the first motion locus based on the mathematical modeling information in cooperation with a video output device capable of outputting an image while being worn on the user's body, A control unit for controlling the output of the motion image in consideration of a motion of a user wearing the image output apparatus through a position tracking sensor or a motion detection sensor provided in the image output apparatus, A sensor for sensing the motion of the hitting means to control the output of the motion image,
Wherein the plurality of feature points include:
At least one second point at a predetermined time interval starting from the first point and a third point at which the movement of the first moving object is terminated, A training method using motion trajectory analysis. The method according to claim 1,
Wherein the step of determining mathematical modeling information comprises:
Obtaining positional information on each feature point included in the plurality of feature points;
Calculating a mathematical expression representing the first motion locus based on the obtained position information of each of the minutiae points; And
And determining the calculated equation as the mathematical modeling information for the first motion locus. delete delete The method according to claim 1,
Wherein the step of controlling the pitching of the second moving object comprises:
And controlling the pitching of the second moving object with a second motion locus equal to the first locus of motion and a second motion velocity equal to the first motion velocity based on the mathematical modeling information. Training methods. The method according to claim 1,
In the training method using the motion trajectory analysis,
Further comprising the step of controlling the output of the motion image of the second moving object so as to correspond to the first motion locus based on the mathematical modeling information after determining the mathematical modeling information, Way. The method of claim 6,
Wherein the step of controlling the output of the motion image of the second moving object comprises:
And controls the output of the motion image of the second moving object moving at a second motion locus equal to the first motion locus and a second motion velocity equal to the first motion velocity based on the mathematical modeling information Training method using motion trajectory analysis. As a training device,
A processor; And
And a memory in which at least one program command executed via the processor is stored,
Wherein the at least one program command comprises:
Acquiring image information about a first moving object from at least one photographing means;
Obtaining a first motion locus and a first motion velocity of the first moving object from the acquired image information;
Extracting a plurality of feature points representing movement of the first moving object in the first motion locus;
Determining mathematical modeling information for the first motion locus based on the minutiae points; And
And controlling the pitching of the second moving object to correspond to the first motion locus based on the mathematical modeling information,
Wherein the training device outputs a motion image of the second moving object in association with the first motion locus based on the mathematical modeling information in cooperation with a video output device capable of outputting an image while being worn on the user's body, A control unit for controlling the output of the motion image in consideration of a motion of a user wearing the image output apparatus through a position tracking sensor or a motion detection sensor provided in the image output apparatus, A sensor for sensing the motion of the hitting means to control the output of the motion image,
Wherein the plurality of feature points include:
At least one second point at a predetermined time interval starting from the first point and a third point at which the movement of the first moving object is terminated, A training device using motion trajectory analysis. The method of claim 8,
Wherein the step of determining mathematical modeling information comprises:
Obtaining positional information on each feature point included in the plurality of feature points;
Calculating a mathematical expression representing the first motion locus based on the obtained position information of each of the minutiae points; And
And determining the calculated equation as the mathematical modeling information for the first motion locus. delete delete The method of claim 8,
Wherein the step of controlling the pitching of the second moving object comprises:
And a second motion locus that is the same as the first motion locus based on the mathematical modeling information and controls the pitching of the second motion object at a second motion velocity that is the same as the first motion locus. Device. The method of claim 8,
Wherein the at least one program command comprises:
And controlling the output of the motion image of the second moving object to correspond to the first motion locus based on the mathematical modeling information after determining the mathematical modeling information. Device. 14. The method of claim 13,
Wherein the step of controlling the output of the motion image of the second moving object comprises:
And controls the output of the motion image of the second moving object moving at a second motion locus equal to the first motion locus and a second motion velocity equal to the first motion velocity based on the mathematical modeling information Training device using motion trajectory analysis.

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