Patent Publication Number: US-2023162458-A1

Title: Information processing apparatus, information processing method, and program

Description:
TECHNICAL FIELD 
     The present disclosure relates to an information processing apparatus, an information processing method, and a program, and more particularly, to an information processing apparatus, an information processing method, and a program capable of providing more effective learning content in learning motion of a body. 
     BACKGROUND ART 
     Conventionally, there is a technology in which a video image captured a state of an instructor performing exercise such as aerobics, yoga, or dance and a video image captured a state of a user performing exercise are displayed side by side, so that the user can easily learn the exercise of the instructor. 
     Furthermore, in recent years, athletes exercise wearing devices capable of receiving various types of information externally via a network. For example, Patent Literature 1 discloses a technique in which, at a place where one athlete is exercising, virtual objects of other athletes who have exercised in the past at the place are superimposed and displayed on a display unit showing the surroundings. 
     CITATION LIST 
     Patent Document 
     
         
         Patent Document 1: Japanese Patent Application Laid-Open No. 2013-167941 
       
    
     SUMMARY OF THE INVENTION 
     Problems to be Solved by the Invention 
     By the way, if the video in which the instructor is exercising and the video in which the user is exercising can be displayed in a superimposed manner, the user can learn the movement of the instructor more accurately. 
     The present disclosure has been made in view of such a situation, and an object of the present disclosure is to provide more effective learning content in learning movement of a body. 
     Solutions to Problems 
     An information processing apparatus according to the present disclosure includes an adjustment unit configured to generate an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     An information processing method according to the present disclosure is an information processing method including: by an information processing apparatus, generating an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     A program according to the present disclosure is a program causing a computer to execute processing of generating an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     According to the present disclosure, an adjusted second virtual object is generated by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a diagram illustrating an example of an outline of an information processing system to which a technology according to the present disclosure is applied. 
         FIG.  2    is a diagram illustrating an example of a superimposed video. 
         FIG.  3    is a diagram illustrating an example of a superimposed video. 
         FIG.  4    is a diagram for describing a use case to which a digital twin is applicable. 
         FIG.  5    is a block diagram illustrating a functional configuration example of an information processing system. 
         FIG.  6    is a diagram for explaining details of a digital twin generation unit. 
         FIG.  7    is a diagram for explaining details of an instruction information generation unit. 
         FIG.  8    is a diagram for explaining details of a digital twin adjustment unit. 
         FIG.  9    is a diagram for explaining details of a superimposed video generation unit. 
         FIG.  10    is a diagram for explaining details of an evaluation unit. 
         FIG.  11    is a diagram for explaining details of an effect generation unit. 
         FIG.  12    is a flowchart for explaining an operation of a device on a teacher side. 
         FIG.  13    is a flowchart for explaining an operation of a device on a student side. 
         FIG.  14    is a flowchart for explaining an operation of a device on a teacher side. 
         FIG.  15    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  16    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  17    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  18    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  19    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  20    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  21    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  22    is a block diagram illustrating another functional configuration example of the information processing system. 
         FIG.  23    is a diagram for explaining details of a storage device. 
         FIG.  24    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  25    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  26    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  27    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  28    is a diagram illustrating an application example of 5G network slicing. 
         FIG.  29    is a diagram illustrating a display example of the digital twin. 
         FIG.  30    illustrates a presentation example of character information. 
         FIG.  31    illustrates a presentation example of character information. 
         FIG.  32    illustrates a presentation example of character information. 
         FIG.  33    is a block diagram illustrating a configuration example of a computer. 
     
    
    
     MODE FOR CARRYING OUT THE INVENTION 
     Embodiments for carrying out the present disclosure (hereinafter referred to as an embodiment) are now described. Moreover, the description is given in the following order. 
     1. Overview of technology according to present disclosure and use case 
     2. Configuration and operation of information processing system 
     3. Application example of 5G network slicing 
     4. Modifications 
     5. Configuration example of computer 
     &lt;1. Overview of Technology According to Present Disclosure and Use Case&gt; 
     (Overview of Information Processing System) 
       FIG.  1    is a diagram illustrating an example of an outline of an information processing system to which a technology according to the present disclosure is applied. 
     In the information processing system of  FIG.  1   , a reference digital twin, which is a virtual object reflecting the body motion, such as aerobics, yoga, and dance, of an instructor TE who is a reference person in a studio SU, is superimposed on a user digital twin, which is a virtual object reflecting the body motion of a user ST in a home HO, and is displayed on a device DE in the home HO. 
     In general, the digital twin refers to an object or an environment in a real space, information indicating a state of the object or the environment, or the like constructed and represented in real time in a virtual space, or a technology therefor. The digital twin in the present embodiment refers to a virtual object in which a skeleton, a body shape, and movement of a person in a real space are reflected in real time on a virtual space. Specifically, the digital twin is three-dimensionally modeled computer graphics (3DCG) of three-dimensional information of a person displayed on a virtual space. The digital twin is generated on the basis of sensor data acquired by sensing the instructor TE and the user ST by one or a plurality of sensors installed in the studio SU or the home HO. The digital twin may be drawn with the skeleton, body shape, and scale of the corresponding person as they are, or may be drawn with the skeleton, body shape, and scale adjusted for the purpose of protecting the privacy of the person. 
     Hereinafter, the reference digital twin of the instructor TE is referred to as a teacher digital twin, and the user digital twin of the user ST is referred to as a student digital twin as appropriate. 
     The user ST can learn the movement of the instructor TE more accurately by moving own body while watching the movement of the teacher digital twin superimposed on the student digital twin. 
     Furthermore, the instructor TE can give an instruction regarding the movement of the user ST to the user ST by viewing the movement of the student digital twin superimposed on the teacher digital twin in the studio SU. 
     The studio SU and the home HO may directly exchange (transmit and receive) information by wired communication or wireless communication, or may exchange (transmit and receive) information via a mobile edge computing (MEC) server  10  or a cloud server  20 . In a case where transmission and reception of information are performed by wireless communication, a communication system such as long term evolution (LTE), Wi-Fi (registered trademark), 4G, or 5G can be applied to a part or the whole of the wireless communication. 
     (Example of Superimposed Video) 
     An example of a superimposed video in which the teacher digital twin is superimposed on the student digital twin displayed on the device DE in the home HO will be described with reference to  FIGS.  2  and  3   . 
     In the state of the screen # 1  of  FIG.  2   , on a student digital twin  30 ST that is upright, a lattice-shaped teacher digital twin  30 TE, which is also upright, is superimposed. In the drawing, a button  41 , which is a graphical user interface (GUI) for starting a lesson by the instructor TE in the studio SU, is displayed on the upper right of the screen # 1 . 
     As illustrated in the state of the screen # 2 , if the user ST raises one hand and it is determined that the hand of the corresponding student digital twin  30 ST overlaps the area of the button  41 , the lesson by the instructor TE is started. Here, determination processing based on the positional relationship between the coordinates of the button  41  in the virtual space and the coordinates of the hand of the student digital twin  30 ST is performed. Therefore, even if the hand of the student digital twin  30 ST overlaps the area of the button  41  in front view as in the screen # 2 , the lesson is not started in a case where the hand of the student digital twin  30 ST is deviated from the area of the button  41  in the depth direction. 
     In the state of the screen # 3  of  FIG.  3   , the teacher digital twin  30 TE in which the instructor TE bends one knee from the upright state and stands on one leg so as to bend the corresponding knee and stand on one leg is displayed. Furthermore, an attention point (fitting point) indicating a body part to be moved in the exercise is superimposed and displayed on the teacher digital twin  30 TE and the student digital twin  30 ST. Specifically, the fitting points indicating the positions of the waist, the knee, and the heel in the state of standing on one leg of the teacher digital twin  30 TE and the fitting points indicating the positions of the waist, the knee, and the heel in the upright state (before standing on one leg) of the student digital twin  30 ST are displayed. 
     In this way, the movement of the user ST can be guided by displaying the fitting points of the teacher digital twin  30 TE and the student digital twin  30 ST. Note that, in addition to the fitting points, lines and figures that assist and guide the movement of the user ST may be superimposed and displayed on the teacher digital twin  30 TE and the student digital twin  30 ST. 
     In the state of the screen # 4 , the user ST stands on one leg in accordance with the movement of the teacher digital twin  30 TE, so that the fitting points of the student digital twin  30 ST match the fitting points of the teacher digital twin  30 TE. At this time, an effect video  43  that recommends to maintain the posture is displayed around (in the background of) the student digital twin  30 ST. Furthermore, an indicator  45  indicating the time during which the user ST (student digital twin  30 ST) maintains the posture is displayed on the upper left of the screen # 4 . 
     On the screens # 3  and # 4 , superimposed videos in a front view (the student digital twin  30 ST and the teacher digital twin  30 TE) are displayed, but superimposed videos at different viewpoints (angles) can also be displayed. As a result, the user ST can confirm the deviation from the movement of the instructor TE in more detail. 
     Furthermore, an effect video may be superimposed on a part (portion) where there is a difference in movement between the student digital twin  30 ST and the teacher digital twin  30 TE such that the part is highlighted. Further, on the contrary, an effect video may be superimposed on a part (portion) where movements are matched between the student digital twin  30 ST and the teacher digital twin  30 TE such that the part is highlighted. 
     When the exercise as shown in the screens # 3  and # 4  is repeated and the lesson ends, a pop-up  47  showing the result of the lesson is displayed as shown in the state of the screen # 5 . In the pop-up  47 , a matching rate of the motion is illustrated as the evaluation result of the exercise of the student digital twin  30 ST with respect to the teacher digital twin  30 TE. The evaluation result of the exercise is not limited to the matching rate, and the degree of achievement according to the level of the exercise or the like may be scored and indicated. 
     In this manner, the user ST can learn the exercise of the instructor TE and recognizes the degree of achievement of the user&#39;s own exercise while watching the superimposed video. 
     (Applicable Use Case) 
     Here, a use case to which the digital twin as described above can be applied will be described with reference to  FIG.  4   .  FIG.  4    illustrates five use cases UC 1  to UC 5 . 
     In the use case UC 1 , a digital twin reflecting the teacher&#39;s body motion in real time is applied as the teacher digital twin. Further, a digital twin reflecting the student&#39;s body motion in real time is applied as the student digital twin. 
     The use case UC 1  can be applied to, for example, a case in which an instructor who is a teacher handles classes such as aerobics, yoga, and dance in real time from a studio to a student who is a user at home (real-time studio class). Note that, in this use case, the teacher can handle a real-time class not only from the studio but also from home or any other space, and the same applies to the subsequent use cases. The use case UC 1  can be implemented by a system configuration including devices on a teacher side and a student side and the MEC server  10 . 
     In the use case UC 2 , as the teacher digital twin, a digital twin in which the teacher&#39;s body motion is reflected in real time or a digital twin in which the teacher&#39;s body motion reflected in video content captured in advance (recoded content) is reflected is applied. Further, a digital twin reflecting the student&#39;s body motion in real time is applied as the student digital twin. 
     Similarly to the use case UC 1 , the use case UC 2  can be applied to a real-time class such as aerobics, yoga, and dance. However, in the real-time class of the use case UC 2 , the teacher can proceed by switching between a case where the teacher performs in real time and a case where the teacher shows the video content (presents a digital twin based on the video content). Furthermore, the use case UC 2  can also be applied to, for example, a soccer school in which a professional soccer player teaches a junior-level player how to shoot (kick) or dribble. The use case UC 2  can be implemented by a system configuration including devices on a teacher side and a student side, the MEC server  10 , and the cloud server  20  capable of handling video content. 
     In the use case UC 3 , a digital twin reflecting the teacher&#39;s body motion in real time is applied as the teacher digital twin. Furthermore, as the student digital twin, a digital twin reflecting the body motion of the student appeared in the video content captured in advance is applied. 
     Similarly to the use case UC 1 , the use case UC 3  can also be applied to a real-time class such as aerobics, yoga, and dance. However, in the real-time class of the use case UC 3 , the teacher confirms the movement of the student digital twin based on the video content of the student, so that instruction information such as an instruction and advice for the video content of the student can be added in real time. The use case UC 3  can also be applied to, for example, a soccer school in which a professional soccer player teaches a junior-level player how to shoot or dribble. The use case UC 3  can be implemented by a system configuration including devices on the teacher side and the student side, the MEC server  10 , and the cloud server  20  capable of handling video content. 
     In the use case UC 4 , as the teacher digital twin, a digital twin in which the teacher&#39;s body motion is reflected in real time or a digital twin in which the teacher&#39;s body motion reflected in video content captured in advance is reflected is applied. Furthermore, as the student digital twin, a digital twin reflecting the body motion of the student appeared in the video content captured in advance is applied. 
     Similarly to the use case UC 1 , the use case UC 4  can also be applied to a real-time class such as aerobics, yoga, and dance. However, in the real-time class of the use case UC 3 , the teacher can proceed by switching a case where instruction information such as an instruction or advice for the video content of the student is added and a case where the video content is shown in real time. The use case UC 4  can also be applied to, for example, a soccer school in which a professional soccer player teaches a junior-level player how to shoot or dribble. The use case UC 4  can be implemented by a system configuration including devices on the teacher side and the student side, the MEC server  10 , and the cloud server  20  capable of handling video content. 
     In the use case UC 5 , as both the teacher digital twin and the student digital twin, a digital twin reflecting the body motion of the student appeared in the video content captured in advance is applied. 
     The use case UC 5  can be applied to, for example, self-conditioning of golf (confirmation of an action such as a swing performed by oneself). Specifically, the student can confirm the action by oneself by superimposing the digital twin based on the current video content on the digital twin based on own past video content as a model (treating the digital twin based on the past video content as the teacher digital twin). The use case UC 5  can also be applied to, for example, self-conditioning of shooting and dribbling for a professional soccer player. The use case UC 5  can be implemented by a system configuration including devices on the student side, the MEC server  10 , and the cloud server  20  capable of handling video content. 
     &lt;2. Configuration and Operation of Information Processing System&gt; 
     Hereinafter, a specific configuration and operation of an information processing system to which the technology according to the present disclosure is applied will be described. 
     (Configuration Example of Information Processing System) 
       FIG.  5    is a block diagram illustrating a configuration example of an information processing system to which the technology according to the present disclosure is applied. 
     The information processing system in  FIG.  5    includes a device  100  on the teacher side and a device  200  on the student side. In the example of  FIG.  5   , the device  100  on the teacher side and the device  200  on the student side are configured to directly communicate with each other, but may also communicate via the MEC server  10  or the cloud server  20 . 
     The device  100  on the teacher side is installed in a space such as a studio or a house where a teacher (an instructor or the like) is located. 
     On the other hand, the device  200  on the student side is installed in a space such as a studio or a house where a student (user) is located. 
     In a case where the device  100  on the teacher side and the device  200  on the student side are installed in a wide space such as a studio, for example, they are configured as a relatively large device (or system) such as a device having a booth type housing surrounding the periphery of a person or a device having a whole-body mirror type display surface in which the entire body of the person is reflected. On the other hand, in a case where the device  100  on the teacher side and the device  200  on the student side are installed in a narrow space such as a home, for example, they are configured as a small-scale device (or system) such as a smartphone including various sensors or a display connectable to the smartphone. Note that the device  100  on the teacher side and the device  200  on the student side may be configured as devices (or systems) of the same scale. 
     The device  100  on the teacher side includes a display unit  110 , an operation unit  120 , a storage unit  130 , a communication unit  140 , a sensor unit  150 , and a control unit  160 . 
     The display unit  110  includes a liquid crystal display, an organic electro-luminescence (EL) display, or the like, and displays the digital twin and various types of information on the basis of the control of the control unit  160 . 
     The operation unit  120  includes a touch panel integrated with a display constituting the display unit  110 , a physical button provided on a housing of the device  100 , a microphone, and the like. The operation unit  120  receives an operation by the teacher and supplies operation information corresponding to the operation to the control unit  160 . 
     The storage unit  130  stores programs necessary for operating the device  100 , various data set in advance by the teacher and desired to be used in the lesson, and the like. 
     The communication unit  140  includes a network interface and the like, and communicates with the device  200  on the student side on the basis of the control of the control unit  160 . 
     The sensor unit  150  includes one or a plurality of sensors, and supplies various sensor data acquired by sensing the body motion of the teacher to the control unit  160 . 
     For example, the sensor unit  150  includes one or a plurality of time of flight (ToF) sensors and an RGB sensors. The control unit  160  generates the teacher digital twin on the basis of the ToF data acquired by the ToF sensor and the RGB data (video data) acquired by the RGB sensor. In a case where the sensor unit  150  includes a plurality of ToF sensors and RGB sensors, the control unit  160  can also generate the teacher digital twin on the basis of the volumetric capture data generated by the volumetric capture using the acquired sensor data. The sensor unit  150  may include various sensors capable of acquiring sensor data other than ToF data and RGB data. 
     The control unit  160  executes various processing on the basis of a program stored in the storage unit  130 , operation information from the operation unit  120 , and information acquired via the communication unit  140 . 
     The control unit  160  includes a digital twin generation unit  161  and an instruction information generation unit  162 . Each functional unit included in the control unit  160  is implemented by executing a program stored in the storage unit  130 . 
     Meanwhile, the device  200  on the student side includes a display unit  210 , an operation unit  220 , a storage unit  230 , a communication unit  240 , a sensor unit  250 , and a control unit  260 . 
     The display unit  210  includes a liquid crystal display, an organic EL display, or the like, and displays the digital twin and various types of information on the basis of the control of the control unit  260 . 
     The operation unit  220  includes a touch panel integrated with a display constituting the display unit  210 , a physical button provided on a housing of the device  200 , a microphone, and the like. The operation unit  220  receives an operation by the student and supplies operation information corresponding to the operation to the control unit  260 . 
     The storage unit  230  stores programs necessary for operating the device  200 , various data prepared in advance by the student, and the like. 
     The communication unit  240  includes a network interface and the like, and communicates with the device  100  on the teacher side on the basis of the control of the control unit  260 . 
     The sensor unit  250  includes a plurality of sensors, and supplies various sensor data acquired by sensing the body motion of the student to the control unit  260 . 
     Specifically, the sensor unit  250  includes one or a plurality of ToF sensors and an RGB sensors. The sensor unit  250  of the device  200  on the student side may be configured similarly to the sensor included in the device  100  on the teacher side, or may be calibrated from a sensor with a different number or type from the sensor included in the device  100  on the teacher side. 
     The control unit  260  executes various processing on the basis of a program stored in the storage unit  230 , operation information from the operation unit  220 , and information acquired via the communication unit  240 . 
     The control unit  260  includes a digital twin generation unit  261 , a digital twin adjustment unit  262 , a superimposed video generation unit  263 , an evaluation unit  264 , an effect generation unit  265 , and a display control unit  266 . Each functional unit included in the control unit  260  is implemented by executing a program stored in the storage unit  230 . 
     As illustrated in  FIG.  5   , each functional unit included in the control unit  160  of the device  100  on the teacher side and each functional unit included in the control unit  260  of the device  200  on the student side execute each processing by transmitting and receiving information to and from each other as indicated by arrows in the figure. In  FIG.  5   , the information corresponding to the dashed arrows is actually transmitted and received via the communication unit  140  of the device  100  on the teacher side and the communication unit  240  of the device  200  on the student side. 
     Hereinafter, details of each functional unit included in the device  100  (the control unit  160 ) on the teacher side and each functional unit included in the device  200  (the control unit  260 ) on the student side will be described. 
     (Details of Digital Twin Generation Unit) 
       FIG.  6    is a diagram for explaining details of the digital twin generation unit  161  of the device  100  on the teacher side and the digital twin generation unit  261  of the device  200  on the student side. 
     Note that the digital twin generation unit  161  of the device  100  on the teacher side and the digital twin generation unit  261  of the device  200  on the student side are configured in a similar manner, and thus will be described as a digital twin generation unit N 61  as illustrated in  FIG.  6   . Furthermore, the sensor unit  150  of the device  100  on the teacher side and the sensor unit  250  of the device  200  on the student side will be similarly described as the sensor unit N 50 . 
     The digital twin generation unit N 61  generates, on the basis of a body motion of a person, a virtual object that performs a body motion similar to that of the person, that is, a digital twin reflecting the body motion of the person. The digital twin generation unit N 61  includes a feature point extraction unit N 71 , a background processing unit N 72 , and a 3D model generation unit N 73 . 
     On the basis of the sensor data from the sensor unit N 50 , the feature point extraction unit N 71  extracts, as feature point information of the person, skeleton information indicating a skeleton and joint points of the person (teacher or student), three-dimensional contour information indicating a three-dimensional contour of the person, and acceleration information indicating a motion of a body of the person. The feature point information is set as data on a time axis that continuously changes with time. 
     The skeleton information is extracted, for example, by performing skeleton estimation using machine learning or the like. The skeleton estimation may be performed using only one of the ToF data and the RGB data, or may be performed using both the ToF data and the RGB data. 
     The three-dimensional contour information is extracted on the basis of, for example, a depth image including ToF data. 
     The acceleration information is calculated on the basis of, for example, displacements of the skeleton and the joint points indicated by the skeleton information. In a case where the person wears an acceleration sensor as one of the sensor units N 50  on each part of the body, the acceleration information may be acquired on the basis of the sensor data from the acceleration sensor. The acceleration information also includes left and right information indicating which any of the body parts (hands, arms, legs, etc.) on the left and right side is moving. 
     These pieces of feature point information are supplied to the background processing unit N 72  together with RGB data (video data). 
     The background processing unit N 72  removes the background of the person in the video data on the basis of the feature point information from the feature point extracting unit N 71  and the video data. The video data from which the background has been removed is supplied to the 3D model generation unit N 73  together with the feature point information. 
     The 3D model generation unit N 73  generates a digital twin of the person on the basis of the video data from which the background has been removed and the feature point information from the background processing unit N 72 . 
     First, the 3D model generation unit N 73  models a target person on the basis of the three-dimensional contour information to create a three-dimensional model (3D model). Next, the 3D model generation unit N 73  associates the skeleton and the joint points indicated by the skeleton information with the created 3D model. As a result, the body motion of the person can be reflected in the 3D model. Then, the 3D model generation unit N 73  synthesizes skin data corresponding to human skin with the 3D model. 
     As the skin data, skin data having different visual texture is prepared for each purpose of body motion of the person. The purpose of the body motion includes, for example, aerobics, yoga, dance, golf, soccer, and the like, and is selected in advance by a teacher or a student. In addition, the purpose of the body motion is not limited to the sports described above, and may include artistic creation activities such as playing a musical instrument such as a guitar or a piano, and operating a potter&#39;s wheel in porcelain. 
     Then, the 3D model generation unit N 73  synthesizes skin data corresponding to the selected purpose of the body motion with respect to the 3D model, thereby generating a digital twin of a type corresponding to the purpose. For example, in a case where soccer is selected as the purpose of the body motion, the digital twin for soccer is generated by synthesizing the skin data for soccer with respect to the 3D model. At this time, for the generated digital twin, meta-information indicating the purpose of the body motion (for example, soccer) may be stored in association with the sensor data. 
     As described above, the digital twin generation unit N 61  extracts the feature point information on the basis of the sensor data, and generates a digital twin as a 3D model on the basis of the extracted feature point information. The feature point information extracted on the basis of the sensor data is added to the generated digital twin and output to the subsequent stage. 
     (Details of Instruction Information Generation Unit) 
       FIG.  7    is a diagram illustrating details of the instruction information generation unit  162  of the device  100  on the teacher side. 
     The instruction information generation unit  162  generates instruction information indicating an instruction or the like for the student on the basis of the operation information corresponding to the operation of the operation unit  120  by the teacher and supplies the instruction information to the display control unit  266  of the device  200  on the student side. 
     The operation information here includes, for example, setting information for setting a GUI such as the button  41  illustrated in the screens # 1  and # 2  of  FIG.  2   , and setting information for setting fitting points illustrated in the screen # 3  of  FIG.  3   . That is, the teacher can set the GUI and the fitting point displayed on the display unit  210  of the device  200  on the student side by operating the operation unit  120 . 
     In this case, the instruction information generation unit  162  generates display information for displaying a GUI or a fitting point as illustrated in  FIG.  2    as the instruction information on the basis of the operation information (setting information). Such display information may be generated, for example, on the basis of display data stored in the storage unit  130  or on the basis of display data acquired via the communication unit  140 . 
     Furthermore, the instruction information generation unit  162  may generate the instruction information on the basis of the evaluation value from the evaluation unit  264  of the device  200  on the student side. The evaluation value indicates, for example, an evaluation result (such as a matching rate of motion) of a lesson illustrated in a pop-up  47  on the screen # 5  in  FIG.  3   , and a comment corresponding to the evaluation value is automatically generated as the instruction information. This comment may be prepared in advance for each evaluation value, and a comment corresponding to the evaluation value may be selected. The comment generated as the instruction information may be integrated with the comment input by the teacher as the operation information corresponding to the operation of the operation unit  120 . Note that there is a possibility that the teacher cannot input an appropriate comment only with the evaluation result such as the matching rate of the motion. Therefore, the instruction information generation unit  162  may generate the instruction information or receive the input of the comment by the teacher on the basis of the superimposed video or the effect video from the device  200  on the student side or the single student digital twin or the RGB data (video data) of the student. 
     These pieces of instruction information are displayed on the display unit  210  on the device  200  on the student side under the control of the display control unit  266 . 
     (Details of Digital Twin Adjustment Unit) 
       FIG.  8    is a diagram for explaining details of the digital twin adjustment unit  262  of the device  200  on the student side. 
     The digital twin adjustment unit  262  generates an adjusted teacher digital twin (adjusted reference digital twin) by adjusting the teacher digital twin from the digital twin generation unit  161  to be superimposed with the student digital twin from the digital twin generation unit  261 . The generated adjusted teacher digital twin is supplied to the superimposed video generation unit  263  and the evaluation unit  264 . 
     Here, the teacher digital twin is adjusted on the basis of the student digital twin so that the teacher digital twin is matched to the student digital twin so that the student who is the user can compare the movement of the student and the movement of the teacher who is the instructor and easily copy the teacher&#39;s movement. 
     Specifically, the digital twin adjustment unit  262  changes the feature point information of the teacher included in the teacher digital twin so as to be close to the feature point information of the student on the basis of the feature point information of the student included in the student digital twin. 
     For example, the size (scale) of the teacher digital twin is adjusted by changing the skeleton information of the teacher digital twin in accordance with the skeleton information of the student digital twin. The left and right information of the teacher digital twin is changed in accordance with the left and right information of the student digital twin, so that the dominant arm and the dominant leg of the teacher digital twin are adjusted. The three-dimensional contour information of the teacher digital twin is changed in accordance with the three-dimensional contour information of the student digital twin, whereby the body shape of the teacher digital twin is adjusted. 
     Then, the digital twin adjustment unit  262  creates the 3D model on the basis of the changed feature point information of the teacher, thereby generating the adjusted teacher digital twin including the adjusted feature point information as the adjusted 3D model. The digital twin adjustment unit  262  can generate an adjusted teacher digital twin in a similar manner to the digital twin generation unit N 61  in  FIG.  6   . 
     (Details of Superimposed Video Generation Unit) 
       FIG.  9    is a diagram for explaining details of the superimposed video generation unit  263  of the device  200  on the student side. 
     The superimposed video generation unit  263  generates a superimposed video obtained by superimposing the student digital twin from the digital twin generation unit  261  on the adjusted teacher digital twin from the digital twin adjustment unit  262 , and supplies the generated superimposed video to the effect generation unit  265  and the display control unit  266 . 
     Specifically, the superimposed video generation unit  263  maps the adjusted teacher digital twin and the student digital twin to a predetermined reference position on the virtual space, and generates the superimposed video by synchronizing them at a predetermined reference time. 
     The superimposed video is displayed on the display unit  210  under the control of the display control unit  266 . 
     (Details of Evaluation Unit) 
       FIG.  10    is a diagram for explaining details of the evaluation unit  264  of the device  200  on the student side. 
     The evaluation unit  264  calculates an evaluation value of the student digital twin (that is, the body motion of the student) by comparing the student digital twin from the digital twin generation unit  261  with the adjusted teacher digital twin from the digital twin adjustment unit  262 . 
     For example, the evaluation unit  264  obtains a difference in the contour information (deviation in posture) between the student digital twin and the adjusted teacher digital twin as the evaluation value. Further, the evaluation unit  264  obtains a difference in the acceleration information (deviation in movement) between the student digital twin and the adjusted teacher digital twin as the evaluation value. Furthermore, the evaluation unit  264  obtains a difference in the fitting points (deviation in posture) between the student digital twin and the adjusted teacher digital twin as the evaluation value. 
     Among the evaluation values calculated in this manner, the 3D model information representing (visualizing) the difference by the 3D model is supplied to the effect generation unit  265 . In addition, among the calculated evaluation values, meta information (a deviation amount, a deviation part, or the like) obtained by converting the difference into a numerical value or a text is supplied to the display control unit  266  and the instruction information generation unit  162  (the device  100  on the teacher side). 
     (Details of Effect Generation Unit) 
       FIG.  11    is a diagram for explaining details of the effect generation unit  265  of the device  200  on the student side. 
     On the basis of the evaluation value (3D model information) from the evaluation unit  264 , the effect generation unit  265  generates an effect video for the superimposed video from the superimposed video generation unit  263 . The effect video is, for example, a video for highlighting a part (portion) deviated in the 3D model between the student digital twin and the adjusted teacher digital twin with a predetermined color or texture, a predetermined figure or pattern combined with the background of the student digital twin in a case where there is a deviation, and a line or an afterimage indicating a trajectory of the movement of the student digital twin or the adjusted teacher digital twin. 
     The effect generation unit  265  maps the effect video to a predetermined reference position on the virtual space, synchronizes the effect video at a predetermined reference time, superimposes the effect video on the superimposed video, and supplies the superimposed video to the display control unit  266 . 
     In the effect video, similarly to the skin data, effect videos having different visual textures are prepared for each purpose of the body motion of the person. That is, the effect generation unit  265  generates an effect video image of a type corresponding to the selected purpose of the body motion. For example, in a case where soccer is selected as the purpose of the body motion, a type of effect video corresponding to soccer is generated, and in a case where aerobics is selected as the purpose of the body motion, a type of effect video corresponding to aerobics is generated. 
     As described above, the display control unit  266  may cause the display unit  210  to display only the superimposed video from the superimposed video generation unit  263 , or may cause the display unit  210  to display the superimposed video on which the effect video is superimposed, from the effect generation unit  265 . 
     Furthermore, in a case where the effect video is displayed on the display unit  210 , the display control unit  266  can also switch the effect video displayed on the display unit  210  to an effect video or the like of another texture, for example, in accordance with an operation of the user (student). In this case, a plurality of types of effect videos having different textures is prepared for the purpose of one body motion. 
     (Operation of Information Processing System) 
     Next, operations of the device  100  on the teacher side and the device  200  on the student side included in the above-described information processing system will be described. 
       FIG.  12    is a flowchart for explaining an operation of the device  100  on the teacher side when the teacher is performing in a real-time class, for example. The processing of  FIG.  12    is executed, for example, in response to an instruction to start a lesson from a student. 
     In step S 11 , the digital twin generation unit  161  generates a teacher digital twin on the basis of sensor data of the teacher sensed by the sensor unit  150 . 
     In step S 12 , the control unit  160  controls the communication unit  140  to transmit the teacher digital twin generated by the digital twin generation unit  161  to the device  200  on the student side. 
       FIG.  13    is a flowchart for explaining an operation of the device  200  on the student side when the teacher is performing in a real-time class, for example. The processing of  FIG.  13    is executed in conjunction with the processing of  FIG.  12   . 
     In step S 21 , the digital twin generation unit  261  generates a student digital twin on the basis of sensor data of the student sensed by the sensor unit  250 . 
     In step S 22 , the digital twin adjustment unit  262  generates an adjusted teacher digital twin by adjusting the teacher digital twin from the device  200  on the student side on the basis of the student digital twin generated by the digital twin generation unit  261 . 
     In step S 23 , the superimposed video generation unit  263  generates a superimposed video in which the student digital twin is superimposed on the adjusted teacher digital twin. 
     In step S 24 , the evaluation unit  264  calculates the evaluation value of the student digital twin by evaluating the student digital twin using the adjusted teacher digital twin. 
     In step S 25 , the effect generation unit  265  generates an effect video for the superimposed image on the basis of the 3D model information among the evaluation values calculated by the evaluation unit  264 . 
     In step S 26 , the display control unit  266  causes the display unit  210  to display the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265 . 
     Meanwhile, the meta information among the evaluation values calculated by the evaluation unit  264  is also transmitted to the device  100  on the teacher side. 
       FIG.  14    is a flowchart for explaining an operation of the device  100  on the teacher side based on the evaluation value from the device  200  on the student side. The processing of  FIG.  14    is executed in parallel with the processing of  FIG.  13   . 
     In step S 31 , the instruction information generation unit  162  generates the instruction information on the basis of the evaluation value (meta information) from the device  200  on the student side. Specifically, the instruction information generation unit  162  generates, as the instruction information, display information indicating the deviation amount or the deviation part of the movement of the student with respect to the movement of the teacher. The display information may include a comment automatically generated according to the evaluation value (meta information) or a comment input by the teacher. 
     In step S 32 , the control unit  160  controls the communication unit  140  to transmit the instruction information generated by the instruction information generation unit  162  to the device  200  on the student side. 
     In the device  200  on the student side, the instruction information from the device  100  on the teacher side is displayed on the display unit  210  together with the superimposed video and the effect video by the display control unit  266 . 
     According to the above processing, since the teacher digital twin is adjusted according to the student digital twin, the student can easily copy the movement of the teacher by comparing the own movement with the teacher&#39;s movement while watching the superimposed video. 
     Furthermore, since the effect video based on the difference from the movement of the teacher is superimposed and displayed on the superimposed video, the student can easily recognize the deviation between the own movement and the teacher&#39;s movement. 
     Furthermore, since the instruction information indicating the deviation amount and the deviation part of the movement of the student and the comment corresponding to the deviation amount and the deviation part are displayed together with the effect video, the student can understand how the own movement is specifically deviated and how to move. 
     As described above, it is possible to provide more effective learning content for the student to learn the movement of the body. 
     Note that, in the above description, only the evaluation value calculated by the evaluation unit  264  is transmitted from the device  200  on the student side to the device  100  on the teacher side. Alternatively, the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  may be transmitted from the device  200  on the student side to the device  100  on the teacher side. In this case, in the device  100  on the teacher side, the superimposed video and the effect video are displayed on the display unit  110  under the control of the control unit  160 . 
     As a result, the teacher can easily recognize the deviation between the movement of the teacher and the movement of the student, and can present a more appropriate instruction or advice to the student as the instruction information (comment). Note that the comment for the student may be not only presented as character information but also output as voice information. 
     &lt;3. Application Example of 5G Network Slicing&gt; 
     As described above, in the information processing system to which the technology according to the present disclosure is applied, 5G can be applied as a communication method between devices. 
     The 5G has three features of “high speed and large capacity”, “low latency”, and “multiple simultaneous connection”. These functions can be implemented by a technology called network slicing for virtually dividing (slicing) a network. In 5G, data can be transmitted in a high-speed large-capacity network slice (hereinafter, simply referred to as a slice.) or can be transmitted in a low-latency network slice according to the type and application of data. 
     (3-1. Application Example of 5G Network Slicing  1 ) 
     Hereinafter, an application example of 5G network slicing applied to an information processing system to which the technology according to the present disclosure is applied will be described. 
     (3-1-1. Device-Device Configuration 1) 
       FIG.  15    is a diagram illustrating an example in which 5G network slicing is applied to the information processing system described above. In the drawing, bold line arrows indicate transmission paths supported by 5G. 
     In the example of  FIG.  15   , in the teacher digital twin generated by the digital twin generation unit  161 , from the teacher side to the student side (the digital twin adjustment unit  262 ), the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the student side to the teacher side (instruction information generation unit  162 ), the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     In this case, the instruction information generation unit  162  may generate the instruction information for the student on the basis of the superimposed video from the superimposed video generation unit  263  or the effect video from the effect generation unit  265 . Furthermore, the superimposed video and the effect video supplied to the instruction information generation unit  162  may be displayed on the display unit  110  under the control of the control unit  160 . 
     As described above, since the feature point information and the evaluation value required for the real-time property are transmitted via the low latency slice, the followability of the digital twin with respect to the body motion of the teacher and the quickness of the feedback regarding the body motion of the student can be secured. 
     Incidentally, each functional unit included in the control unit  160  and each functional unit included in the control unit  260  described above may not be implemented on the device  100  on the teacher side and the device  200  on the student side, respectively. 
     (3-1-2. Device-Device Configuration 2) 
     As illustrated in  FIG.  16   , the digital twin adjustment unit  262  may be implemented on the device  100  on the teacher side. 
     In the example of  FIG.  16   , from the teacher side to the student side (the superimposed video generation unit  263  and the evaluation unit  264 ), among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the student side to the teacher side (instruction information generation unit  162 ), the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. Note that the feature point information of the student digital twin generated by the digital twin generation unit  261  may be transmitted to the teacher side (the digital twin adjustment unit  262 ) via a low latency slice. 
     Although examples in which the digital twin adjustment unit  262  is implemented on either the device  100  on the teacher side or the device  200  on the student side have been described above, it may be implemented on both the devices  100 , and  200 . Furthermore, the function of the device  100  on the teacher side and the function of the device  200  on the student side may be switched at a predetermined timing. 
     (3-1-3. Device-MEC-Device Configuration 1) 
     As illustrated in  FIG.  17   , the digital twin generation unit  161  and the instruction information generation unit  162  may be implemented on a MEC server  10 TE close to the device  100  on the teacher side, and the digital twin generation unit  261  to the effect generation unit  265  may be implemented on a MEC server  10 ST close to the device  200  on the student side. 
     In this case, the device  100  on the teacher side transmits the sensing data acquired by the sensor unit  150  to the MEC server  10 TE (the digital twin generation unit  161 ). Similarly, the device  200  on the student side transmits the sensing data acquired by the sensor unit  250  to the MEC server  10 ST (the MEC server  10 ST). 
     Note that the MEC server  10 TE (the digital twin generation unit  161 ) may generate the teacher digital twin by extracting feature points from the recoded content stored in the cloud server  20 . As a result, the use case UC 2  and the use case UC 4  in  FIG.  4    are implemented. 
     In the example of  FIG.  17   , in the teacher digital twin generated by the digital twin generation unit  161 , from the MEC server  10 TE on the teacher side to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the MEC server  10 ST on the student side to the MEC server  10 TE (the instruction information generation unit  162 ) on the teacher side, the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-1-4. Device-MEC-Device Configuration 2) 
     As illustrated in  FIG.  18   , the digital twin generation unit  161  and the instruction information generation unit  162  may be implemented on the MEC server  10 TE close to the device  100  on the teacher side, and the digital twin generation unit  261 , the digital twin adjustment unit  262 , and the evaluation unit  264  may be implemented on a MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  18   , in the teacher digital twin generated by the digital twin generation unit  161 , from the MEC server  10 TE on the teacher side to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In the student digital twin generated by the digital twin generation unit  261 , from the MEC server  10 ST on the student side to the device  200  (the superimposed video generation unit  263 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. Similarly, to the device  200  (the superimposed video generation unit  263 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     In addition, the evaluation value calculated by the evaluation unit  264  is transmitted from the MEC server  10 ST on the student side to the MEC server  10 TE (the instruction information generation unit  162 ) on the teacher side via a low latency slice. Furthermore, from the device  200  on the student side to the MEC server  10 TE (the instruction information generation unit  162 ) on the teacher side, the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-1-5. Device-MEC-Device Configuration 3) 
     As illustrated in  FIG.  19   , the digital twin generation unit  161  may be realized on the MEC server  10 TE close to the device  100  on the teacher side, and the digital twin generation unit  261  and the digital twin adjustment unit  262  may be realized on a MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  19   , in the teacher digital twin generated by the digital twin generation unit  161 , from the MEC server  10 TE on the teacher side to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In the student digital twin generated by the digital twin generation unit  261 , from the MEC server  10 ST on the student side to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. Similarly, to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the device  200  on the student side to the device  100  (instruction information generation unit  162 ) on the teacher side, the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-1-6. Device-MEC-Device Configuration 4) 
     As illustrated in  FIG.  20   , the digital twin generation unit  161  may be implemented on the MEC server  10 TE close to the device  100  on the teacher side, and the digital twin generation unit  261  to the evaluation unit  264  may be implemented on a MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  20   , in the teacher digital twin generated by the digital twin generation unit  161 , from the MEC server  10 TE on the teacher side to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In addition, the evaluation value calculated by the evaluation unit  264  is transmitted from the MEC server  10 ST on the student side to the device  100  (the instruction information generation unit  162 ) on the teacher side via a low latency slice. Furthermore, from the device  200  on the student side to the device  100  (the instruction information generation unit  162 ) on the teacher side, the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     Note that the superimposed video generated by the superimposed video generation unit  263  may be transmitted from the MEC server  10 ST on the student side to the device  200  (the effect generation unit  265 ) on the student side via a large-capacity slice. Furthermore, the evaluation value (3D model information) calculated by the evaluation unit  264  may be transmitted from the MEC server  10 ST on the student side to the device  200  (the effect generation unit  265 ) on the student side via a large-capacity slice. 
     (3-1-7. Device-MEC-Device Configuration 5) 
     As illustrated in  FIG.  21   , only the digital twin adjustment unit  262  may be implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  21   , in the teacher digital twin generated by the digital twin generation unit  161 , from the device  100  on the teacher side to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     From the MEC server  10 ST on the student side, to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the device  200  on the student side to the device  100  (instruction information generation unit  162 ) on the teacher side, the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     Note that the feature point information of the student digital twin generated by the digital twin generation unit  261  may be transmitted to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side via a low latency slice. 
     In the example of  FIG.  21   , the digital twin adjustment unit  262  is implemented on the MEC server  10 ST close to the device  200  on the student side, but may be implemented on the MEC server  10 TE close to the device  100  on the teacher side. 
     (3-2. Other Configuration Examples of Information Processing System) 
     The configuration of the information processing system that realizes the real-time class has been mainly described above. On the other hand, if the teacher digital twin generated in advance can be reproduced, the user (student) at home can take a non-real-time lesson at a desired timing instead of a real-time class. 
       FIG.  22    is a block diagram illustrating another configuration example of an information processing system to which the technology according to the present disclosure is applied. 
     The information processing system in  FIG.  22    includes a cloud server  20  and a device  200  on the student side. The device  200  on the student side in  FIG.  22    is configured similarly to the device  200  on the student side described above, but only main functional units are illustrated in  FIG.  22   . 
     The cloud server  20  includes a storage device  310  and an instruction information generation unit  320 . 
     The storage device  310  stores the teacher digital twin generated in advance, and supplies the teacher digital twin to the device  200  on the student side in response to a request from the device  200  on the student side. 
     The instruction information generation unit  320  basically has a function similar to that of the instruction information generation unit  162  described above, but is different from the instruction information generation unit  162  in that the instruction information is automatically generated on the basis of artificial intelligence (AI). 
       FIG.  23    is a diagram for explaining details of the storage device  310 . 
     As illustrated in  FIG.  23   , the storage device  310  includes a communication unit  311 , a storage unit  312 , and a control unit  313 . 
     The communication unit  311  includes a network interface and the like, and communicates with the device  200  on the student side on the basis of the control of the control unit  313 . 
     The storage unit  312  stores programs necessary for operating the storage device  310 , various data prepared in advance, and the like. 
     Specifically, the storage unit  312  stores the real-time performance of the person and the teacher digital twin generated on the basis of the recoded content, and the stored teacher digital twin is read in response to a request from the device  200  on the student side. 
     Furthermore, the storage unit  312  may store sensor data and feature point information acquired in advance, and the teacher digital twin may be generated on the basis of the sensor data and the feature point information. Furthermore, a predetermined recoded content may be stored in the storage unit  312 , and the teacher digital twin may be generated on the basis of the recoded content. 
     The control unit  313  executes various processing on the basis of the program stored in the storage unit  312 . For example, in response to a request from the device  200  on the student side, the control unit  313  supplies the teacher digital twin stored in the storage unit  312  to the device  200  on the student side, and generates the teacher digital twin on the basis of the sensor data and the feature point information stored in the storage unit  312 . 
     Also in the above configuration, since the teacher digital twin is adjusted according to the student digital twin, the student can easily copy the movement of the teacher by comparing the own movement with the teacher&#39;s movement while watching the superimposed video. 
     Furthermore, since the effect video based on the difference from the movement of the teacher is superimposed and displayed on the superimposed video, the student can easily recognize the deviation between the own movement and the teacher&#39;s movement. 
     Furthermore, since the instruction information indicating the deviation amount and the deviation part of the movement of the student and the comment corresponding to the deviation amount and the deviation part are displayed together with the effect video, the student can understand how the own movement is specifically deviated and how to move. 
     As described above, it is possible to provide more effective learning content for the student to learn the movement of the body. 
     Note that, in the storage device  310 , the teacher digital twin, the sensor data, and the feature point information stored in the storage device  310  may be managed in association with the person who has performed the body motion reflected in the digital twin, the sensor data, and the feature point information. Furthermore, in the storage device  310 , for example, feature point information may be extracted from a game video of a professional soccer player, and a teacher digital twin generated on the basis of skeleton estimation using machine learning or the like may be managed in association with the professional soccer player. 
     For example, a person ID for specifying a certain person, time information indicating the date and time when the digital twin is generated, genre information indicating the purpose and type of the body motion, and the like are associated with the digital twin reflecting the body motion of the certain person. 
     As a result, the user to be a student can select a desired person or a digital twin of body motion and take a non-real-time lesson. 
     Furthermore, the digital twin associated with the person ID may be a target of electronic commerce in a marketplace (electronic market). In this case, in the storage device  310 , the metadata of the copyright information including the person ID, the sales price, the sales period, and the like of the digital twin is stored as a database and centrally managed. 
     As a result, it is possible to manage the copyright of the provider of the digital twin, for example, protecting the provider&#39;s own movement such as an instructor who has provided the digital twin as a work or entering a license agreement by the provider with a predetermined company or group. 
     (3-3. Application Example of 5G Network Slicing  2 ) 
     The 5G network slicing can also be applied to the information processing system of  FIG.  22   . 
     (3-3-1. Device-MEC-Cloud Configuration 1) 
       FIG.  24    is a diagram illustrating an example in which 5G network slicing is applied to the information processing system of  FIG.  22   . In the drawing, bold line arrows indicate transmission paths supported by 5G. 
     In the example of  FIG.  24   , the digital twin generation unit  261  to the effect generation unit  265  are implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In this case, the device  200  on the student side transmits the sensing data acquired by the sensor unit  250  to the MEC server  10 ST (the digital twin generation unit  261 ). 
     In the example of  FIG.  24   , in the teacher digital twin stored in the storage device  310 , from the cloud server  20  to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the MEC server  10 ST on the student side to the cloud server  20  (the instruction information generation unit  320 ), the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-3-2. Device-MEC-Cloud Configuration 2) 
     As illustrated in  FIG.  25   , the digital twin generation unit  261 , the digital twin adjustment unit  262 , and the evaluation unit  264  may be implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  25   , in the teacher digital twin stored in the storage device  310 , from the cloud server  20  to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In the student digital twin generated by the digital twin generation unit  261 , from the MEC server  10 ST on the student side to the device  200  (the superimposed video generation unit  263 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. Similarly, to the device  200  (the superimposed video generation unit  263 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     In addition, the evaluation value calculated by the evaluation unit  264  is transmitted from the MEC server  10 ST on the student side to the cloud server  20  (the instruction information generation unit  320 ) via a low latency slice. Furthermore, from the device  200  on the student side to the cloud server  20  (the instruction information generation unit  320 ), the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-3-3. Device-MEC-Cloud Configuration 3) 
     As illustrated in  FIG.  26   , the digital twin generation unit  261  and the digital twin adjustment unit  262  may be implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  26   , in the teacher digital twin stored in the storage device  310 , from the cloud server  20  to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In the student digital twin generated by the digital twin generation unit  261 , from the MEC server  10 ST on the student side to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. Similarly, to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the device  200  on the student side to the cloud server  20  (the instruction information generation unit  320 ), the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     (3-3-4. Device-MEC-Cloud Configuration 4) 
     As illustrated in  FIG.  27   , the digital twin generation unit  261  to the evaluation unit  264  may be implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  27   , in the teacher digital twin stored in the storage device  310 , from the cloud server  20  to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     In addition, the evaluation value calculated by the evaluation unit  264  is transmitted from the MEC server  10 ST on the student side to the cloud server  20  (the instruction information generation unit  320 ) via a low latency slice. Furthermore, from the device  200  on the student side to the cloud server  20  (the instruction information generation unit  320 ), the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     Note that the superimposed video generated by the superimposed video generation unit  263  may be transmitted from the MEC server  10 ST on the student side to the device  200  (the effect generation unit  265 ) on the student side via a large-capacity slice. Furthermore, the evaluation value (3D model information) calculated by the evaluation unit  264  may be transmitted from the MEC server  10 ST on the student side to the device  200  (the effect generation unit  265 ) on the student side via a large-capacity slice. 
     (3-3-5. Device-MEC-Cloud Configuration 5) 
     As illustrated in  FIG.  28   , only the digital twin adjustment unit  262  may be implemented on the MEC server  10 ST close to the device  200  on the student side. 
     In the example of  FIG.  28   , in the teacher digital twin stored in the storage device  310 , from the cloud server  20  to the MEC server  10 ST (the digital twin adjustment unit  262 ) on the student side, the feature point information is transmitted via a low latency slice, and the 3D model is transmitted via a large-capacity slice. 
     From the MEC server  10 ST on the student side, to the device  200  (the superimposed video generation unit  263  and the evaluation unit  264 ) on the student side, among the adjusted teacher digital twin generated by the digital twin adjustment unit  262 , the adjusted feature point information is transmitted via a low latency slice, and the adjusted 3D model is transmitted via a large-capacity slice. 
     Furthermore, from the device  200  on the student side to the cloud server  20  (the instruction information generation unit  320 ), the evaluation value calculated by the evaluation unit  264  is transmitted via a low latency slice, and the superimposed video generated by the superimposed video generation unit  263  and the effect video generated by the effect generation unit  265  are transmitted via a large-capacity slice. 
     Note that the feature point information of the student digital twin generated by the digital twin generation unit  261  may be transmitted to the teacher side (the digital twin adjustment unit  262 ) via a low latency slice. 
     As described above, the 5G network slicing can also be applied to the information processing system of  FIG.  22   . 
     &lt;4. Modifications&gt; 
     Hereinafter, modifications of the above-described embodiment will be described. 
     (Display Example of Digital Twin) 
     In the above description, as the digital twin, the 3D model combined with the skin data is displayed on the device  200  or the like on the student side. In addition, as illustrated in  FIG.  29   , the skeleton image based on the skeleton information may be superimposed and displayed on the 3D model as the digital twin. 
     In the example of  FIG.  29   , a skeleton image  430  representing a skeleton and joint points of a person who is a student is superimposed and displayed on an upright student digital twin  30 ST (3D model). In the example of  FIG.  29   , the teacher digital twin  30 TE illustrated in  FIG.  2    is not superimposed, but the teacher digital twin  30 TE may be further superimposed and displayed on the skeleton image  430 . 
     (Presentation Example of Character Information) 
     In the above description, information such as a digital twin, instruction information, and an evaluation value is transmitted and received between the device  100  on the teacher side and the device  200  on the student side. In addition, for example, status information indicating the progress status of the lesson taken by the student and the state of the student performing the body motion in the lesson may be transmitted and received between the device  100  on the teacher side and the device  200  on the student side. 
       FIGS.  30  to  32    are diagrams illustrating presentation examples of character information indicating the above-described status information in the device  200  on the student side. 
     (Presentation Example 1) 
     In the example of  FIG.  30   , status information indicating that a lesson is started by the student performing an operation for starting the lesson is transmitted from the device  200  on the student side to the device  100  on the teacher side. 
     For example, in the state of the screen # 11  of  FIG.  30   , character information  441  indicating the name of a lesson to be started is displayed together with the student digital twin  30 ST standing upright. Furthermore, on the upper right of the screen # 11 , a GUI button  41  for starting a lesson is displayed as in  FIG.  2   . 
     As illustrated in the state of the screen # 12 , if the student raises one hand and it is determined that the hand of the corresponding student digital twin  30 ST overlaps the area of the button  41 , the lesson by the instructor TE is started. At this time, the character information  441  changes to a particle video  442 . 
     Thereafter, status information indicating the start of a lesson is transmitted to the device  100  on the teacher side, and the particles constituting the particle video  442  move so as to be sucked into the upper side of the screen # 13  as illustrated in the state of the screen # 13 . 
     As described above, the character information  441  changes to the particle video  442  and moves to the upper side of the screen # 13 , so that the student as the user can intuitively understand that the status information indicating the start of the lesson has been transmitted to the device  100  on the teacher side. 
     (Presentation Example 2) 
     In the example of  FIG.  31   , status information indicating that the student taking a lesson is too close to the display (display unit  210 ) and is dangerous is transmitted from the device  200  on the student side to the device  100  on the teacher side. 
     For example, in the state of the screen # 21  in  FIG.  31   , character information  451  indicating the distance between the student and the display is displayed together with the student digital twin  30 ST. On the screen # 21 , the character information  451  indicates that the distance between the student and the display is 146 cm. 
     When the distance between the student and the display falls below a predetermined threshold value (for example, 145 cm), the character information  451  changes to the particle video  452  as illustrated in the state of the screen # 22 . 
     Thereafter, status information indicating the student is too close to the display is transmitted to the device  100  on the teacher side, and the particles constituting the particle video  452  move so as to be sucked into the upper side of the screen # 23  as illustrated in the state of the screen # 23 . 
     As described above, the character information  451  changes to the particle video  452  and moves to the upper side of the screen # 23 , so that the student as the user can intuitively understand that the status information indicating the student himself/herself is too close to the display has been transmitted to the device  100  on the teacher side. 
     (Presentation Example 3) 
     In the example of  FIG.  32   , status information indicating that the physical load of the student taking a lesson is transmitted from the device  200  on the student side to the device  100  on the teacher side. The status information indicating the physical load of the student is generated on the basis of a vital sign acquired by a vital sensor provided as the sensor unit  250 , for example. 
     For example, in the state of the screen # 31  in  FIG.  32   , character information  461  indicating the physical load of the student is displayed together with the student digital twin  30 ST. On the screen # 31 , the character information  461  indicates that the physical load state of the student is “HARD”. 
     When the vital sign of the student exceeds a predetermined limit value, the character information  461  changes to a particle video  462  as illustrated in the state of the screen # 32 . 
     Thereafter, status information indicating the physical load of the student exceeds a predetermined limit value is transmitted to the device  100  on the teacher side, and the particles constituting the particle video  462  move so as to be sucked into the upper side of the screen # 33  as illustrated in the state of the screen # 33 . 
     As described above, the character information  461  changes to the particle video  462  and moves to the upper side of the screen # 33 , so that the student as the user can intuitively understand that the status information indicating the physical load of the student himself/herself exceeds the limitation has been transmitted to the device  100  on the teacher side. 
     In the above-described examples, the character information indicating the progress status of the lesson or the state of the student is changed to the particle video, but a part of the skeleton image  430  superimposed and displayed on the student digital twin  30 ST may be changed to the particle video. 
     For example, when the skeleton image  430  corresponding to the portion of the student digital twin which has moved differently from the teacher digital twin changes to the particle video, the student can recognize that he/she has made an erroneous movement. 
     Note that when the character information changes to the particle video, display colors may change, for example, the black character information may change to the red particle video. 
     (Application Example) 
     The above-described presentation example can also be applied to, for example, a configuration in which a line manager of a factory monitors the state of on-site production line workers individually. In this case, the line manager can collectively grasp the work situation, the physical load, the mental stress, and the like of the on-site worker, and if there is a possibility that the state of the site worker hinders the work, the line manager can immediately notify the management manager of the factory of the possibility. 
     (Application of Face Authentication) 
     In the embodiments described above, face authentication may be performed when starting a lesson or when starting work in a factory, for example. As a result, it is possible for a teacher to avoid offering a lesson to a wrong student, and it is possible for a line manager of a factory to easily grasp an attendance state of an on-site worker. 
     (Adjustment of Digital Twin) 
     In the embodiment described above, mainly on the basis of the student digital twin reflecting the body motion of the student who is the user (first person), the teacher digital twin is adjusted so that the teacher digital twin reflecting the body motion of the teacher who is the reference person (second person) matches the student digital twin. Conversely, the student digital twin may be adjusted on the basis of the teacher digital twin so as to match the student digital twin with the teacher digital twin, or the person to be reference (reference person) may be switched between the student and the teacher. 
     &lt;5. Configuration Example of Computer&gt; 
     The series of processes described above can be executed by hardware, and can also be executed in software. In the case of executing the series of processes by software, a program forming the software is installed on a computer. Herein, the term computer includes a computer built into special-purpose hardware, a computer able to execute various functions by installing various programs thereon, such as a general-purpose personal computer, for example, and the like. 
       FIG.  33    is a block diagram illustrating a hardware configuration example of a computer that executes the series of processes described above according to a program. 
     In the computer, a central processing unit (CPU)  1001 , read only memory (ROM)  1002 , and random access memory (RAM)  1003  are interconnected by a bus  1004 . 
     Additionally, an input/output interface  1005  is connected to the bus  1004 . An input unit  1006 , an output unit  1007 , a storage unit  1008 , a communication unit  1009 , and a drive  1010  are connected to the input/output interface  1005 . 
     The input unit  1006  includes a keyboard, a mouse, a microphone, and the like, for example. The output unit  1007  includes a display, a speaker, and the like, for example. The storage unit  1008  includes a hard disk, non-volatile memory, and the like, for example. The communication unit  1009  includes a network interface, for example. The drive  1010  drives a removable medium  1011  such as a magnetic disk, an optical disc, a magneto-optical disc, or semiconductor memory. 
     In a computer configured as above, the series of processes described above are performed by having the CPU  1001  load a program stored in the storage unit  1008  into the RAM  1003  via the input/output interface  1005  and the bus  1004 , and execute the program, for example. 
     For example, programs to be executed by the computer (CPU  1001 ) can be recorded and provided in the removable medium  1011 , which is a packaged medium or the like. In addition, the program can be supplied via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcast. 
     In the computer, by mounting the removable medium  1011  onto the drive  1010 , programs can be installed into the storage unit  1008  via the input/output interface  1005 . Programs can also be received by the communication unit  1009  via a wired or wireless transmission medium and installed into the storage unit  1008 . In addition, programs can be installed in advance into the ROM  1002  or the storage unit  1008 . 
     Note that a program executed by the computer may be a program in which processing is chronologically carried out in a time series in the order described herein or may be a program in which processing is carried out in parallel or at necessary timing, such as when the processing is called. 
     In the present specification, steps of describing a program recorded in a recording medium include not only processing performed in chronological order according to the described order, but also processing executed in parallel or individually even if the processing is not necessarily performed in chronological order. 
     Further, in this specification, a system has the meaning of a set of a plurality of structural elements (such as an apparatus or a module (part)), and does not take into account whether or not all the structural elements are in the same casing. Therefore, the system may be either a plurality of apparatuses, stored in separate casings and connected through a network, or a single device including a plurality of modules within a single casing. 
     In addition, an embodiment of the present technology according to the present disclosure is not limited to the embodiments described above, and various changes and modifications may be made without departing from the scope of the technology according to the present disclosure. 
     Furthermore, the effects described in this specification are merely examples and are not limited, and other effects may be exerted. 
     Additionally, the technology according to the present disclosure may also be configured as below. 
     (1) 
     An information processing apparatus including: 
     an adjustment unit configured to generate an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     (2) 
     The information processing apparatus according to (1), in which 
     the adjustment unit changes the feature point information of the second person included in the second virtual object on the basis of the feature point information of the first person included in the first virtual object. 
     (3) 
     The information processing apparatus according to (2), in which 
     the feature point information includes at least one of skeleton information, left and right information, or three-dimensional contour information. 
     (4) 
     The information processing apparatus according to any one of (1) to (3), in which 
     the adjustment unit adjusts at least a scale of the second virtual object on the basis of the feature point information. 
     (5) 
     The information processing apparatus according to any one of (1) to (4) further including 
     a generation unit configured to generate, on the basis of the feature point information of a person, a virtual object reflecting a body motion of the person. 
     (6) 
     The information processing method according to (5), in which 
     the generation unit extracts feature point information of the person on the basis of sensor data obtained by sensing the person. 
     (7) 
     The information processing apparatus according to (6), in which 
     the sensor data includes at least one of ToF data, RGB data, or volumetric capture data. 
     (8) 
     The information processing apparatus according to (6) or (7) further including 
     a sensor configured to sense the person. 
     (9) 
     The information processing apparatus according to (5), in which 
     the generation unit extracts the feature point information of the person on the basis of a video showing the person. 
     (10) 
     The information processing apparatus according to any one of (5) to (9), in which 
     the generation unit 
     removes a background of the person in the RGB data on the basis of the feature point information of the person and the RGB data obtained by sensing the person, and 
     generates the virtual object on the basis of the RGB data from which the background has been removed and the feature point information of the person. 
     (11) 
     The information processing apparatus according to any one of (5) to (10, in which 
     the generation unit generates the virtual object of a type according to a purpose of the body motion of the person. 
     (12) 
     The information processing apparatus according to any one of (1) to (11) further including 
     a video generation unit configured to generate a superimposed video in which the first virtual object is superimposed on the adjusted second virtual object. 
     (13) 
     The information processing apparatus according to (12) further including 
     an evaluation unit configured to generate an evaluation value of the first virtual object by comparing the first virtual object with the adjusted second virtual object. 
     (14) 
     The information processing apparatus according to (13), in which 
     the evaluation value includes at least one of a difference in three-dimensional contour information, a difference in acceleration information, or a difference in a predetermined fitting point between the first virtual object and the adjusted second virtual object. 
     (15) 
     The information processing apparatus according to (13) or (14) further including 
     an effect generation unit configured to generate an effect video for the superimposed video on the basis of the evaluation value. 
     (16) 
     The information processing apparatus according to (15), in which 
     the effect generation unit generates the effect video according to a purpose of the body motion of the first person. 
     (17) 
     The information processing apparatus according to (15) or (16) further including 
     a display control unit configured to display the superimposed video and the effect video on a display unit. 
     (18) 
     The information processing apparatus according to (17), in which 
     the display control unit switches the effect video to be displayed on the display unit according to an operation of the first person. 
     (19) 
     The information processing apparatus according to (17) or (18) further including 
     an instruction information generation unit configured to generate instruction information for the second person to provide a predetermined instruction to the body motion of the first person on the basis of the evaluation value. 
     (20) 
     The information processing apparatus according to (19), in which 
     the display control unit further displays the instruction information on the display unit. 
     (21) 
     The information processing apparatus according to any one of (1) to (20), in which 
     a virtual object includes feature point information of a person and a three-dimensional model based on the feature point information, and 
     the feature point information and the three-dimensional model are transmitted via different network slices. 
     (22) 
     The information processing apparatus according to (21), in which 
     the feature point information is transmitted via a low-latency network slice, and 
     the three-dimensional model is transmitted via a large-capacity network slice. 
     (23) 
     The information processing apparatus according to any one of (1) to (22), in which 
     a functional unit including the adjustment unit is implemented by a mobile edge computing (MEC). 
     (24) 
     The information processing apparatus according to any one of (1) to (23), in which 
     the second virtual object is managed on the basis of copyright information including a person ID for specifying the second person. 
     (25) 
     An information processing method including: 
     by an information processing apparatus, 
     generating an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     (26) 
     A program causing a computer 
     to execute processing of: 
     generating an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. 
     REFERENCE SIGNS LIST 
     
         
           10 ,  10 TE,  10 ST MEC Server 
           20  Cloud server 
           100  Device 
           150  Sensor unit 
           160  Control unit 
           161  Digital twin generation unit 
           162  Instruction information generation unit 
           200  Device 
           250  Sensor unit 
           260  Control unit 
           261  Digital twin generation unit 
           262  Digital twin adjustment unit 
           263  Superimposed video generation unit 
           264  Evaluation unit 
           265  Effect generation unit 
           266  Display control unit 
           310  Storage device 
           320  Instruction information generation unit 
           312  Storage unit 
           313  Control unit 
           1001  CPU