KR102500621B1 - Apparatus and Method for Processing of Exercise Information - Google Patents

Abstract

The present invention relates to an exercise information processing apparatus and method.
An exercise information processing apparatus according to the present invention includes a camera unit for capturing an exercise image of a user selected as a target among a plurality of users in a preset exercise area, and a camera unit for the user's exercise selected based on the exercise image. It may include a control unit for obtaining information.

Description

Exercise information processing device and method {Apparatus and Method for Processing of Exercise Information}

The present invention relates to an exercise information processing apparatus and method.

BACKGROUND ART With the improvement of living standards, people's interest in health is rapidly increasing. As part of this, modern people are gradually increasing the number of people who exercise for disease prevention and personal hobbies.

In recent years, Personal Training (PT), which is a 1: 1 exercise with a trainer, is in the spotlight.

However, in the case of PT, the cost is expensive.

If the user exercises alone, there is a problem in that it is difficult to determine the accuracy of the user's motion or the appropriateness of the exercise performed by the user.

An object of the present invention is to provide an exercise information processing apparatus and method for providing exercise information by photographing a user's exercise image and analyzing the photographed exercise image.

An exercise information processing apparatus according to the present invention includes a camera unit for capturing an exercise image of a user selected as a target among a plurality of users in a preset exercise area, and a camera unit for the user's exercise selected based on the exercise image. It may include a control unit for obtaining information.

Also, the control unit may include a path determination unit that determines information about a path within the exercise area of the user selected based on the exercise image.

In addition, the control unit may include a mechanism discrimination unit that determines information on the exercise equipment used by the user based on the exercise image.

Also, the control unit may include a preference determination unit that determines information about the user's preference for the exercise machine based on the exercise image.

In addition, the camera unit includes a first camera and a second camera, and when the first camera loses the user from the field of view while photographing the user, the controller controls the second camera. The user may be tracked in an image captured by a camera.

Also, the control unit may include a type determining unit that determines the type of the user's exercise based on the exercise image.

In addition, the control unit may include a motion determining unit for discriminating an exercise motion of the user based on the exercise image.

In addition, the control unit may include a number determination unit for determining the number of times of exercise of the user based on the exercise image.

In addition, the control unit may include a time determination unit for measuring the user's exercise time based on the exercise image.

In addition, the control unit may determine that the user's exercise ends when the user leaves the exercise area for more than a predetermined reference time.

An exercise information processing method according to the present invention includes a photographing step of photographing an exercise image of a user selected as a target among a plurality of users in a preset exercise area by a camera unit, and an exercise of the user selected based on the exercise image It may include an information acquisition step of acquiring information about.

Also, the information acquisition step may include determining information about a path of the user within the exercise area based on the exercise image.

In addition, the information acquisition step may further include determining information about an exercise device used by the user based on the exercise image.

The information acquisition step may include determining information about the user's preference for the exercise equipment based on the exercise image.

In addition, the camera unit includes a first camera and a second camera, and when the first camera misses the user in the process of photographing the user, the second camera captures the user. The user can be tracked in one video.

Also, the information acquisition step may include determining the type of exercise of the user based on the exercise image.

Also, the information acquisition step may include determining an exercise motion of the user based on the exercise image.

Also, the information acquisition step may include determining the number of times of exercise of the user based on the exercise image.

Also, the information acquisition step may further include measuring an exercise time of the user based on the exercise image.

The information acquisition step may further include determining that the user's exercise ends when the user leaves the exercise area for more than a predetermined reference time.

The exercise information processing apparatus and method according to the present invention can provide information about the user's exercise motion, exercise frequency, etc. by analyzing the user's exercise image, thereby providing objective and accurate exercise information to the user at a lower cost. It works.

1 is a diagram for explaining the configuration of an exercise information processing device according to the present invention;
2 to 33 are diagrams for explaining an exercise information processing method according to the present invention;
34 to 37 are views for explaining another exercise information processing method according to the present invention,
38 to 47 are diagrams for explaining a method of processing exercise information in consideration of a motion path.

Hereinafter, an exercise information processing apparatus and method according to the present invention will be described in detail with reference to the accompanying drawings.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. This is not intended to limit the present invention to specific embodiments, and it can be understood to include all changes, equivalents, and substitutes included in the spirit and technical scope of the present invention.

In describing the present invention, terms such as first and second may be used to describe various components, but the components may not be limited by the terms. The terms may only be used for the purpose of distinguishing one component from another. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present invention.

The terms and/or may include any combination of a plurality of related recited items or any of a plurality of related recited items.

When a component is referred to as being "connected" or "connected" to another component, it may be directly connected or connected to the other component, but other components may exist in the middle. can be understood On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it may be understood that no other element exists in the middle.

Terms used in this application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions may include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "having" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, and one or more other features It may be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

Unless defined otherwise, all terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person of ordinary skill in the art to which the present invention belongs. Terms such as those defined in commonly used dictionaries may be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in the present application, interpreted in an ideal or excessively formal meaning. It may not be.

In addition, the following embodiments are provided to more completely explain to those with average knowledge in the art, and the shapes and sizes of elements in the drawings may be exaggerated for clearer explanation.

1 is a diagram for explaining the configuration of an exercise information processing device according to the present invention.

1, the exercise information processing device 10 according to the present invention includes a control unit 100, a camera unit 300, an output unit 400, a user input unit 500, a memory unit 600, and a communication unit 700. can include

The camera unit 300 may capture a predetermined image under the control of the controller 100 . For example, the camera unit 300 may capture an exercise image of the user. Alternatively, the camera unit 300 can capture an image of a predetermined exercise area (eg, a gym).

The camera unit 300 may include at least one camera.

The output unit 400 may output predetermined information under the control of the control unit 100 so that the user can check it. In detail, the output unit 400 may output information about exercise, for example, information about a reference motion, a reference number of times, and the like of an exercise so that the user can check it.

The output unit 400 may include a display unit 410 and an audio output unit 420 .

The display unit 410 may display various information as images. The audio output unit 420 may output various information as audio.

The user input unit 500 may be used for a user to input a predetermined command. The user input unit 500 may include at least one of a key input unit, a touch input unit, and a voice input unit.

The memory unit 600 may store various types of information under the control of the controller 100 . For example, the memory unit 600 may store information about a reference number of times, a reference operation, and a reference time.

The communication unit 700 may communicate with other devices. For example, the communication unit 700 may transmit exercise information or an edited exercise video to another device or a predetermined page (website) under the control of the control unit 100 .

The controller 100 may control overall operations of the exercise information processing device 10 .

The controller 100 may obtain various information about the user's exercise based on the exercise image captured by the camera unit 300 .

The controller 100 may determine the start and end of the user's exercise.

The control unit 100 includes a type determination unit 110, an action determination unit 120, a number determination unit 130, a time determination unit 140, an apparatus determination unit ( 150), tracking unit 160, path determination unit 170, preference determination unit 180, object recognition unit 190, motility determination unit 200, information provision unit 210 and editing unit 220 can do.

The type determination unit 110 may determine the type of exercise for the user's exercise based on the user's exercise image captured by the camera unit 300 .

The motion determining unit 120 may determine the user's motion motion based on the motion image.

The number determination unit 130 may determine the number of times the user exercises based on the exercise image.

The number determination unit 130 may count the number of exercises when the user's exercise motion matches a preset standard ratio or more.

The time determination unit 140 may determine the user's exercise time based on the exercise image.

The equipment determination unit 150 may determine the type of exercise equipment selected by the user.

In addition, when the exercise type is an exercise using a weight mechanism, the mechanism determining unit 150 may determine a load set in the weight mechanism.

The tracking unit 160 may track a selected user among a plurality of users as a target within a preset exercise area.

The path determination unit 170 may determine information about a path within the selected user's exercise area based on the exercise image.

The preference determining unit 180 may determine at least one user's preference for exercise equipment or at least one user's preference for a warming type.

The object recognizing unit 190 may recognize a moving object by analyzing the motion image.

The motility calculation unit 200 may classify the motion of the moving object recognized by the object recognition unit 190 by varying the brightness over time, and calculate the motility based on the direction and degree of change in brightness.

The information providing unit 210 may provide recommendation information to the user based on at least one of information on the type of exercise, information on the number of exercises, or information on the exercise time.

In addition, the information providing unit 210 may provide various information obtained by analyzing the exercise images to the user, other devices, and/or a predetermined website.

The image editing unit 220 may extract/edit a highlight image from the user's exercise image.

The exercise information processing device 10 configured in FIG. 1 may be realized with various types of hardware. For example, the exercise information processing device 10 according to the present invention may be manufactured in the form of a mobile communication terminal such as a smart phone, or may be manufactured in the form of a fixed terminal such as a CCTV.

An exercise information processing method using the exercise information processing apparatus having this configuration will be described in detail below with reference to the accompanying drawings.

2 to 37 are diagrams for explaining an exercise information processing method according to the present invention. Hereinafter, description of the contents described above may be omitted.

Referring to FIG. 2 , in the exercise information processing method according to the present invention, first, the exercise foundation processing device 10 may be set (S100).

In the setting step, it is possible to place the camera unit 300 at a location where motion images can be captured.

Alternatively, the exercise information processing device 10 may be set to an exercise image capturing mode.

If necessary, the user can be authenticated by inputting information such as the user's ID or password (PW).

When a photographing command is input, the camera unit 300 may capture an exercise image of the user under the control of the controller 100 (S400). For example, as in the case of FIG. 3 , it is possible for the exercise information processing device 10 in the form of a mobile communication terminal to capture an image of the user H exercising.

Thereafter, the controller 100 may analyze the motion image captured by the camera unit 300 (S300).

In addition, the controller 100 may determine various exercise information as a result of analyzing the exercise image (S400).

Thereafter, the controller 100 may provide various information based on the determined information (S500).

In the information providing step, the communication unit 700 may transmit the information determined by the controller 100 to another device or a pre-designated homepage under the control of the controller 100 .

A method for analyzing motion images is described below.

Referring to FIG. 4 , in the step of analyzing the motion image (S300), a background may be first extracted from the motion image (S310). In detail, a plurality of image frames are compared to determine a part without motion or very little as a background, and the background can be extracted according to the result of the determination.

For example, as in the case of FIG. 5 , when a first frame (A) and a second frame (B) after the first frame (A) are compared, the second frame (B) has a predetermined It can be seen that the object (OB) is included, and the object (OB) is not included in the first frame (A).

In this case, the newly added object OB in the temporally late second frame B may be recognized as the moving object OB.

In the first frame (A) and the second frame (B), there is almost no change in the images of the remaining parts except for the object (OB). In other words, the image of the remaining part except for the object OB hardly moves. Accordingly, all parts other than the object OB may be recognized as a background.

Alternatively, when the moving object OB is not captured in the motion image, an image such as the first frame A may continue. In this case, the first frame (A) image may be recognized as a background image. In other words, all parts appearing in the first frame A can be recognized as a background.

As such, it is possible to recognize and extract a non-moving part of an image as a background during a preset reference frame period.

When a background image similar to the first frame A continues and the object OB is captured by the camera unit 300, an image similar to the second frame B may be obtained. If the object OB continues to move and leaves the screen, an image similar to that of the first frame A will be obtained again.

If an image before the object OB passes and an image after the object OB passes is compared, the two images may be almost the same.

As such, even if motion is detected in the image as the object OB moves in the image for a certain period of time, if the image before the object OB is captured and the image after the object OB has passed are almost the same, it corresponds to the corresponding image. Most of what you do may be the background.

In other words, even if there is a part that changes according to movement in the image for a certain period of time, if the image before the change starts and after the change ends are almost the same, the corresponding image can be recognized as a background image.

After extracting the background, the color of the background can be determined and information about it can be stored.

Thereafter, the color of the background (image that becomes the background) and other motion images may be compared (S320).

The object recognizing unit 190 may recognize a part having a different color from the background in the motion image as a moving object OB (S330).

For example, as shown in (A) of FIG. 6 , a part having a different color from the background, that is, the object OB may be detected.

In addition, after distinguishing the background and the object OB, the background may be treated as a single color. For example, the background can be treated as black. In this case, the motion of the object OB can be more easily analyzed.

Thereafter, as shown in (B) of FIG. 6 , the silhouette of the object OB may be determined. In (B) of FIG. 6, the red part (ER) in the upper left corner is too different from the shape of a person, so it can be treated as an error.

Through this process, it is possible to recognize a moving object (OB) in a motion image.

Then, the motion calculation unit 200 may analyze the motion of the object OB (S340).

In addition, mobility may be calculated according to the result of the motion analysis (S360).

In detail, the motion calculation unit 200 may distinguish the motion of the moving object OB by varying brightness according to time. In addition, the motion calculation unit 200 may calculate mobility based on the direction and degree of change in brightness.

For example, as in the case of FIG. 7 , assume a case where the object OB, that is, the user lifts the left arm.

As shown in FIG. 7 , the current appearance of the user may be relatively bright and the previous appearance may be relatively dark.

In this case, it can be determined that the user's left arm moved from the bottom to the top from the dark area to the light area. That is, the direction of movement can be determined.

In addition, the movement speed of the left arm may be determined according to whether the change in brightness of the left arm is rapid or gradual.

For example, as shown in (A) of FIG. 8, when the object OB rotates 180° (degrees) around an axis and as shown in (B) of FIG. 8, the object (OB) rotates 90° (degrees) around an axis. ) Let's assume the case of rotation.

When the change in brightness of (A) and (B) of FIG. 8 is the same, it can be seen that the case of (A) of FIG. 8 has greater mobility than the case of (B), that is, the movement speed is faster. .

Alternatively, as shown in (A) and (B) of FIG. 9 , assume a case in which the object OB rotates 180° (degrees) around an axis, respectively.

When the change in brightness occurs more rapidly in (B) than in (A) of FIG. 9, in the case of (A) of FIG. 9, the object OB rotates 180° (degree) for a relatively short time. rotation, and in the case of (B) of FIG. 9 , it may correspond to a case where the object OB rotates 180° (degrees) for a relatively long time.

Accordingly, the case of (A) of FIG. 9 may have greater mobility than the case of (B).

In this way, it is possible to recognize a moving object OB and calculate the movement of the recognized object OB.

Meanwhile, it is possible to use a predetermined mask to detect motion. For example, a mask having a predetermined size may be applied to a specific region of an image, and a change in luminance of the corresponding mask may be detected to determine mobility.

A method for determining exercise information is as follows.

Information about the type of exercise, exercise operation, number of exercises, and exercise time described below may be determined based on the information about the mobility calculated by the mobility calculation unit 200 .

Referring to FIG. 10 , in the information determination step (S400), at least one of an exercise type, exercise motion, exercise frequency, exercise time, exercise equipment, exercise route, or preference may be determined.

A method for determining an exercise motion and/or type is as follows.

Information on the reference motion may be set and stored for each type of exercise. For example, as in the case of FIG. 11, in the case of a push-up exercise, a reference angle (Xb) between the floor (GND) and the leg of the user (H), a reference distance (Xa) between the upper body and the floor (GND), etc. information can be set in advance.

Thereafter, when the user performs an exercise as shown in (A) and (B) of FIG. 12, when the camera unit 300 captures an exercise image of the user, the motion determination unit 120 analyzes the exercise image and determines the exercise motion. information can be identified.

The motion determination unit 120 may discriminate/obtain information about exercise motions, such as an angle between the floor and the leg, a distance between the upper body and the floor, and the like.

The type determining unit 110 may compare motion information acquired by the motion determining unit 120 with information on a preset reference motion.

For example, in the case of (A) of FIG. 12 , the angle between the floor (GND) and the leg of the user (H) is the first angle (Xb1), and the distance between the upper body and the floor (GND) is the first distance (Xa1). ), it is possible to determine how similar the first angle Xb1 is to the preset reference angle Xb, and how similar the first distance Xa1 is to the reference distance Xa.

If the first angle Xb1 is similar to the reference angle Xb within a predetermined range and the first distance Xa1 is similar to the reference distance Xa within a predetermined range, FIG. 12 ( The same type of exercise as A) can be identified as push-ups.

In this way, it is possible to determine the exercise type of FIG. 12 (B) as a push-up.

13, the angle between the floor (GND) and the leg (third angle (X2)) is similar to the preset reference angle (Xb) within a preset range. However, since the upper body of the user H is in contact with the floor GND, the type determination unit 110 may recognize that the exercise is not push-up.

Here, only the reference distance Xa and the reference angle Xb are described for reference information for convenience of explanation, but the present invention may not be limited thereto. For example, information about the position of the hip, the angle of the knee, the position of the head, the angle of both arms, and the position of both hands may be set as reference information.

The motion determination unit 120 may discriminate/acquire information on an exercise motion from an exercise image, and may also determine information on exercise accuracy.

The motion determination unit 120 may determine how similar the user's exercise motion is to a preset reference motion. In other words, the action determination unit 120 can determine how accurately and in good form (action) the user H is exercising.

For example, as in the case of FIG. 14, information about the angle of the arm, the degree of bending of the arm, the angle between the floor and the leg, the angle of the knee, the height of the hip, etc. in the user's exercise motion is compared with a preset reference exercise motion, and each accuracy score can be determined.

In addition, the motion determining unit 120 may calculate a comprehensive evaluation score for the accuracy of the user's motion compared to the reference motion motion. That is, it is possible to set a model answer for the exercise motion and evaluate the score for the user's exercise motion.

Items evaluated by the operation determination unit 120 may be variously changed.

For example, in the case of a running exercise, items such as a step angle, stride length, arm angle, upper and lower body movements, etc. may be evaluated, and accuracy may be determined according to the evaluation result.

In addition, the motion determination unit 120 may also evaluate the difficulty of the user's exercise.

For example, when the user performs an exercise in the form of (A), (B), (C), (D) or (E) of FIG. 15, the motion determination unit 120 (A) of FIG. ), (B), (C), (D), and (E) can all be identified as push-ups.

In addition, the operation determination unit 120 determines the degree of difficulty in the case of FIG. 15 (A) as a first level, and sets the degree of difficulty in the case of FIG. 15 (B) to a level higher than the first level. It is determined as a high second level, and the difficulty in the case of FIG. 15 (C) is determined as a third level higher than the second level, and the case of FIG. 15 (D) It is possible to determine the degree of difficulty as a fourth level higher than the third level, and to determine the degree of difficulty in the case of FIG. 15(E) as a fifth level higher than the fourth level.

In the above, the case of bare-handed exercise (push-up) has been described, but the above information can also be applied to exercise using equipment.

The criterion for determining the accuracy of the operation of the operation determination unit 120 may be set differently for each exercise with bare hands and for each exercise with equipment, and may also be set differently according to the type of equipment.

As shown in FIG. 16 , when the user H performs an exercise using a predetermined exercise device 800, the exercise information processing device 10 in the form of a mobile communication terminal may capture an exercise image.

In this case, the exercise information processing device 10 may analyze/determine information on the type of exercise and motion motion according to the above description.

The equipment determination unit 150 of the exercise information processing device 10 may determine the type of exercise equipment 800 used by the user H to exercise.

For example, it is possible to determine which type of exercise machine the user is using by storing shape information and image information for each exercise machine in the memory unit 600 and comparing it with the exercise machine shown in the exercise image. .

Alternatively, it may be possible to allocate identification information such as a barcode capable of identifying the equipment to each exercise equipment, and to determine the exercise equipment using this.

In addition, when the type of exercise determined by the type determining unit 110 is an exercise using a weight mechanism, the mechanism determination unit 150 may determine a load set in the weight mechanism.

For example, information on the weight, size, shape, etc. of weights used for each exercise device is stored in advance in the memory unit 600, and the total weight is compared with the weights used by the user shown in the exercise video using this information. load can be identified.

Alternatively, it is possible to install a strain gauge on an exercise device and check the load of the device using the strain gauge.

The time determining unit 140 may measure/determine the user's exercise time based on the exercise image.

For example, let's assume a case where the result shown in FIG. 17 is obtained as a result of analyzing the user's exercise image.

Referring to FIG. 17, in the process of starting the exercise at time T0 and ending the exercise at time Te, the user's mobility may exceed the average value Aa during the periods T1-T2, T3-T4, and T5-T6.

In this case, the time determination unit 140 determines that the user exercises during periods T1-T2, T3-T4, and T5-T6, and takes a break during periods T0-T1, T2-T3, T4-T5, and T6-Te. can be identified as

In this way, the time determination unit 140 may determine information on a break time as well as information on a user's exercise time.

The above-described exercise type, exercise operation, exercise time, information on exercise equipment, etc. may be processed and provided in a form that can be checked by the user.

For example, as in the case of FIG. 18, when the user performs a bench press exercise, the total exercise time, rest time, number of sets, number of exercises for each set, load (weight) for each set, and each set Information about exercise time and the like may be provided to the user.

Information on the exercise set can be determined in the same way as in FIG. 17 above.

The number determination unit 130 may determine the number of times the user exercises based on the exercise image.

For example, as shown in FIG. 19 , when the user H performs a push-up exercise, a motion of bending and straightening his arm in a prone state may be determined as one push-up exercise. If the user maintains an extended state without bending the arm, it may be determined that the user did not perform a push-up exercise no matter how long a time elapses.

It may be desirable for the number determination unit 130 to count the number of times when the user's exercise motion matches a preset reference ratio or more to a preset reference motion.

For example, as shown in (A) of FIG. 20, in the case of a push-up exercise, a reference angle (Xb) between the floor (GND) and the leg of the user (H), a reference distance (Xa) between the upper body and the floor (GND) ), etc., information can be set in advance.

Thereafter, when the user performs a push-up exercise as shown in (B) of FIG. 20, the angle between the floor (GND) and the user's (H) leg is the third angle (Xb3), and the upper body and the floor (GND) When the distance between them is the third distance Xa3, it is determined how similar the third angle Xb3 is to the preset reference angle Xb, and to what extent the third distance Xa3 is equal to the reference distance Xa. similarity can be determined.

As a result of the determination, the third angle (Xb3) matches the reference motion (reference angle (Xb)) and the reference ratio or more, and the third distance (Xa3) matches the reference motion (reference distance (Xa)), the reference motion, or more than the reference ratio. In the case of matching, it may be determined that the user H performed a push-up exercise once.

If the user exercises in the form of (B) of FIG. 21, even if the angle Xb4 between the floor GND and the leg matches the reference angle Xb and the reference ratio or more, the user H ), since the distance Xa4 between the upper body and the floor GND does not change, that is, the distance Xa4 between the user H's upper body and the floor GND does not match the standard motion and the standard ratio or more, It can be determined that the stretching exercise was not performed.

The method of determining the number of exercises can be applied not only to bare-handed exercises such as push-ups, but also to machine exercises using a machine.

For example, as shown in FIG. 22, let's assume a case in which the user H uses the pull-down exercise device 810.

In this case, it can be determined that the pull-down exercise has been performed once only when the handle of the pull-down exercise device 810 moves up and down together with the user H's arm while the user H raises and lowers his arm. there is.

The information providing unit 210 may provide information about exercise results to the user.

For example, as in the case of (A) of FIG. 23, the user's current state (the number of push-up exercises performed by the user), average number of push-ups, and information on the target value for push-up exercises performed by the user are provided together. It is possible.

Alternatively, as shown in (B) of FIG. 23, in the case of a pull-down exercise, it is possible to provide information on the current state (load (weight) of the pull-down exercise performed by the user), average load, and target value.

23 (C) discloses the case of bench press exercise.

It may be desirable for the information providing unit 210 to provide information on achievement to the user based on at least one of information on the type of exercise, information on the number of exercises, and information on exercise time. The higher the number of exercises and the shorter the exercise time, the higher the achievement level.

For example, referring to FIGS. 23(A) and 24(A) , in the case of a push-up exercise, the user's achievement may be 80% of the average number of times and 67% of the target value.

Achievement information may also be applied to pull-down exercise and bench press exercise.

In addition, the information providing unit 210 may provide recommended information to the user based on at least one of information on the type of exercise, information on the number of exercises, or information on the exercise time. Here, the recommendation information may include at least one of recommendation information on the number of times of exercise, recommendation information on exercise time, or recommendation information on the type of exercise.

For example, as shown in (B) of FIG. 24, in the case of push-up exercise, it is recommended to increase the number of executions by 20%, in the case of pull-down exercise, it is recommended to increase the load by 16%, and in the case of bench press exercise, it is recommended to increase the number of times by 30 A reduction of % can be recommended. In addition, instead of reducing the number of bench press exercises, it can be recommended to add butterfly exercises. This is because the achievement of the bench frame exercise exceeded 100% as shown in FIG. 24 (A).

Alternatively, as shown in (A) of FIG. 25 , in case of a push-up exercise, it is possible to provide the user with recommended information about an exercise operation, such as straightening the knees.

In addition, as shown in (B) of FIG. 25, an example of a desirable push-up motion may be displayed on the display unit 410 so that the user can more easily understand.

The provision of recommendation information may be applied to exercises such as yoga, in which the exercise itself is considered important, in addition to exercises related to the number of exercises, such as push-ups.

For example, as shown in (A) of 26, when the user H performs a yoga exercise, exercise motion information MD may be extracted from the user's exercise image.

In FIG. 26, for convenience of explanation, exercise motions are represented by movements of the skeleton as shown in (B) of FIG. 26, but the present invention may not be limited thereto. For example, even in the case of yoga exercise, mobility can be analyzed/determined by the object recognition unit 190 and the mobility calculation unit 200 described above.

When the user's exercise motion information (MD) is obtained, as shown in FIG. 26 (C), the user's exercise motion information (MD) may be compared with preset reference motion information (SD).

As a result of the comparison, the similarity between the motion information MD of the user and the reference motion information SD may be determined as an achievement level.

For example, as shown in (A) of FIG. 27, in the user's yoga exercise, the arm motion is 92% similar to the reference motion information (SD), the leg motion is 95% similar, and the trunk motion is 98% similar to the accuracy. information can be identified. In other words, the user's yoga motion can be regarded as having 92% accuracy in the arm motion category.

Based on this accuracy information, as shown in (B) of FIG. 27, recommendation information for a corresponding exercise may be provided to the user.

It may also be possible that the achievement level is determined according to the exercise time regardless of the load or the number of times.

For example, as shown in (A) of FIG. 28 , it is possible to determine/provide achievement levels for exercise time of various exercises such as bench press exercise, pull-down exercise, push-up exercise, and running.

In addition, as shown in (B) of FIG. 28, recommendation information may be provided to the user based on the achievement level of each exercise.

For example, if the user's push-up exercise time is shorter than the average (10 minutes), it is possible to provide the user with recommendation information telling the user to invest more time in the push-up exercise.

It may be desirable to apply the achievement according to exercise time to exercise such as yoga and running.

For example, as shown in (A) of FIG. 29 , it is assumed that the user H assumes a grasshopper posture, a dog posture, a plow posture, and an eagle posture during yoga exercise.

In this case, it is possible to determine/provide an achievement level (100%) by comparing the time (60 seconds) for which the user assumes the grasshopper posture and maintains the posture with a preset reference time (60 seconds).

In addition, based on the level of achievement, it is possible to provide recommendation information to the user, such as reducing the eagle posture time and increasing the practice time for the dog posture and the plow posture.

Meanwhile, it is possible to differently provide recommendation information according to the degree of difficulty.

For example, as in the case of FIG. 30, in the case of push-up exercise, level 1 is set for 100 times for 10 minutes, and level 2 is for 130 times for 10 minutes, 160 times for 10 minutes. Let's assume that level 3 sets the case of performing 190 times for 10 minutes as level 4, and level 5 sets the case of performing 220 times for 10 minutes.

As shown in (A) of FIG. 31, when user A at the level 2 stage performs a total of 90 push-ups for 10 minutes and the achievement is 69%, the level is set to level 1 as shown in (B) of FIG. Downgrading can be recommended.

Alternatively, the exercise information processing device 10 may forcibly lower the level of user A from level 2 to level 1.

On the other hand, as shown in (A) of FIG. 32, when user B at level 4 performs a total of 230 push-ups for 10 minutes and his achievement is 121, he moves to level 5 as shown in (B) of FIG. I can recommend upgrading the level.

Alternatively, the exercise information processing device 10 may forcibly raise the level of user B from level 4 to level 5.

The information providing unit 210 may compare various information collected from the user with information of other users to provide information on the health status of the user.

For example, as in the case of FIG. 33, information such as the user's current muscle strength, muscular endurance, cardiorespiratory endurance is predicted by comparing the information obtained by analyzing the user's exercise image and discriminated/obtained with big data, and It is possible to provide it to users.

In the above, the case where the exercise information processing device 10 determines the type of exercise performed by the user from the exercise image has been described. However, it is possible for the exercise information processing device 10 to provide information on the type of exercise first. . In this regard, referring to the accompanying drawings, it will be described as follows.

34 to 37 are diagrams for explaining another exercise information processing method according to the present invention. Hereinafter, descriptions of the parts described in detail above will be omitted. For example, the following contents may be substantially the same as those described above unless otherwise specified, except that information on the type of exercise and information on the reference motion of the corresponding exercise are provided to the user in advance before shooting. .

Referring to FIG. 34 , a step of providing information on the type of exercise (S600) may be included before the step of photographing (S200).

In this case, it is also possible that the type determination unit 110 in the control unit 100 is omitted.

For example, as in the case of FIGS. 35 to 36, the exercise information processing device 10 displays information on the type of exercise and information on the reference motion of the exercise to the user before capturing an exercise image on a screen (display unit 410). ) can be provided.

Then, the user can check what kind of exercise he or she should currently do.

Further, the exercise information processing device 10 monitors whether the user H is performing a corresponding exercise.

This method may be preferably applied to exercises in which various exercises are performed by sets, such as Crossfit.

For example, as in the case of FIG. 37 , in the first step, a yoga exercise maintaining the crossed legs posture may be performed.

In this case, as in the case of FIG. 35 , information on the reference motion information of the braided posture may be displayed on the display unit 410 .

In this case, the exercise information processing device 10 may determine an exercise action for the user's cross-legged posture exercise.

In addition, when the user completes a yoga exercise in which the user maintains a cross-legged posture, that is, when the corresponding exercise ends, the exercise information processing device 10 determines the type of exercise and the reference motion for another exercise, such as a push-up exercise. information can be provided.

Then, the exercise information processing device 10 may determine the user's number of exercises for the push-up exercise.

In other words, the exercise information processing device 10 provides information on the reference motion for the first exercise to the user, and discriminates / can be obtained

Thereafter, when the first exercise is finished, the exercise information processing device 10 further provides information on a reference motion of a second exercise that is different from the first exercise, and provides exercise motion and/or motion for the second exercise and/or Information on the number of exercises can be determined/obtained.

Here, a method of determining whether the exercise is finished is as follows.

A first condition is that the number of exercises for the user's first exercise reaches a preset reference number, and a case in which the exercise motion for the user's first exercise matches the reference motion with a preset reference ratio or more is determined. Let's assume 2 conditions.

Here, when at least one of the first condition or the second condition is satisfied, it may be determined that the first exercise ends.

In this way, it is possible to discriminate/acquire various exercise information during exercise such as CrossFit.

38 to 47 are diagrams for explaining a method of processing exercise information in consideration of a motion path. Hereinafter, description of the parts described in detail above may be omitted.

Referring to FIG. 38 , in the setting step (S100) to capture an exercise image, an exercise information processing device 10, that is, a camera unit 300 may be installed to capture a wider space.

For example, as in the case of FIG. 39 , the camera unit 300 may be installed to take pictures of the exercise area 900 of the health club.

Thereafter, a user selected as a target among a plurality of users in a preset exercise area 900 may be tracked (S900), and an exercise image of the user being tracked may be captured (S200).

For example, a user may install a personal mobile communication terminal in a health club used by a plurality of users, and take pictures of his/her own exercise while exercising while designating himself/herself as a user.

Alternatively, it is possible to capture an exercise image of a specific user using a public terminal and a public camera (CCTV camera, etc.) installed in the health club.

Thereafter, the photographed exercise image may be analyzed (S300), various data may be discriminated (S400), and various information may be acquired based on this (S1000).

An example of a method of selecting and tracking a desired user from among a plurality of users is as follows.

As in the case of FIG. 40 , a predetermined space in which the exercise equipment IG is disposed and can exercise may be set as the exercise area 900 .

An entrance may also be set in the exercise area 900 .

Among at least one user located within the set exercise area 900, a user to be photographed may be selected. For example, it is possible for an administrator to designate a user or a user to designate himself.

The exercise information processing device 10 may store information on the selected user. For example, the exercise information processing device 10 may store various information such as a user's face, clothes, height, body shape, and hairstyle, and track the user by using the stored information.

When the user enters the exercise area 900, the exercise information processing device 10 detects this and automatically tracks the user while capturing an exercise image.

Alternatively, it is possible for the user to wear a predetermined tracking device for tracking. For example, a user may exercise while wearing a tracking device manufactured in the form of a headband, bracelet, ring, or clothes.

In this case, the exercise information processing device 10 can capture an exercise image while tracking the user using a tracking device worn by the user.

It may also be possible to recognize information about a user using a tracking device. For example, when a user enters the exercise area 900 while wearing a tracking device, the exercise information processing device 10 recognizes the tracking device, so that when (date, time, etc.) It is possible to recognize and determine that the exercise has been performed by entering the exercise area 900 by (date, time, etc.).

The path determination unit 170 of the control unit 100 of the exercise information processing device 10 according to the present invention may determine information about the user's exercise path based on the exercise image.

For example, as in the case of FIG. 41 , the path determining unit 170 may determine and obtain information on which path PT the user moves in the exercise area 900 while exercising.

Information on the user's preferred exercise and/or exercise equipment (IG) can be obtained by using the information on the exercise path.

In addition, the control unit 100 may analyze the exercise images to obtain information about the time (exercise time) allocated to the exercise performed by the user or the exercise equipment used.

For example, as in the case of FIG. 42, the controller 100 determines the time the user exercised using the treadmill (T13), the time the user exercised using the bench press (T10), and the pull-down mechanism. It is possible to obtain information about the time T11 for exercising and the time T12 for exercising using a cycle.

In addition, the preference determination unit 180 of the control unit 100 may determine information about the user's preference for the exercise equipment (IG) based on the exercise image.

For example, the controller 100 may determine information about the occupancy rate for each exercise based on the information about exercise time as shown in FIG. 42 .

Referring to FIG. 43, in the exercise performed by the user, the time invested in the treadmill exercise is 45% of the total exercise time, the time invested in the bench press exercise is 8% of the total exercise time, and the time invested in the pull-down exercise is It can be seen that it is 12% of the total exercise time, and the time invested in cycling exercise is 35% of the total exercise time.

In addition, the controller 100 may determine the user's preference according to each period (day of the week, month, etc.). For example, as in the case of FIG. 44 , the controller 100 may obtain information about the day on which the user performed a treadmill exercise, the day on which a bench press exercise was performed, and the like.

In addition, the control unit 100 may provide recommendation information to the user based on the content analyzed based on the above information.

The exercise information processing device 10 can capture motion images using a plurality of camera units 300 .

For example, as in the case of FIG. 45 , the first exercise area 910 of the exercise area 900 is photographed by the first camera unit 310, and the second exercise area 920 is captured by the second camera unit. It is possible that 320 is in charge of shooting.

This case may correspond to a case where it is difficult for one camera to cover the entire exercise area 900 .

If the selected user exercises in the first exercise area 910, the first camera 310 may capture an exercise image of the user.

Thereafter, when the user leaves the first exercise area 910 and enters the second exercise area 920, the user may not be captured in the image taken by the first camera 310. That is, the first camera 310 may lose sight of the user.

In this case, the corresponding user may be tracked in an image taken by the second camera 320 .

If the second camera 320 finds the corresponding user in the captured image, the second camera 320 is set as a basic camera, and the user's motion image can be subsequently captured using the second camera 320 .

Meanwhile, the controller 100 may determine that the user's exercise ends when the user leaves the exercise area 900 for a predetermined reference time or longer.

Alternatively, the controller 100 may determine that the exercise has ended when the user leaves the exit set in the exercise area 900 and passes a reference time or more.

Alternatively, the controller 100 may determine that the exercise is not ended and the user is taking a break when the user leaves the exercise area 900 for more than a reference time without leaving the exit set in the exercise area 900. .

Thereafter, the controller 100 may determine that when the user re-enters the exercise area 900, the rest ends and the exercise resumes.

In the above, a case of tracking a single user within a certain area (exercise area 900) and capturing a motion image is described, but it is possible to simultaneously track a plurality of users and capture a motion image. An explanation of this is as follows.

Referring to FIG. 46 , in the step of tracking a user (S900), it is possible to simultaneously track a first user (S910), track a second user (S920), and track a third user (S930).

In this case, it is possible to capture motion images for the first user, the second user, and the third user at the same time.

In addition, the path determination unit 170 is capable of determining and obtaining information about the movement path of the selected plurality of users.

For example, as in the case of FIG. 47 , the information on the motion path includes information on the motion path PT1 of the first user in the exercise area 900, information on the motion path PT2 of the second user, and It may include information about the motion path PT3 of the third user.

Using the information on the movement paths of the plurality of users, it is possible to obtain information on the preference for each exercise equipment (IG). In addition, information on areas and routes preferred by users may also be obtained.

Then, it may be possible to rearrange the exercise equipments IG according to the route preferred by the users.

For example, referring to the case of FIG. 47 , the first area AR of the exercise area 900 may not pass through the exercise paths PT1, PT2, and PT3 of the first, second, and third users. Then, it is possible to dispose the exercise equipment IG having a low preference or not to arrange the exercise equipment IG in the first area AR.

As such, it will be understood that the technical configuration of the present invention described above can be implemented in other specific forms without changing the technical spirit or essential features of the present invention by those skilled in the art to which the present invention pertains.

Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting, and the scope of the present invention is indicated by the claims to be described later rather than the foregoing detailed description, and the meaning and scope of the claims And all changes or modified forms derived from the equivalent concept should be construed as being included in the scope of the present invention.

Claims (20)

a camera unit for capturing an exercise image of a user selected as a target among a plurality of users within a preset exercise area; and
A control unit for obtaining information on the user's exercise selected on the basis of the exercise image; includes,
The control unit
An apparatus including an apparatus determining unit for discriminating information on an exercise apparatus used by the user based on the exercise image. According to claim 1,
The control unit
and a path determination unit configured to determine information about a path of the selected user within the exercise area based on the exercise image. delete According to claim 1,
The control unit
and a preference determination unit configured to determine information about the user's preference for the exercise equipment based on the exercise image. According to claim 1,
The camera unit includes a first camera and a second camera,
When the first camera loses the user from view while photographing the user,
The control unit tracks the user in the image captured by the second camera. According to claim 1,
The control unit
An apparatus comprising a type determination unit for determining the type of exercise of the user based on the exercise image. According to claim 1,
The control unit
An apparatus comprising a motion determining unit configured to determine an exercise motion of the user based on the exercise image. According to claim 1,
The control unit
and a number determination unit configured to determine the number of times of exercise of the user based on the exercise image. According to claim 1,
The control unit
Device comprising a time determination unit for measuring the exercise time of the user based on the exercise image. According to claim 1,
The control unit
Apparatus for determining that the user's exercise ends when the user leaves the exercise area for more than a predetermined reference time. A photographing step of capturing an exercise image of a user selected as a target among a plurality of users in a preset exercise area by a camera unit; and
An information acquisition step of acquiring information on the user's exercise selected on the basis of the exercise image;
The information acquisition step
The method further comprising the step of determining information on the exercise equipment used by the user based on the exercise image. According to claim 11,
The information acquisition step
and determining information about a path of the user within the exercise area based on the exercise image. delete According to claim 11,
The information acquisition step
and determining information about the user's preference for the exercise equipment based on the exercise image. According to claim 11,
The camera unit includes a first camera and a second camera,
When the first camera loses the user from the field of view while photographing the user,
A method of tracking the user in an image captured by the second camera. According to claim 11,
The information acquisition step
and determining the type of exercise of the user based on the exercise image. According to claim 11,
The information acquisition step
and determining an exercise motion of the user based on the exercise image. According to claim 11,
The information acquisition step
and determining the number of times of exercise of the user based on the exercise image. According to claim 11,
The information acquisition step
The method further comprising measuring a user's exercise time based on the exercise image. According to claim 11,
The information acquisition step
The method further comprising determining that the user's exercise ends when the user leaves the exercise area for more than a predetermined reference time.

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