KR20170119337A - Apparatus and Method for Processing of Exercise Information - Google Patents

Abstract

The present invention relates to an apparatus and method for processing a motion information.
A motion information processing apparatus according to the present invention includes a camera unit for photographing a motion image of a user, a type discrimination unit for discriminating a motion type of the user on the basis of the motion image, And an operation determination unit for determining the motion of the user based on the motion image.

Description

[0001] Apparatus and Method for Processing Exercise Information [

The present invention relates to an apparatus and method for processing a motion information.

With the improvement of living standards, the interest of modern people is increasing rapidly. As a part of this, modern people are increasingly exercising with disease prevention and personal hobbies.

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

However, PT has the disadvantage of high cost.

If the user conducts the exercise alone, it is difficult to determine the accuracy of the motion of the user or the fitness of the user.

It is an object of the present invention to provide a motion information processing apparatus and method for capturing a motion image of a user and analyzing a photographed motion image to provide motion information.

A motion information processing apparatus according to the present invention includes a camera unit for photographing a motion image of a user, a type discrimination unit for discriminating a motion type of the user on the basis of the motion image, And an operation determination unit for determining the motion of the user based on the motion image.

The apparatus may further include a time determination unit for measuring a user's exercise time based on the motion image.

The information processing apparatus may further include an information providing unit for providing recommendation information to the user based on at least one of information on the type of exercise, information on the number of exercises, information on the exercise operation, and information on the exercise time .

The information providing unit may further provide the user with information on the achievement level based on at least one of the information on the exercise operation, information on the exercise type, information on the exercise frequency, or information on the exercise time can do.

In addition, when the motion type is a motion using a weight mechanism, the apparatus may further include a mechanism determination unit that determines a load set to the weight mechanism.

The number determining unit may count the number of times when the motion of the user is matched by a predetermined reference ratio or more to a preset reference motion.

In addition, the operation determination unit may further provide information on the similarity between the motion operation of the user and a preset reference motion.

The object recognition unit may further include an object recognition unit for analyzing the motion image to recognize a moving object. The object recognition unit extracts a background from the motion image, recognizes a portion having a color different from the extracted background as the moving object can do.

The motion estimating unit may further include a motion calculating unit that calculates motions based on the direction and degree of the brightness varying by dividing the motion of the moving object with different brightness according to time.

In addition, the frequency determining unit may determine the number of times of motion of the user based on the motility, and the motion determining unit may determine the motion of the user based on the motility.

According to another aspect of the present invention, there is provided a method for processing a motion information, comprising the steps of capturing a motion image of a user, discriminating the type of motion of the user based on the motion image, determining the number of motions of the user based on the motion image And determining the motion of the user based on the motion image.

The method may further include measuring a user's exercise time based on the motion image.

The method may further include providing the recommendation information to the user based on at least one of information on the type of exercise, information on the number of times of exercise, information on the exercise operation, or information on the exercise time have.

The method may further include providing information on the achievement level to the user based on at least one of the information on the exercise operation, information on the exercise type, information on the exercise frequency, and information on the exercise time can do.

Further, when the motion type is a motion using a weight mechanism, it may include a step of determining a load set to the weight mechanism.

In addition, the number of times the user's motion is counted can be counted when the motion of the user is matched more than a predetermined reference ratio to a preset reference motion.

In addition, the method may further include providing information on the motion of the user and the similarity of the preset reference motion.

Further, the method may further include a recognition step of analyzing the motion image to recognize a moving object. In the recognition step, a background is extracted from the motion image, and a part having a color different from the extracted background is recognized as the moving object can do.

Further, the method may further include dividing the movement of the moving object by different brightness according to time, and calculating the mobility based on the direction and the degree of change of the brightness.

The method may further include determining a number of times of the user's motion based on the motility, and determining the motion of the user based on the motility.

The apparatus and method for processing exercise information according to the present invention can provide information about the exercise operation and the number of exercises of the user by analyzing the user's exercise image to provide objective and accurate exercise information to the user at a lower cost It is effective.

1 is a diagram for explaining a configuration of a motion information processing apparatus according to the present invention,
2 to 33 are views for explaining a method of processing exercise information according to the present invention,
34 to 37 are diagrams for explaining another exercise information processing method according to the present invention.

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

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 that the present invention is not intended to be limited to the specific embodiments but includes all changes, equivalents, and alternatives falling within the spirit and scope of the present invention.

In describing the present invention, the terms first, second, etc. 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 element 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.

The term " and / or " may include any combination of a plurality of related listed items or any of a plurality of related listed items.

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, but other elements may be present in between Can be understood. On the other hand, when it is mentioned that an element is "directly connected" or "directly connected" to another element, it can be understood that no other element exists 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 may include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used interchangeably to designate one or more of the features, numbers, steps, operations, elements, components, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, may 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 can be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are, unless expressly defined in the present application, interpreted in an ideal or overly formal sense .

In addition, the following embodiments are provided to explain more fully to the average person skilled in the art. The shapes and sizes of the elements in the drawings and the like can be exaggerated for clarity.

1 is a diagram for explaining a configuration of a motion information processing apparatus according to the present invention.

1, a motion information processing apparatus 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, . ≪ / RTI >

The camera unit 300 can take a predetermined image under the control of the control unit 100. [ For example, the camera unit 300 can take a motion image of the user. Alternatively, the camera unit 300 can photograph an image of a predetermined exercise area (such as a health club).

The camera unit 300 may include at least one camera.

The output unit 400 may output predetermined information according to the control of the control unit 100 so that the user can confirm the information. In detail, the output unit 400 may output information on the motion, such as the reference motion of the motion, the reference frequency, etc., so that the user can confirm the information.

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 an image. The audio output unit 420 can output various information by voice.

The user input unit 500 may be used by 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 information under the control of the control unit 100. [ For example, the memory unit 600 may store information on a reference count, a reference operation, a reference time, and the like.

The communication unit 700 can perform communication with other devices. For example, the communication unit 700 can transmit motion information or an edited motion image to another device or a pre-designated predetermined page (web site) under the control of the control unit 100. [

The control unit 100 can control the overall operation of the exercise information processing apparatus 10. [

The control unit 100 can acquire various information on the motion of the user based on the motion image captured by the camera unit 300.

The control unit 100 can determine the start and end of the user's motion.

The control unit 100 includes a type determination unit 110, an operation determination unit 120, a frequency determination unit 130, a time determination unit 140, and a device determination unit (not shown) The navigation system includes a tracking unit 160, a path determination unit 170, a preference determination unit 180, an object recognition unit 190, a motility determination unit 200, an information providing unit 210, and an editing unit 220 can do.

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

The motion determining unit 120 can determine the motion of the user based on the motion image.

The frequency determination unit 130 can determine the number of times of the user's motion based on the motion image.

The number determining unit 130 may count the number of motions when the user's motion is matched with a preset reference motion by a predetermined ratio or more.

The time determining unit 140 can determine the user's exercise time based on the motion image.

The apparatus determining unit 150 can determine the type of the exercise instrument selected by the user.

In addition, when the motion type is the motion using the weight mechanism, the device determination unit 150 can determine the 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 moving range.

The path determination unit 170 can determine information about a path in the motion area of the selected user based on the motion image.

The preference determining unit 180 may determine at least one user's preference or at least one user's preference for the warm-up type for the exercise device.

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

The motility calculation unit 200 can distinguish the motions of the moving objects recognized by the object recognition unit 190 with different brightnesses according to time, and calculate the motility based on the direction and degree of brightness change.

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 times of exercise, or information on the exercise time.

In addition, the information providing unit 210 may provide various information obtained by analyzing the motion image to a user, another device, and / or a predetermined web site.

The image editing unit 220 can extract / edit the highlight image from the user's motion image.

The exercise information processing device 10 having the configuration shown in Fig. 1 can be realized by various types of hardware. For example, the motion information processing apparatus 10 according to the present invention may be manufactured in the form of a mobile communication terminal such as a smart phone or a fixed terminal such as a CCTV.

A motion information processing method using the motion information processing device having such a configuration will be described in detail below with reference to the accompanying drawings.

2 to 37 are views for explaining a motion information processing method according to the present invention. In the following, description of the contents described above may be omitted.

Referring to FIG. 2, in the motion information processing method according to the present invention, it is possible to first set the motion picture processing apparatus 10 (S100).

In the setting step, it is possible to arrange the camera unit 300 at a position where the motion image can be photographed.

Alternatively, the motion information processing apparatus 10 can be set to the motion image shooting mode.

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

When a photographing command is input, the camera unit 300 can photograph a user's motion image under control of the controller 100 (S400). For example, as in the case of Fig. 3, it is possible for the motion information processing device 10 in the form of a mobile communication terminal to photograph an image in which the user H is moving.

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

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

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

In the information providing step, the communication unit 700 can transmit the information determined by the control unit 100 to another device or a predetermined homepage or the like under the control of the control unit 100. [

A method of analyzing the motion image will be described below.

Referring to FIG. 4, in step S300 of analyzing the motion image, a background may be extracted from the motion image S310. More specifically, a plurality of image frames can be compared to determine a motionless or very small portion as a background, and a background can be extracted according to the determined result.

For example, as in the case of FIG. 5, if the first frame (A) and the second frame (B) after the first frame A are compared with each other, (OB), and it can be confirmed that the object (OB) is not included in the first frame (A).

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

The images of the remaining portions except the object OB in the first frame A and the second frame B hardly change. In other words, the rest of the image except the object OB has little motion. Therefore, all the remaining parts except the object OB can be recognized as the background.

Alternatively, if the moving object OB is not captured in the moving image, the same image as the first frame A may continue. In this case, the first frame (A) image can be recognized as a background image. In other words, all the parts of the first frame A can be recognized as backgrounds.

As described above, it is possible to recognize and extract a motionless portion as a background during a preset reference frame period in an image.

When a background image similar to the first frame A is continued and the object OB is captured by the camera unit 300, an image similar to the second frame B can be obtained. If the object OB continuously moves and leaves the screen, the same image as the first frame A will be obtained again.

When the image before the object OB passes and the image after the object OB passes are compared, the two images can be almost the same.

As described above, even if the motion of the object OB is detected while moving the object OB for a predetermined period of time, if the image before the object OB is captured and the images after the object OB have passed are substantially the same, Can be mostly background.

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

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

Thereafter, the background (the background image) and the colors of the other motion images can be compared (S320).

The object recognizer 190 recognizes a portion having a color different from the background in the moving image as the moving object OB (S330).

For example, as shown in Fig. 6A, a portion having a different color from the background, that is, the object OB can be detected.

In addition, after separating the background and the object (OB), the background can be processed in a single color. For example, you can treat the background as black. In this case, the motion of the object OB can be more easily analyzed.

Thereafter, as shown in Fig. 6B, the silhouette of the object OB can be discriminated. In Fig. 6 (B), the red part ER in the upper left corner is very different from the human form, so it can be treated as an error.

In this process, the moving object (OB) can be recognized in the motion image.

Thereafter, the motion calculating unit 200 may analyze the motion of the object OB (S340).

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

In detail, the motion calculating unit 200 can distinguish the motion of the moving object OB by changing the brightness with time. In addition, the motion calculating unit 200 can calculate the mobility based on the direction and degree of change in brightness.

For example, as in the case of Fig. 7, suppose that the object OB, i.e., the user lifts the left arm.

As shown in FIG. 7, the current state of the user can be relatively brightened, and the previous state can be relatively darkened.

In such a case, it can be determined that the user's left arm moves from the dark portion to the bright portion upward from below. That is, the direction of motion can be determined.

In addition, the movement speed of the arm can be determined according to whether the brightness change of the left arm is abrupt or gentle.

For example, as shown in Fig. 8A, when the object OB rotates 180 degrees (degrees) about the axis and when the object OB is 90 degrees (degrees) about the axis as shown in Fig. 8B, ) Let us suppose that it rotates.

8 (A) and 8 (B) are the same, it can be seen that the case of FIG. 8 (A) is higher in motility than the case of (B), that is, the moving speed is faster .

Alternatively, as shown in FIGS. 9A and 9B, it is assumed that the object OB rotates 180 degrees (degrees) about the respective axes.

In the case of FIG. 9A, when the change of brightness occurs more rapidly in the case of FIG. 9A than in FIG. 9A, the object OB is 180 degrees in a relatively short time, In the case of FIG. 9B, the object OB may rotate 180 degrees (degrees) for a relatively long time.

Accordingly, the case of (A) in Fig. 9 can be greater in motility than the case of (B).

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

On the other hand, it is possible to use a predetermined mask to detect motion. For example, a predetermined size mask may be applied to a specific area of the image, and the mobility may be determined by detecting a change in luminance of the mask.

How to identify exercise information is as follows.

The information on the type of exercise, the exercise operation, the number of times of exercise, and the exercise time, which will be described below, can be determined based on the information on the mobility calculated by the mobility calculation unit 200.

Referring to FIG. 10, in the information determination step (S400), at least one of the type of motion, the motion motion, the number of motions, the motion time, the motion mechanism, the motion path, or the preference can be determined.

A method of discriminating a movement operation and / or a kind will be described as follows.

Information about the reference motion can be set and stored for each type of motion. 11, the reference angle Xb between the ground (GND) and the legs of the user H, the reference distance Xa between the upper body and the floor GND, etc. in the case of the push- Information can be set in advance.

12 (A) and 12 (B), when the camera unit 300 captures a user's motion image, the motion determiner 120 analyzes the motion image to perform a motion operation Can be identified.

The operation determination unit 120 can determine / obtain information about the motion operation with respect to the angle between the floor and the leg, the distance between the upper body and the floor, and the like.

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

12 (A), the angle between the ground (GND) and the legs 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 discriminate to what extent the first angle Xb1 is similar to the preset reference angle Xb and to what extent the first distance Xa1 is similar to the reference distance Xa.

If the first angle Xb1 is similar to the reference angle Xb within a predetermined predetermined range and the first distance Xa1 is similar to the reference distance Xa within a preset predetermined range, A) can be identified by push-and-push.

In this way, it is possible to discriminate the exercise form of FIG. 12 (B) by pushing up and down.

13, the angle (third angle X2) between the ground (GND) and the leg is set to be similar to the preset reference angle Xb within a preset range The upper end of the user H is in contact with the floor (GND), so that the type discriminating unit 110 can recognize that the stroke is not the arm-pushing-up.

For convenience of explanation, only the reference distance Xa and the reference angle Xb are described for the reference information, but the present invention is not limited to this. For example, information on the position of the buttocks, the angle of the knee, the position of the head, the angle of both arms, the position of both hands, and the like can be set as the reference information.

The motion determining unit 120 can discriminate / acquire information on the motion motion in the motion image, and can also determine information on the motion accuracy.

The operation determination unit 120 may determine how similar the user's motion is to a preset reference motion. In other words, the operation determination unit 120 can determine how precisely and accurately the user H is performing the motion.

For example, as in the case of Fig. 14, the information about the octagon angle, the degree of bending arm, the angle between the floor and the leg, the knee angle, the hip height, Can be determined.

In addition, the operation determination unit 120 may calculate an overall evaluation score on the accuracy with respect to the reference motion operation of the user's motion. That is, it is possible to set a model answer for the exercise operation and to evaluate the score of the user's exercise operation.

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

For example, in the case of a running exercise, items such as the angle at which the foot is taken, the stride, the angle of the arm, the movement of the upper body and the lower body can be evaluated, and the accuracy can be determined according to the evaluation result.

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

For example, when the user proceeds the motion in the form of (A), (B), (C), (D), or (E) of FIG. 15, the operation determining unit 120 determines ), (B), (C), (D), and (E) can all be determined as an arm push-up motion.

In addition, the operation determination unit 120 determines the degree of difficulty in the case of FIG. 15A as the first level and the degree of difficulty in the case of FIG. 15B as the degree of difficulty The degree of difficulty in the case of FIG. 15 (C) is determined to be a second level higher than the second level, and the degree of difficulty in 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 determine the degree of difficulty in the case of (E) in Fig. 15 as a fifth level (Fifth Level) higher than the fourth level.

In the above description, the case of bare-handed motion (push-up) is explained, but the above description can also be applied to the exercise using the apparatus.

The criterion for determining the accuracy of the operation of the operation determination unit 120 can be set differently according to the movement of the bare hand and the movement of the mechanism, and can be set differently according to the type of the mechanism.

As shown in FIG. 16, when the user H carries out a movement using a predetermined exercise device 800, the exercise information processing device 10 in the form of a mobile communication terminal can take a motion image thereon.

In this case, the motion information processing apparatus 10 can analyze / discriminate the kind of motion and information on the motion motion according to the above-described contents.

The device determining unit 150 of the motion information processing device 10 can determine the type of the exercise device 800 used by the user H to exercise.

For example, it is possible to store shape information and image information for each exercise apparatus in the memory unit 600, compare the same with the exercise apparatus shown in the exercise image, and determine what type of exercise apparatus is used by the user .

Alternatively, it is also possible to assign identification information, such as a bar code, to each exercise device so as to identify the device, and to use this information to identify the exercise device.

In addition, when the type determined by the type determining unit 110 is a motion using a weight mechanism, the device determining unit 150 can determine a load set in the weighting mechanism.

For example, information on the weight, size, and shape of the weight used in each exercise machine is stored in advance in the memory 600, and compared with the weight used by the user in the exercise image, The load can be determined.

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

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

For example, let us assume that the result of analyzing the user's motion image is as shown in FIG. 17.

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

In this case, the time determining unit 140 determines whether the user performs the exercise during the periods T1-T2, T3-T4 and T5-T6 and rests during the periods T0-T1, T2-T3, T4- .

As described above, the time determination unit 140 can determine not only the information on the user's exercise time but also information on the break time.

The above-described information on the type of exercise, exercise operation, exercise time, exercise equipment, and the like can be processed in a form that can be confirmed to 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) Exercise time and the like can be provided to the user.

Information on the exercise set can be determined in the same manner as in FIG.

The frequency determination unit 130 can determine the number of times of the user's motion based on the motion image.

For example, when the user H performs the push-up exercise as shown in Fig. 19, one arm-pushing motion can be discriminated from the operation of bending and stretching the arm in the prone position. If the user keeps his / her arm without bowing, it can be judged that he / she does not perform the push-up exercise for a long time.

The frequency determining unit 130 may preferably count the number of times when the user's motion is matched by more than a predetermined reference ratio to a preset reference motion.

20A, the reference angle Xb between the ground (GND) and the leg of the user H, the reference distance Xa between the upper body and the floor GND in the case of the push-up and pull-up motion, And the like can be set in advance.

20B, the angle between the ground GND and the legs of the user H is the third angle Xb3, and the angle between the upper body and the floor GND, It is judged how much the third angle Xb3 is similar to the preset reference angle Xb when the distance between the third distance Xa3 and the third distance Xa3 is larger than the reference distance Xa, A similarity can be determined.

As a result of the determination, if the third angle Xb3 matches the reference operation (reference angle Xb) more than the reference ratio and the third distance Xa3 is larger than the reference operation (reference distance Xa) It can be determined that the user H has performed the push-up exercise once.

21 (B), even if the angle Xb4 between the ground (GND) and the leg is matched with the reference angle Xb by more than the reference ratio, the user H Since the distance Xa4 between the upper body of the user H and the ground GND is not matched with the reference movement by more than the reference ratio because the distance Xa4 between the upper body of the user H and the ground GND does not change, It can be judged that the exercise is not performed.

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

For example, assume that the user H uses a pull-down exercise device 810 as shown in Fig.

In this case, it can be judged that the pulling operation of the pull-down exercising apparatus 810 is performed with the arm of the user H up and down together with the pulling operation of the user H while raising and lowering the arm, have.

The information providing unit 210 may provide information on the exercise result to the user.

For example, as in the case of FIG. 23 (A), information on the current state of the user (the number of times the user performs the push-up and pull-up exercises), the average number of times, and the target value are provided together with the push- It is possible to do.

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

23 (C) shows a case of a bench press motion.

The information providing unit 210 may provide information on the achievement level to the user based on at least one of information on the type of exercise, information on the number of times of exercise, or information on the exercise time. Achievement can be increased with more exercise frequency and shorter exercise time.

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

Achievement information can also be applied to pulldown and bench presses.

In addition, 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 times of exercise, or information on the exercise time. Here, the recommendation information may include at least one of recommendation information on the number of exercises, recommendation information on exercise time, or recommendation information on the kind of exercise.

For example, as shown in FIG. 24 (B), it is recommended to increase the number of times of execution by 20% in the case of the push-up and pull-up motion, to increase the load by 16% in the case of pull-down movement, %. It is also advisable to add a butterfly motion instead of reducing the number of bench presses. This is because the achievement of the bench frame motion exceeds 100% as shown in FIG. 24 (A).

Alternatively, as shown in FIG. 25 (A), it is possible to provide the user with recommendation information on the exercise operation such as straightening the knee more straightly in the case of the push-up and pull-up exercise.

In addition, as shown in FIG. 25 (B), an example of a desired push-up and down operation can be displayed on the display unit 410 so that the user can understand it easily.

Provision of recommendation information can 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-up.

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

In FIG. 26, for the sake of convenience of description, the motion operation is expressed by the skeletal motion as shown in FIG. 26 (B), but the present invention is not limited thereto. For example, in the case of yoga exercise, the mobility can be analyzed / discriminated by the object recognition unit 190 and the mobility calculation unit 200 described above.

When the user's motion motion information MD is obtained, the user's motion motion information MD can be compared with preset reference motion information SD as shown in Fig. 26C.

As a result of comparison, the similarity between the user's operation information (MD) and the reference operation information (SD) can be determined as the achievement.

For example, as shown in FIG. 27 (A), the arm motion in the user's yaw motion is 92% similar to the reference motion information SD, the leg motion is 95% similar, and the torso motion is 98% Can be identified. In other words, the user's yoga movements can be seen to have 92% accuracy in arm movements.

Based on the information on such accuracy, as shown in FIG. 27 (B), it is possible to provide recommendation information on the exercise to the user.

It is also possible that performance may be determined by exercise time, regardless of load or frequency.

For example, as shown in (A) of FIG. 28, it is possible to discriminate / provide achievement of 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 can be provided to the user based on the achievement of each exercise.

For example, if the exercise time of the user's push-up exercise is less than the average (10 minutes), it is possible to provide the user with recommendation information that the user should spend more time in the push-up exercise.

The performance according to the exercise time may be preferably applied to the exercise such as yoga and running.

For example, as shown in Fig. 29 (A), assume that the user H takes a grasshopper posture, a sideline posture, a plow posture, and an eagle posture in yoga exercise.

In this case, the user can discriminate / provide the achievement (100%) by comparing the time (60 seconds) with which the user takes the grasshopper posture and maintains the posture with the preset reference time (60 seconds).

In addition, based on the achievement, the user can be provided with recommendation information such as reducing the eagle's posture time and increasing the practice time of the diving posture and the plow posture.

On the other hand, it is possible to provide recommendation information differently depending on the degree of difficulty.

For example, as in the case of Fig. 30, in the case of the push-up and pull-up exercise, the case of performing 100 times for 10 minutes is set as the level 1, the case of 130 times for 10 minutes is executed as 160 times for the level 2, , The level 3 is executed for 10 minutes, the level 4 is executed for 10 minutes, and the level 5 is set 220 times for 10 minutes.

As shown in (A) of FIG. 31, when Level A user A performs a total of 90 push-up exercises for 10 minutes and the achievement is 69%, the level is set to level 1 as shown in FIG. 31 (B) It is recommended to adjust it downward.

Alternatively, the level of the user A can be forcibly lowered from the level 2 to the level 1 in the exercise information processing device 10.

On the other hand, as shown in FIG. 32 (A), when the level B level user B performs a total of 230 push-up exercises for 10 minutes and the achievement level is 121, It is recommended to adjust the level up.

Alternatively, the exercise information processing device 10 can forcibly increase the level of the user B from level 4 to level 5. [

The information providing unit 210 can provide information on the health status of the user by comparing various information collected from the user with information of other users.

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

In the above description, the case where the motion information processing apparatus 10 discriminates the kind of exercise performed by the user from the motion image has been described, but it is possible to provide the motion information processing apparatus 10 with information on the type of motion first . Hereinafter, the present invention will be described with reference to the accompanying drawings.

34 to 37 are diagrams for explaining another exercise information processing method according to the present invention. Hereinafter, the description of the portions described in detail above will be omitted. For example, the following may be approximately the same as described above unless otherwise noted, except that it provides information about the type of motion and information about the reference motion of the motion in advance to the user .

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

In this case, the type discriminating unit 110 may be omitted in the control unit 100. [

35 to 36, the motion information processing apparatus 10 displays information on the motion type and the reference motion of the motion on the screen (the display unit 410) before the motion image capturing, ).

Then, the user can confirm what kind of exercise he / she should perform at present.

The exercise information processing device 10 monitors whether the user H is performing the exercise.

It may be desirable to apply this method to movements that perform various exercises on a set-by-set basis, such as a crossfit.

For example, as in the case of FIG. 37, a yoga exercise can be performed to maintain the braided leg posture in the first step.

In such a case, as in the case of Fig. 35, information on the reference operation information of the legged posture can be displayed on the display unit 410. Fig.

In such a case, the exercise information processing apparatus 10 can discriminate the exercise operation for the braid leg posture motion of the user.

In addition, when the user completes the yoga exercise in which the user holds the legged posture, that is, when the exercise is completed, the exercise information processing device 10 performs the exercise type and the reference movement for another exercise, for example, the push- Can be provided.

Thereafter, the exercise information processing device 10 can determine the number of times the user exercises for the push-up and pull-up motion.

In other words, the motion information processing apparatus 10 provides the user with information on the reference motion for the first exercise, identifies / informs the motion information about the first motion and / Can be obtained.

Then, the motion information processing apparatus 10 further provides information on the reference motion of the second exercise (Second Exercise) different from the first motion when the first motion is finished, Information on the number of times of exercise can be discriminated / acquired.

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

The first condition is that the number of motions for the first movement of the user reaches a preset reference number and the case where the motions for the first movement of the user are matched with the reference motion by more than a preset reference ratio, 2 condition.

Here, when at least one of the first condition or the second condition is satisfied, it can be determined that the first motion is ended.

In this way, it is possible to discriminate / acquire various kinds of exercise information during exercise such as cross pit.

As described above, it is to be understood that the technical structure of the present invention can be embodied in other specific forms without departing from the spirit and essential characteristics of the present invention.

It should be understood, therefore, that the embodiments described above are to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than the foregoing description, And all changes or modifications derived from equivalents thereof should be construed as being included within the scope of the present invention.

Claims (20)

A camera unit for photographing a user's motion image;
A type determining unit for determining a type of the user's motion based on the motion image;
A frequency determining unit for determining a frequency of motion of the user based on the motion image; And
An operation determining unit for determining a motion of the user based on the motion image;
/ RTI > The method according to claim 1,
And a time discrimination unit for measuring a user's exercise time based on the motion image. 3. The method of claim 2,
Further comprising an information providing unit for providing recommendation information to the user based on at least one of information on the type of exercise, information on the number of exercises, information on the exercise operation, and information on the exercise time. 3. The method of claim 2,
The information providing unit may further provide information on the achievement to the user based on at least one of information on the exercise operation, information on the exercise type, information on the exercise frequency, . The method according to claim 1,
And a device discrimination unit for discriminating a load set to the weight mechanism when the motion type is a motion using the weight mechanism. The method according to claim 1,
Wherein the number determining unit counts the number of times when the motion of the user is matched by a predetermined reference ratio or more to a preset reference operation. The method according to claim 1,
Wherein the operation determination unit further provides information on a similarity between a motion operation of the user and a predetermined reference operation. The method according to claim 1,
And an object recognition unit for analyzing the motion image and recognizing a moving object,
The object recognition unit
Extracts a background from the motion image, and recognizes a part having a color different from the extracted background as the moving object. 9. The method of claim 8,
Further comprising a motion calculating unit for dividing the motion of the moving object by different brightness according to time and calculating the motion based on the direction and degree of the brightness changing. 10. The method of claim 9,
Wherein the frequency determining unit determines the number of times the user exercises based on the motility,
Wherein the operation determination unit determines the motion operation of the user based on the mobility. Capturing a motion image of a user;
Determining a movement type of the user based on the motion image;
Determining a number of times of motion of the user based on the motion image; And
Determining a motion of the user based on the motion image;
≪ / RTI > 12. The method of claim 11,
And measuring a user's exercise time based on the motion image. 13. The method of claim 12,
And providing recommendation information to the user based on at least one of information on the type of exercise, information on the number of times of exercise, information on the exercise operation, and information on the exercise time. 13. The method of claim 12,
And providing information on the achievement level to the user based on at least one of information on the exercise operation, information on the exercise type, information on the exercise frequency, and information on the exercise time . 12. The method of claim 11,
And a step of discriminating a load set to the weight mechanism when the motion type is a motion using the weight mechanism. 12. The method of claim 11,
And counting the number of times when the motion of the user is matched by a preset reference ratio to a predetermined reference operation. 12. The method of claim 11,
Further comprising providing information about the motion behavior of the user and a similarity of a predetermined reference motion. 12. The method of claim 11,
Further comprising a recognition step of analyzing the motion image to recognize a moving object,
Wherein the recognition step extracts a background from the motion image and recognizes a part having a color different from the extracted background as the moving object. 19. The method of claim 18,
Further comprising dividing the movement of the moving object by different brightness according to time, and calculating the mobility based on the direction and degree of change of the brightness. 20. The method of claim 19,
Determining a number of times the user is exercising based on the motility; And
Determining a motion of the user based on the motility;
≪ / RTI >

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