TW201926238A - Information processing device and program - Google Patents

Abstract

This information processing device for evaluating a subject's beauty of movement is provided with: a means for acquiring a moving image of a walking subject; a means for extracting the walking speed, the walking posture, and the motion frequency through analysis of the moving image; a means for calculating a first parameter on the basis of a correlation between the walking speed and beauty; a means for calculating a second parameter on the basis of a correlation between the walking posture and beauty; a means for calculating a third parameter on the basis of a correlation between the motion frequency and beauty; and a means for calculating a beauty-of-movement score, which is an index related to the beauty of movement, using the first through third parameters.

Description

Information processing device, program

The present invention relates to an information processing apparatus and program.

It is known that there is a correlation between walking action and the characteristics of the human body. That is, if the walking motion is observed, the characteristics of the human body can be known. For example, Japanese Laid-Open Patent Publication No. H06-6305 discloses a technique for estimating the physical strength of a subject based on a walking parameter indicating a walking state.

[The problem that the invention wants to solve]

According to recent research, it is gradually found that there is a correlation between the walking motion of human beings and the gracefulness of human activities.

However, the technique of Japanese Patent Laid-Open No. 2017-6305 is only for assessing the physical strength, and therefore the gracefulness of the activity cannot be evaluated.
That is, in the prior art, the gracefulness of the activity cannot be evaluated based on the walking motion.

The object of the present invention is to evaluate the gracefulness of an activity based on walking motion.
[Technical means to solve the problem]

One aspect of the present invention is an information processing device.
It evaluates the gracefulness of the activity of the subject and has the following:
a mechanism for obtaining a moving image of a subject being walked;
a mechanism for extracting a walking speed, a walking posture, and an activity frequency by analyzing the moving image;
a mechanism for calculating the first parameter based on the correlation between the walking speed and the grace level;
a mechanism for calculating the second parameter based on the association between the walking posture and the grace level;
a mechanism for calculating a third parameter based on the correlation between the activity frequency and the grace level; and a mechanism for calculating a score of the grace of the activity using the first parameter to the third parameter.
[Effects of the Invention]

According to the present invention, the gracefulness of the activity can be evaluated based on the walking action.

Hereinafter, an embodiment of the present invention will be described in detail based on the drawings. In the drawings, the same components are denoted by the same reference numerals, and the description thereof will not be repeated.

(1) The composition of the information processing system explains the composition of the information processing system. Fig. 1 is a schematic view showing an information processing system of the embodiment. Figure 2 is a block diagram showing the construction of the information processing system of Figure 1.

As shown in FIG. 1, the information processing system 1 includes a client device 10 and a server 30.
The client device 10 and the server 30 are connected via a network (e.g., the Internet or an internal network) NW.

The client device 10 is an example of a message processing device that transmits a request to the server 30. The client device 10 is, for example, a smart phone, a tablet terminal, or a personal computer.

The server 30 is an example of an information processing device that provides a response to the client device 10 in response to a request transmitted from the client device 10. The server 30 is, for example, a web server.

(1-1) Configuration of Client Device The configuration of the client device 10 will be described.

As shown in FIG. 2, the client device 10 includes a memory device 11, a processor 12, an input/output interface 13, a communication interface 14, and a camera 15.

The memory device 11 is constructed in the form of a memory program and data. The memory device 11 is, for example, a combination of a ROM (Read Only Memory), a RAM (Random Access Memory), and a storage (for example, a flash memory or a hard disk).

The program includes, for example, the following programs.
・Program of OS (Operating System) ・Program for executing information processing (for example, web browser)

The information includes, for example, the following information.
• The database referenced in the information processing • The information obtained by performing the information processing (that is, the execution result of the information processing)

The processor 12 is configured to implement the functions of the client device 10 by activating a program stored in the memory device 11. The processor 12 is an example of a computer.

The input/output interface 13 is configured to acquire an instruction from a user connected to the client device 10 and output information to an output device connected to the client device 10.
The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof.
The output device is for example a display.

The communication interface 14 is constructed to control communication between the client device 10 and the server 30.

The camera 15 is configured to capture a moving image and generate moving image data of the captured moving image (hereinafter referred to as "capturing moving image"). The camera 15 has, for example, a CMOS (Complementary Metal Oxide Semiconductor) image sensor.

(1-2) Configuration of Server The configuration of the server 30 will be described.

As shown in FIG. 2, the server 30 includes a memory device 31, a processor 32, an input/output interface 33, and a communication interface 34.

The memory device 31 is constructed in the form of a memory program and data. The memory device 31 is, for example, a combination of a ROM, a RAM, and a storage (for example, a flash memory or a hard disk).

The program includes, for example, the following programs.
・OS program ・Application program for executing information processing

The information includes, for example, the following information.
・Database and information processing execution results that are referenced in information processing

The processor 32 is configured to implement the function of the server 30 by activating a program stored in the memory device 31. The processor 32 is an example of a computer.

The input/output interface 33 is configured to acquire an instruction from a user connected to the server 30 and output information to an output device connected to the server 30.
The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof.
The output device is for example a display.

The communication interface 34 is constructed to control communication between the server 30 and the client device 10.

(2) Outline of the present embodiment The outline of this embodiment will be described. Fig. 3 is an explanatory view showing an outline of the embodiment.

As shown in FIG. 3, the client device 10 captures a moving image of the subject OBJ during walking, and generates moving image data for capturing a moving image.
The client device 10 transmits the moving image data to the server 30.

The server 30 calculates the score of the grace of the activity by performing image analysis on the moving image data transmitted from the client device 10.

As described above, the server 30 of the present embodiment evaluates the gracefulness of the activity of the subject OBJ based on the moving image of the subject OBJ during walking. Thereby, the evaluation index of the gracefulness of the activity of the subject OBJ can be obtained only by taking a shadow of the walking situation.

(3) The database describes the database of the embodiment. The following database is stored in the memory device 31.

(3-1) Subject Information Database The subject information database of the present embodiment will be described. Fig. 4 is a view showing the data structure of the subject information database of the present embodiment.

In the subject information database of FIG. 4, the subject information related to the subject is stored.
The subject information database includes a "subject ID (identification)" field, a "subject name" field, and a "subject attribute" field. Each field is associated with each other.

In the "Subject ID" field, the subject ID identifying the subject OBJ is stored. The subject ID is arbitrarily determined by the server 30.

In the "Subject Name" field, information related to the name of the subject OBJ (for example, text) is stored.

In the "Subject attribute" field, the subject attribute information related to the attribute of the subject OBJ is stored. The "Subject Attributes" field includes the "Gender" field, the "Age" field, and the "Occupation" field.

In the "Gender" field, information related to the gender of the subject OBJ is stored.

In the "Age" field, information related to the age of the subject OBJ is stored.

In the "Occupation" field, information related to the occupation of the subject OBJ is stored.

(3-2) Computational Master Data Library The calculation master data library of this embodiment will be described. Fig. 5 is a view showing the data structure of the calculation type master data library of the present embodiment.

In the calculation master data library of FIG. 5, a calculation formula corresponding to the object attribute information is stored.
The computational master database includes the "Object Properties" field and the "Calculation" field. Each field is associated with each other.

The "Subject Attributes" field is the same as the "Subject Attributes" field in Figure 4.

In the "Calculation" field, the first calculation formula (Formula 1) for calculating the speed score S1 (an example of "1st score") and the posture score S2 (for example, "the second score") are stored. The fourth calculation formula (Formula 2), the third calculation formula (Formula 3) for calculating the technical score S3 (an example of "the third score"), and the fourth calculation formula for calculating the score Sm of the grace degree of the activity (Formula 4).

Formula 1 is an example of the first calculation formula. The coefficients w11 to w13 are determined based on the subject attribute information. The coefficient w11 is larger than the coefficients w12 and w13. In general, walking speed is known to depend on mental state. The psychological state is, for example, reflected in the stress level, or the measured value of the mouth angle activity at the time of smiling, or the state evaluated by the measured value. Since the coefficient w11 is larger than the coefficients w12 and w13, the speed score S1 can also be referred to as "a score related to the psychological state of the subject". The greater the speed score S1, the more negative the mental state (eg, the state of depression).
[Number 1]

・p1...the first parameter related to the walking speed of the subject, w11...the first weighting factor related to the walking speed of the speed score S1, p2...the second parameter related to the walking posture of the subject ・W12...the second weighting coefficient related to the walking posture of the speed score S1, p3...the third parameter related to the walking technique of the subject, w13...the third related to the walking technique for calculating the speed score S1 Weighting factor

Equation 2 is an example of the second calculation formula. The coefficients w21 to w23 are determined based on the subject attribute information. The coefficient w22 is larger than the coefficients w21 and w23. In general, walking postures are known to depend on body composition. The body composition is, for example, reflected in a measured value of the body fat percentage or a state evaluated using the measured value. Since the coefficient w22 is larger than the coefficients w21 and w23, the posture score S2 can also be referred to as "a score related to the body composition of the subject". The larger the posture score S2, the more negative the body composition (for example, the fat is above the average).
[Number 2]

・w21... The first weighting factor for calculating the posture score S2 in relation to the walking speed, w22, the second weighting factor for calculating the posture of the posture score S2, and the w23... for calculating the posture score S2 and walking. Technology-related third weighting factor

Equation 3 is an example of the third calculation formula. The coefficients w31 to w33 are determined based on the subject attribute information. The coefficient w33 is larger than the coefficients w31 and w32. In general, walking techniques are known to be dependent on motion control. The motion control is, for example, reflected in a measured value of the skeletal muscle index or a state evaluated using the measured value. Since the coefficient w33 is larger than the coefficients w31 and w32, the technical score S3 can also be referred to as "a score related to the motion control of the subject". The larger the technical score S3, the more negative the motion control (for example, the state in which the rhythm of the motion is not fixed).
[Number 3]

・w31...the first weighting factor for calculating the technical score S3 in relation to the walking speed, w32...the second weighting factor for calculating the technical score S3 and the walking posture, w33...for calculating the technical score S3 and walking Technology-related third weighting factor

Equation 4 is an example of the fourth calculation formula. The coefficients wm1 to wm3 are determined based on the subject attribute information.
[Number 4]

・wm1... The first weighting factor for calculating the grace level of the activity Sm and the walking speed, wm2, the second weighting factor for the walking posture, and the second weighting factor for the walking posture. To calculate the graceful degree of activity, Sm, the third weighting factor related to walking technique

(3-3) Evaluation Master Database The master database of this embodiment will be described. Fig. 6 is a view showing the data structure of the evaluation master database of the present embodiment.

In the evaluation master database of Figure 6, the information related to the assessment corresponding to the score is stored.
The assessment master database includes the "Score" field and the "Evaluation" field. Each field is associated with each other.

In the "Evaluation" field, an evaluation message indicating an evaluation corresponding to each of the speed score, the posture score, and the technical score is stored.

(3-4) Solution Master Database The solution master database of this embodiment is described. Fig. 7 is a view showing the data structure of the solution master database of the present embodiment.

In the solution master database of Figure 7, the solution information corresponding to the score is stored.
The solution master database includes the "Score" field and the "Solutions" field. Each field is associated with each other.

In the "Solutions" field, store the solution information corresponding to the combination of the activity's grace score, speed score, posture score, and technical score.
The "Resolution" field includes the "Recommended" field and the "Recommended Items" field.

In the "Recommendations" field, store a suggestion message indicating recommendations related to lifestyle. Living habits include, for example, the following.
・Sports, diet, sleep

In the "Recommended Items" field, store product information related to the product (for example, the product name, the URL of the website used to purchase the product (Uniform Resource Locator), or a combination thereof). Goods include, for example, the following.
・Cosmetics, sports equipment, food, and supplements

(3-5) Score log information database The score log information database of the present embodiment will be described. Fig. 8 is a view showing the structure of the data of the score log information database of the present embodiment.

The score log information is stored in the score log information database of FIG.
The score log information database includes the "Score Log ID" field, the "Date" field, and the "Score" field. Each field is associated with each other.
The score log information database is associated with the subject ID.

In the "Score Log ID" field, the score log ID of the recognition score log is stored. The score log ID is arbitrarily determined by the server 30.

In the "Date" field, store information related to the date the score log was obtained.

The "Score" field includes the "Speed Score" field, the "Pose Score" field, the "Technical Score" field, and the "Score of Activity Rating" field.

In the "Speed" field, store the speed score.

In the "Pose Score" field, the posture score is stored.

In the "Technical Score" field, store the technical score.

In the "Scoring of the Grace of Activity" field, the score of the gracefulness of the event is stored.

(4) Information Processing The information processing of this embodiment will be described. Figure 9 is a sequence diagram of information processing in an embodiment. Fig. 10 is a view showing an example of a screen displayed in the information processing of Fig. 9. Figure 11 is a flow chart showing the details of the score calculation of Figure 9.

As shown in FIG. 9, the client device 10 performs acquisition of a moving image (S100).
Specifically, the processor 12 displays the screen P100 (FIG. 11) on the display.

As shown in FIG. 9, the screen P100 includes button objects B100a to B100b, an input field object F100, and an image object IMG100.
The input field object F100 is an object that accepts the input of the object ID of the subject OBJ.
The button object B100a is an object for accepting a user instruction for recording of a moving image.
The button object B100b is an object that accepts a user's instruction for requesting an evaluation of the grace of the activity.
The image object IMG 100 corresponds to a moving image captured by the camera 15 .

If the user of the client device 10 operates the button object B 100a, the processor 12 causes the camera 15 to start.
The camera 15 captures a moving image of the subject OBJ while walking, and generates moving image data of the captured moving image.

After step S100, the client device 10 performs an evaluation request (S101).
Specifically, if the user operates the button object B100b (FIG. 9), the processor 12 transmits the evaluation request data to the server 30.
The evaluation request information includes the following information.
・Subject ID
- The moving image data generated in step S100 and the information related to the execution date in step S101

After step S101, the server 30 performs calculation of the score based on the moving image data included in the evaluation request material (S300).
Step S300 will be described with reference to Fig. 11 .

As shown in FIG. 11, the server 30 performs calculation of the speed parameter (S3000).
Specifically, the processor 32 specifies a pixel (for example, a foot) that is strongly associated with the walking speed by performing feature value analysis on the moving image data included in the evaluation request data (hereinafter referred to as " The first reference pixel ").
The processor 12 calculates the amount of change in the coordinates of the first reference pixel in the plurality of frames constituting the moving image data. This variation is a speed parameter related to the walking speed.

After step S3000, the server 30 performs calculation of the posture parameters (S3001).
Specifically, the processor 32 specifies a part that is strongly associated with the walking posture by performing feature value analysis on the moving image data included in the evaluation request data (for example, the spine, the trunk, the pelvis, and the entire body). At least one of the pixels (hereinafter referred to as "second reference pixel").
The processor 32 refers to the second reference pixel and calculates the forward tilt angle of the portion. The forward tilt angle is a posture parameter related to the walking posture.
The forward tilt angle includes at least one of the following angles.
The angle of inclination of the cervical vertebra relative to the vertical line is inclined relative to the vertical line. The angle of the pelvis is relative to the horizontal line. The angle of inclination of the whole body relative to the vertical line is the angle of the hip joint (for example, at least one of the movable angle and the bending angle)
Angle of the foot joint (eg, at least one of a movable angle and a bending angle)

After step S3001, the server 30 performs calculation of the technical parameters (S3002).
Specifically, the processor 32 specifies a pixel of a portion (for example, the entire body) that is strongly associated with the walking motion by performing feature value analysis on the moving image data included in the evaluation request data (hereinafter referred to as "3rd reference pixel").
The processor 32 calculates the frequency of the displacement of the third reference pixel (hereinafter referred to as "active frequency") in the plurality of frames constituting the moving image data. This activity frequency is a technical parameter related to walking techniques, especially the smoothness of walking.

After step S3002, the server 30 performs a decision of the calculation formula (S3003).
Specifically, the processor 32 refers to the subject information master library (FIG. 4), and specifies the subject attribute information associated with the subject ID included in the evaluation request material.
The processor 32 refers to the calculation master data library (FIG. 5), and specifies a calculation formula (first calculation formula to fourth calculation formula) associated with the specified subject attribute information.

After step S3003, the server 30 performs calculation of the speed score (S3004).
Specifically, the processor 32 applies the parameters (the speed parameter p1, the posture parameter p2, and the technical parameter p3) calculated in steps S3000 to S3002 to the first calculation formula (Formula 1) specified in step S3003. And calculate the speed score S1.

After step S3004, the server 30 performs calculation of the posture score (S3005).
Specifically, the processor 32 applies the parameters (speed parameter p1, posture parameter p2, and technical parameter p3) calculated in steps S3000 to S3002 to the second calculation formula (formula 2) specified in step S3003. And calculate the posture score S2.

After step S3005, the server 30 performs calculation of the technical score (S3006).
Specifically, the processor 32 applies the parameters (speed parameter p1, posture parameter p2, and technical parameter p3) calculated in steps S3000 to S3002 to the third calculation formula (formula 3) specified in step S3003. And the calculation technique scores S3.

After step S3006, the server 30 performs calculation of the score of the grace of the activity (S3007).
Specifically, the processor 32 applies the score (speed score S1, posture score S2, and technical score S3) calculated in steps S3004 to S3006 to the fourth calculation formula (Expression 4) specified in step S3003. And calculate the score Sm of the gracefulness of the activity.

As shown in FIG. 9, after step S300, the server 30 performs update of the database (S301).
Specifically, the processor 32 adds a new record to the evaluation log information database (FIG. 8) associated with the subject ID included in the evaluation request material.
Processor 32 stores the following information in each field of the new record.
• Store the new score log ID in the "Score Log ID" field.
・In the "Date" field, the information related to the execution date contained in the evaluation request data is stored.
・ The speed score S1 calculated in step S3004 is stored in the "speed score" field.
・ The posture score S2 calculated in step S3005 is stored in the "posture score" field.
・ In the "Technical Score" field, the technical score S3 calculated in step S3006 is stored.
・In the "Activity Grace Score" field, the score Sm of the grace level of the activity calculated in step S3007 is stored.

After step S301, the server 30 performs evaluation (S302).
Specifically, the processor 32 refers to the evaluation master database (FIG. 6), and specifies the information (evaluation message) stored in the "evaluation" field associated with each of the scores calculated in steps S3004 to S3007.

After step S302, the server 30 performs the specificity of the solution information (S303).
Specifically, the processor 32 refers to the solution master database (FIG. 7), and specifies the information stored in the "solution" field associated with each of the scores calculated in steps S3004 to S3007 (recommendation message and Product information).

After step S303, the server 30 performs an evaluation response (S304).
Specifically, the processor 32 transmits the evaluation response data to the client device 10.
The assessment response information includes the following information.
・The score obtained in step S300 (speed score S1, posture score S2, technical score S3, and score of activity grace Sm)
・Evaluation message specified in step S302 and solution information (suggested message and product information) specified in step S303

After step S304, the client device 10 performs screen display (S102).
Specifically, the processor 12 displays a screen P102 (FIG. 10) based on the evaluation response data on the display.

As shown in FIG. 10, the screen P102 includes display objects A101a to A101b.
The display object A101a includes a suggestion message included in the evaluation response data.
The display object A 101b includes the solution information included in the evaluation response data.

According to the present embodiment, the score Sm of the gracefulness of the activity is calculated using the parameters extracted from the specific portion included in the moving image (specifically, the portion having a strong correlation with the walking speed, the walking posture, and the walking technique). Thereby, the gracefulness of the activity can be evaluated based on the walking action.

(5) A summary of this embodiment summarizes this embodiment.

The first aspect of the embodiment is an information processing device.
It is an information processing device (for example, the server 30) that evaluates the gracefulness of the activity of the subject, and has:
a mechanism for acquiring a moving image of the subject being walked (for example, the processor 32 performing the processing of step S300),
a mechanism for extracting a walking speed, a walking posture, and an activity frequency by analyzing the moving image (for example, the processor 32 executing the processing of step S300),
a mechanism for calculating the first parameter p1 based on the correlation between the walking speed and the grace level (for example, the processor 32 performing the processing of step S3000),
a mechanism for calculating the second parameter p2 based on the association between the walking posture and the grace level (for example, the processor 32 executing the processing of step S3001),
A mechanism for calculating the third parameter p3 based on the correlation between the activity frequency and the grace level (for example, the processor 32 performing the processing of step S3002) and the mechanism for calculating the score Sm of the grace of the activity using the first parameter p1 to the third parameter p3 (For example, the processor 32 that performs the processing of step S3007).

According to the first aspect, the score Sm of the grace of the activity is calculated using the first to third parameters extracted by analyzing the moving image of the subject being walked. Thereby, the gracefulness of the activity can be evaluated based on the walking action.

A second aspect of the present embodiment is an information processing apparatus comprising:
A mechanism for calculating the first score S1 related to the mental state of the subject using the first parameter p1 to the third parameter p3 and the first weighting coefficient related to the walking speed (for example, the processor 32 executing the processing of step S3004).

According to the second aspect, the first score S1 related to the psychological state of the subject can be obtained by using the first parameter to the third parameter and the first weighting coefficient related to the walking speed associated with the mental state.

A third aspect of the present embodiment is an information processing apparatus comprising:
A mechanism for calculating the second score S2 related to the body composition of the subject using the first parameter p1 to the third parameter p3 and the second weighting coefficient related to the walking posture (for example, the processor 32 executing the processing of step S3005).

According to the third aspect, the second score S2 related to the body composition of the subject can be obtained by using the first parameter to the third parameter and the second weighting coefficient related to the walking posture associated with the body composition.

A fourth aspect of the present embodiment is an information processing apparatus comprising:
A mechanism for calculating the third score S3 related to the motion control of the subject using the first parameter p1 to the third parameter p3 and the third weighting coefficient related to the walking technique (for example, the processor 32 executing the processing of step S3006).

According to the fourth aspect, the third score S3 related to the motion control of the subject can be obtained by using the first to third parameters and the second weighting coefficient related to the walking technique associated with the motion control.

A fifth aspect of the present embodiment is an information processing apparatus comprising:
A mechanism prompting at least one of the calculated scores (for example, the processor 32 performing the processing of step S304).

According to the fifth aspect, the user can be made aware of the score.

A sixth aspect of the present embodiment is an information processing apparatus comprising:
An institution that prompts solution information corresponding to at least one of the calculated scores (for example, the processor 32 that performs the processing of step S304).

According to the sixth aspect, it is possible to provide the user with information useful for the solution.

A seventh aspect of the present embodiment is an information processing apparatus, wherein the solution information includes a recommendation relating to at least one of an appropriate lifestyle and an appropriate commodity.

According to the seventh aspect, it is possible to provide the user with information useful for at least one of appropriate living habits and appropriate commodities.

The eighth aspect of the present embodiment is an information processing apparatus which is provided with a calculation formula (Expression 4) for correlating the subject attribute information relating to the attribute of the subject with the score Sm of the grace of the activity, and memorizing a mechanism (for example, the memory device 31), and the acquisition mechanism further acquires object attribute information of the subject,
The calculation means uses the score Sm of the grace degree of the calculation calculation activity associated with the acquired subject attribute information.

According to the eighth aspect, since the calculation formula corresponding to the attribute of the subject is used, a high-precision score in consideration of the subject attribute can be obtained.

The ninth aspect of the present embodiment is an information processing apparatus comprising:
A mechanism that recognizes the object recognition information of the subject and at least one of the calculated scores (for example, the processor 32 that performs the processing of step S301).

According to the ninth aspect, since the subject identification information is associated with the score, the log of the score can be saved.

The tenth aspect of the present embodiment is a program for causing a computer (for example, the processor 32) to function as each of the above mechanisms.

(6) Other variations

The memory device 11 can also be connected to the client device 10 via the network NW. The memory device 31 can also be connected to the server 30 via the network NW.

The steps of the above information processing can be performed by either the client device 10 or the server 30.

In the present embodiment, an example of the server 30 that performs information processing (FIG. 9) based on the moving image data acquired by the client device 10 in step S100 is shown. However, the embodiment is not limited to this.
The server 30 of the present embodiment can also perform information processing based on the moving image data stored in the memory device 31 (FIG. 9). In this case, step S100 is omitted.

In the present embodiment, the posture parameter includes at least one of a cervical vertebra forward angle with respect to the perpendicular, a forward angle of the trunk relative to the perpendicular, a front oblique angle of the pelvis with respect to the horizontal line, and an angle of inclination of the entire body with respect to the vertical. An example of the person. However, the posture parameter of the present embodiment is not limited to this.
The posture parameter may also include at least one of the following.
・The angle of the hip joint (at least one of the movable angle and the bending angle)
・The angle of the knee (at least one of the movable angle and the bending angle)
・Step size

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to the above embodiments. Further, the above-described embodiments can be variously modified or changed without departing from the spirit and scope of the invention. Further, the above embodiments and modifications can be combined.

1‧‧‧Information Processing System

10‧‧‧Client device

11‧‧‧ memory device

12‧‧‧ Processor

13‧‧‧Input and output interface

14‧‧‧Communication interface

15‧‧‧ camera

30‧‧‧Server

31‧‧‧ memory device

32‧‧‧ processor

33‧‧‧Input and output interface

34‧‧‧Communication interface

A101a‧‧‧Display object

A101b‧‧‧Display object

B100a‧‧‧ button object

B100b‧‧‧ button object

F100‧‧‧Input field object

IMG100‧‧‧Image Object

NW‧‧‧Network

OBJ‧‧‧ Subject

P100‧‧‧ screen

P101‧‧‧ screen

P102‧‧‧ screen

S1‧‧‧ speed score

S2‧‧‧ pose score

S3‧‧‧Technical score

S100~S102‧‧‧Steps

S300~S304‧‧‧Steps

S3000~S3007‧‧‧Steps

Sm‧‧‧Sports score

Fig. 1 is a schematic view showing an information processing system of the embodiment.

Figure 2 is a block diagram showing the construction of the information processing system of Figure 1.

Fig. 3 is an explanatory view showing an outline of the embodiment.

Fig. 4 is a view showing the data structure of the subject information database of the present embodiment.

Fig. 5 is a view showing the data structure of the calculation type master data library of the present embodiment.

Fig. 6 is a view showing the data structure of the evaluation master database of the present embodiment.

Fig. 7 is a view showing the data structure of the solution master database of the present embodiment.

Fig. 8 is a view showing the structure of the data of the score log information database of the present embodiment.

Figure 9 is a sequence diagram of information processing in an embodiment.

Fig. 10 is a view showing an example of a screen displayed in the information processing of Fig. 9.

Figure 11 is a flow chart showing the details of the score calculation of Figure 9.

Claims (10)

An information processing device that evaluates the gracefulness of an activity of a subject and has the following: a mechanism for obtaining a moving image of a subject being walked; a mechanism for extracting walking speed, walking posture, and activity frequency by analyzing the moving image; a mechanism for calculating the first parameter based on the correlation between the walking speed and the grace level; a mechanism for calculating the second parameter based on the association between the walking posture and the grace level; a mechanism for calculating the third parameter based on the correlation between the activity frequency and the grace level; and A mechanism for calculating the score of the grace of the activity using the first parameter to the third parameter described above. The information processing device of claim 1, comprising: calculating the first score related to the psychological state of the subject using the first parameter to the third parameter and the first weighting coefficient related to the walking speed; mechanism. The information processing device according to claim 1 or 2, comprising: calculating the second body related to the body composition of the subject using the first parameter to the third parameter and the second weighting coefficient related to the walking posture The institution that scores. The information processing device according to any one of claims 1 to 3, wherein the motion control of the subject is calculated using the first parameter to the third parameter and a third weighting coefficient related to the walking technique The relevant third score agency. The information processing apparatus according to any one of claims 1 to 4, further comprising means for presenting at least one of the calculated scores. The information processing apparatus according to any one of claims 1 to 5, further comprising means for presenting solution information corresponding to at least one of the calculated scores. The information processing apparatus of claim 6, wherein the solution information includes a recommendation relating to at least one of an appropriate lifestyle and an appropriate commodity. The information processing device according to any one of claims 1 to 7, further comprising means for associating and storing a calculation formula of a subject attribute information relating to an attribute of the subject and a score of the grace of the activity, and The acquiring mechanism further acquires object attribute information of the object, The calculation unit calculates a score of the grace of the activity by using a calculation formula associated with the acquired subject attribute information. The information processing device according to any one of claims 1 to 8, further comprising means for associating the object identification information identifying the subject with at least one of the calculated scores. A program for causing a computer to function as each of the mechanisms of any one of claims 1 to 9.