CN109331455A - Movement error correction method, device, storage medium and the terminal of human body attitude - Google Patents
Movement error correction method, device, storage medium and the terminal of human body attitude Download PDFInfo
- Publication number
- CN109331455A CN109331455A CN201811379006.9A CN201811379006A CN109331455A CN 109331455 A CN109331455 A CN 109331455A CN 201811379006 A CN201811379006 A CN 201811379006A CN 109331455 A CN109331455 A CN 109331455A
- Authority
- CN
- China
- Prior art keywords
- data
- human body
- video
- error correction
- video data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
- A63B2024/0068—Comparison to target or threshold, previous performance or not real time comparison to other individuals
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
- A63B2071/0636—3D visualisation
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B2071/0647—Visualisation of executed movements
Abstract
The embodiment of the present application discloses movement error correction method, device, storage medium and the terminal of a kind of human body attitude, determines the first video data according to instructional video first；The first human body coordinate data is determined according to first video data；Then, the second video data of user is obtained, second video data includes imitation image of the user according to first video data；The second human body coordinate data is determined according to second video data；Finally, determining the first error correction data according to the first human body coordinate data and the second human body coordinate data, first error correction data is exported.Error correction data can be determined based on the imitation image of instructional video and user, provide error correcting prompt for user, accurately human body attitude is corrected, improve body-building effect.
Description
Technical field
The invention relates to the movement error correction method of technical field of mobile terminals more particularly to human body attitude, device,
Storage medium and terminal.
Background technique
With the development of the society, the health sense of people gradually increases, but due to the limitation of body-building field so that very much
People carries out body-building in the case where no exercise guide, causes body-building effect bad since body-building movement is nonstandard.How to
The body-building movement at family, which correct, becomes urgent problem to be solved.
Summary of the invention
The purpose of the embodiment of the present application is to provide movement error correction method, device, storage medium and the end of a kind of human body attitude
End, can more accurately correct human body attitude.
In a first aspect, the embodiment of the present application provides a kind of movement error correction method of human body attitude, comprising:
The first video data is determined according to instructional video；
The first human body coordinate data is determined according to first video data；
The second video data of user is obtained, second video data includes user according to first video data
Imitate image；
The second human body coordinate data is determined according to second video data；
The first error correction data is determined according to the first human body coordinate data and the second human body coordinate data；
Export first error correction data.
Second aspect, the embodiment of the present application provide a kind of movement error correction device of human body attitude, comprising:
First video determining module, for determining the first video data according to instructional video；
First coordinate determining module, first video data for being determined according to the first video determining module are true
Fixed first human body coordinate data；
Second video acquiring module, for obtaining the second video data of user, second video data includes user
According to the imitation image of first video data；
Second coordinate determining module, second video data for being obtained according to second video acquiring module are true
Fixed second human body coordinate data；
Error correction data determining module, the first human body number of coordinates for being determined according to the first coordinate determining module
The first error correction data is determined according to the second human body coordinate data determined with the second coordinate determining module；
Output module, first error correction data determined for exporting the error correction data determining module.
The third aspect, the embodiment of the present application provide a kind of computer readable storage medium, are stored thereon with computer journey
Sequence realizes the movement error correction method of the human body attitude as shown in first aspect when the program is executed by processor.
Fourth aspect, the embodiment of the present application provide a kind of terminal, including memory, and processor and storage are on a memory
And the computer program that can be run in processor, processor realize the human body appearance as shown in first aspect when executing computer program
The movement error correction method of state.
The movement error correction scheme of the human body attitude provided in the embodiment of the present application, determines the first view according to instructional video first
Frequency evidence；The first human body coordinate data is determined according to first video data；Then, the second video data of user is obtained,
Second video data includes imitation image of the user according to first video data；It is true according to second video data
Fixed second human body coordinate data；Finally, determining according to the first human body coordinate data and the second human body coordinate data
One error correction data exports first error correction data.Error correction data can be determined based on the imitation image of instructional video and user,
Error correcting prompt is provided for user, accurately human body attitude is corrected, improves body-building effect.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application；
Fig. 2 is the flow diagram of the movement error correction method of another human body attitude provided by the embodiments of the present application；
Fig. 3 is the flow diagram of the movement error correction method of another human body attitude provided by the embodiments of the present application；
Fig. 4 is the flow diagram of the movement error correction method of another human body attitude provided by the embodiments of the present application；
Fig. 5 is the flow diagram of the movement error correction method of another human body attitude provided by the embodiments of the present application；
Fig. 6 is the flow diagram of the movement error correction method of another human body attitude provided by the embodiments of the present application；
Fig. 7 is a kind of structural schematic diagram of the movement error correction device of human body attitude provided by the embodiments of the present application；
Fig. 8 is the structural schematic diagram of the movement error correction device of another human body attitude provided by the embodiments of the present application；
Fig. 9 is a kind of structural schematic diagram of mobile terminal provided by the embodiments of the present application.
Specific embodiment
Further illustrate the technical solution of the application below with reference to the accompanying drawings and specific embodiments.It is understood that
It is that specific embodiment described herein is used only for explaining the application, rather than the restriction to the application.It further needs exist for illustrating
, part relevant to the application is illustrated only for ease of description, in attached drawing rather than entire infrastructure.
It should be mentioned that some exemplary embodiments are described as before exemplary embodiment is discussed in greater detail
The processing or method described as flow chart.Although each step is described as the processing of sequence by flow chart, many of these
Step can be implemented concurrently, concomitantly or simultaneously.In addition, the sequence of each step can be rearranged.When its operation
Processing can be terminated when completion, it is also possible to have the additional step being not included in attached drawing.Handle the side of can correspond to
Method, function, regulation, subroutine, subprogram etc..
With the development of the society, the health sense of people gradually increases, but due to the limitation of body-building field so that very much
People carries out body-building in the case where no exercise guide, causes body-building effect bad since body-building movement is nonstandard.How to
The body-building movement at family, which correct, becomes urgent problem to be solved.
Based on this, the embodiment of the present application provides a kind of movement error correction method of human body attitude, is based on instructional video and use
The imitation image at family determines error correction data, provides error correcting prompt for user, accurately corrects to human body attitude, improves body-building
Effect.Concrete scheme is as follows:
Fig. 1 is the flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, and this method is used for
The case where providing movement error correction when user carries out body-building imitation referring to terminal plays instructional video for user.This method can be by having
There is the terminal of front camera to execute, which can be smart phone, tablet computer, wearable device, notebook
Computer etc., this method specifically comprises the following steps:
Step 110 determines the first video data according to instructional video.
Instructional video can be obtained by internet, can also be obtained by body-building application (APP), can also be terminal
The body-building video being locally stored.First video data is the positive text video in instructional video, in addition to positive text video in instructional video
It further include the rotating videos such as advertisement.The can be determined from instructional video by image recognition or specific text video identifier
One video data.
Step 120 determines the first human body coordinate data according to the first video data.
First video data is the video data that the body-building of standard acts.It can be from the first video data by preset algorithm
Frame image in obtain the first human body coordinate data.Wherein it is possible to obtain the according to each frame image in the first video data
One human body coordinate data can also determine a first human body coordinate data every N number of frame.Wherein, N is greater than 1 less than 10, optional
It is 3 or 5.Preset algorithm is referred to the acquisition that OpenPose algorithm carries out human body attitude, obtains the first human body in frame image and sits
Mark data.OpenPose algorithm can be used for identifying the human body attitude in two dimensional image.
Step 130, the second video data for obtaining user, the second video data includes user according to the first video data
Imitate image.
Instructional video is exported, user imitates according to instructional video.User is obtained when being played to the first video data
The second video data.The second video data of user can be obtained by the front camera of terminal.
Step 140 determines the second human body coordinate data according to the second video data.
The algorithm that can refer to step 120 offer, determines the second human body coordinate data according to the second video data.First human body
Coordinate data and the second human body coordinate data are made of the key point on human body.
Optionally, the frame image of video data (the first video data or the second video data) default human body is input to close
In key point identification model, which can determine the coordinate data of human body key point according to the frame image of the video data of input.
Human body key point identification model can be cyclic convolution neural network model.Key point includes: clavicle midpoint, left hand elbow, a left side
Wrist, left hip, left knee, left ankle and right hand elbow, right finesse, right hip, right knee, right ankle etc..Key point can be used for
The joint for identifying human body is mobile.It further, can also include the key point of each finger.
Step 150 determines the first error correction data according to the first human body coordinate data and the second human body coordinate data.
Optionally, axis compares the first human body coordinate data and the second human body coordinate data at the same time, according to coordinate
Difference determines the first error correction data.First error correction data may include written form or speech form.First misremembers data can be with
The key point of difference and the correct position of the key point are acted for prompt user's appearance, and is determined and is closed according to the correct position
The moving direction of key point indicates.
Further, the imitation of user may postpone than the first video data, can be sought at this time according to delay situation
Look for the first human body coordinate data being closer to the second human body coordinate data.
Step 160, the first error correction data of output.
The movement error correction method of the human body attitude provided in the embodiment of the present application, determines the first view according to instructional video first
Frequency evidence.The first human body coordinate data is determined according to the first video data.Then, the second video data of user is obtained, second
Video data includes imitation image of the user according to the first video data.The second human body number of coordinates is determined according to the second video data
According to.Finally, determining the first error correction data according to the first human body coordinate data and the second human body coordinate data, the first error correction number is exported
According to.Exist after the three-dimensional data of standard operation is manually entered in the related technology, uses the three-dimensional data and user action of standard
Three-dimensional data carries out the scheme than error correction, but the three-dimensional data needs of program Plays movement are manually entered by programmer,
The corresponding limbs state of every group of three-dimensional data is made of due to body-building movement multiple limbs states, a body-building
Movement needs to input a large amount of standard operation three-dimensional data, and then greatly improves make-up time and cost.The embodiment of the present application mentions
The movement error correction method of the human body attitude of confession can determine error correction data based on the imitation image of instructional video and user, according to religion
Learning video can determine the first video data, determine the first human body coordinate data, the first human body number of coordinates according to the first video data
It is manually entered according to without programmer, therefore can quickly determine the first human body coordinate data, so that error correction is lighter
It is easily achieved, the second video data of user can be obtained by front camera, and the second people is determined according to the second video data
Body coordinate data, the second human body coordinate data can accurately embody user's limb action, by comparing the first human body number of coordinates
After and output first error correction data determining with the second human body coordinate data, error correcting prompt can be provided for user, it is accurately right
Human body attitude is corrected, and body-building effect is improved.
Fig. 2 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, as right
The further explanation of above-described embodiment, comprising:
Step 210 obtains instructional video according to destination address.
Step 220, the positive mark for obtaining instructional video, positive mark include at least one set of origin identification and cut-off mark
Know.
Advertisement may be set in stem and tail portion in instructional video, it is also possible to wide in the rest of movement or buffer stage setting
It accuses, the positive of instructional video is intercepted as multistage at this time.The initial position of every section of positive is provided with origin identification, every section of positive
End position is provided with cut-off mark.When playing band respective frame image, the mark carried according to frame image (cut by origin identification
Only identify or without mark) it may recognize that positive identifies.
Step 230 obtains the first video data according to origin identification and cut-off mark.
Multiple positive segments can be identified according to origin identification and cut-off mark, after positive sub-piece is synthesized,
Obtain the first video data.
Further, it is identified if there is multiple groups positive, then obtains multiple first sub-video datas, each first son respectively
The corresponding one group of positive mark of video data.Splice multiple first sub-video datas, obtains the first video data.
Step 240 determines the first human body coordinate data according to the first video data.
Step 250, the second video data for obtaining user, the second video data includes user according to the first video data
Imitate image.
Step 260 determines the second human body coordinate data according to the second video data.
Step 270 determines the first error correction data according to the first human body coordinate data and the second human body coordinate data.
Step 280, the first error correction data of output.
The movement error correction method of human body attitude provided by the embodiments of the present application, relative to being mixed in advertisement in current instructional video
Miscellaneous advertising information causes additional human bioequivalence to cause power wastage, and the first video counts can be accurately identified from instructional video
According to, and accurately and effectively the first human body coordinate data is obtained, improve recognition efficiency.
Fig. 3 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, as right
The further explanation of above-described embodiment, comprising:
Step 301 determines the first video data according to instructional video.
Step 302 determines the first human body coordinate data according to the first video data.
Step 303 determines the first expressive features according to the facial image in the first video data.
By can determine human face region after carrying out recognition of face to the frame image in the first video data；According to human face region
It can determine the first expressive features.For certain Dancing Teachings, not only body posture needs to correct, while facial expression is also required to entangle
It is wrong.It can determine that the first expressive features, the first expressive features can be to smile, frown, laughing according to the coordinate of face feature point
Deng.Since the demonstration face in instructional video is different from user's face, misremember according to coordinate being easy to appear error, because
This can identify the expressive features in the first video data, special based on expression after identifying the second expressive features of user
Sign carries out error correction.
Step 304 determines the second expressive features according to the face characteristic of user.
Step 305 determines the second error correction data according to the first expressive features and the second expressive features.
Step 306, the second error correction data of output.
Step 307, the second video data for obtaining user, the second video data includes user according to the first video data
Imitate image.
Step 308 determines the second human body coordinate data according to the second video data.
Step 309 determines the first error correction data according to the first human body coordinate data and the second human body coordinate data.
Step 310, the first error correction data of output.
The movement error correction method of human body attitude provided by the embodiments of the present application, can be other than human body attitude, to face
Expressive features are identified, and carry out error correction based on human body expressive features, and then more comprehensively realize human body attitude and table
The error correction of feelings improves error correction efficiency.
Fig. 4 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, as right
The further explanation of above-described embodiment, comprising:
Step 410 determines the first video data according to instructional video.
Step 420 determines the first human body coordinate data according to the first video data.
Step 430, the limit for obtaining user act coordinate data.
Since the natural ligaments length of each user is different, itself pole may be had reached for identical movement user
Limit, but still have gap with instructional video, this kind of action error should be distinguished with the malfunction of user.It can play
Before first video data, guidance video is played, so that user is according to guidance video input human body limit position.For example, lower fork
Two leg angles and leg curvature degree, arm occupy the degree etc. that height is arm vertically.
If step 440, the first human body coordinate data and limit movement coordinate data mismatch, is acted and sat according to the limit
The first human body of data point reuse coordinate data is marked, to make the movement limit of the first human body coordinate data matching user.
When being acted in the first video data there are human body limit position, if user using reach itself the limit as,
And the extreme position of not up to the first video, then the warning prompt different from stroke defect is produced, so that user avoids excessively
Firmly cause to pull.
Step 450, the second video data for obtaining user, the second video data includes user according to the first video data
Imitate image.
Step 460 determines the second human body coordinate data according to the second video data.
Step 470 determines the first error correction data according to the first human body coordinate data and the second human body coordinate data.
Step 480, the first error correction data of output.
The movement error correction method of human body attitude provided by the embodiments of the present application, can according to the extreme position of user itself into
Row error correction, reaches the movement of itself limit to user and the miscue of movement that user does wrong distinguishes, and improves ease for use.
Fig. 5 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, as right
The further explanation of above-described embodiment, comprising:
Step 501 determines the first video data according to instructional video.
Step 502 determines the first human body coordinate data according to the first video data.
Step 503 determines instrument characteristics and the first instrument coordinate data according to the first video data.
Step 504 identifies the instrument that user uses according to instrument characteristics, and obtains the second instrument of the used instrument of user
Coordinate data.
In some body-building or dance movement, need by external device.If position or the usage mode mistake of instrument
Or used the instrument of wrong model, then also it is unable to reach desired effect.For example, the position that ball for health is contacted with body, or
Health and fitness facilities and the laminating type of arm etc..The instrument of different type, different model can be identified by deep learning.And know
Not Chu instrument and user the way of contact and contact position as the second instrument coordinate data.
Step 505 determines third error correction data according to the first instrument coordinate data and the second instrument coordinate data.
Third error correction data may include instrument error correction information, such as please replace instrument or the position of instrument and should move up
Deng.
Step 506, output third error correction data.
Step 507, the second video data for obtaining user, the second video data includes user according to the first video data
Imitate image.
Step 508 determines the second human body coordinate data according to the second video data.
Step 509 determines the first error correction data according to the first human body coordinate data and the second human body coordinate data.
Step 510, the first error correction data of output.
The movement error correction method of human body attitude provided by the embodiments of the present application can be known outside identification human body attitude information
The coordinate data for the instrument that Chu do not use generates the error correction information of instrument, improves the ease for use of error correction.
Fig. 6 is a kind of flow diagram of the movement error correction method of human body attitude provided by the embodiments of the present application, as right
The further explanation of above-described embodiment, comprising:
Step 610 determines the first video data according to instructional video.
Step 620 determines the first human body coordinate data according to the first video data.
Step 630, the second video data and the corresponding depth information of the second video data for obtaining user, the second video
Data include imitation image of the user according to the first video data.
The second video data of user and the depth information of user images can be obtained by depth camera, and then are obtained
To the three-dimensional data of user.Depth information includes the depth information of each key point of user, is provided in conjunction with the second video data
2-D data and depth information can synthesize the three-dimensional data of key point.
Step 640 determines user's 3 D human body coordinate data according to the second video data and depth information.
Step 650 determines the second human body coordinate data according to the second video data.
Step 660 obtains the corresponding target 3 D human body coordinate data of the first human body coordinate data.
Step 670 determines the 4th error correction number according to target 3 D human body coordinate data and user's 3 D human body coordinate data
According to.
Target 3 D human body coordinate data can be downloaded from internet and be obtained after determining instructional video.Optionally,
The corresponding target 3 D human body coordinate data of first video data can store in corresponding frame image.
Compare target 3 D human body coordinate data in three dimensions and user's 3 D human body coordinate data can determine the 4th
Error correction data.4th error correction data includes prompting the direction of motion of user in three dimensions.
Step 680, the first error correction data of output.
The movement error correction method of human body attitude provided by the embodiments of the present application, the three-dimensional error correction being capable of providing in three-dimensional space
Prompt, and then more error correction accurately is provided for user.
Fig. 7 is a kind of structural schematic diagram of the movement error correction device of human body attitude provided by the embodiments of the present application.Such as Fig. 7 institute
Show, which includes: the first video determining module 710, the first coordinate determining module 720, the second video acquiring module 730,
Two coordinate determining modules 740, error correction data determining module 750 and output module 760.
First video determining module 710, for determining the first video data according to instructional video；
First coordinate determining module 720, first video for being determined according to the first video determining module 710
Data determine the first human body coordinate data；
Second video acquiring module 730, for obtaining the second video data of user, second video data includes using
Family is according to the imitation image of first video data；
Second coordinate determining module 740, second video for being obtained according to second video acquiring module 730
Data determine the second human body coordinate data；
Error correction data determining module 750, first human body for being determined according to the first coordinate determining module 720
The second human body coordinate data that coordinate data and the second coordinate determining module 740 determine determines the first error correction data；
Output module 760, first error correction data determined for exporting the error correction data determining module 750.
Further, the first video determining module 710 is used for:
Instructional video is obtained according to destination address；
The positive mark of the instructional video is obtained, the positive mark includes at least one set of origin identification and cut-off mark
Know；
The first video data is obtained according to the origin identification and cut-off mark.
Further, the first video determining module 710 is used to obtain the first view according to the origin identification and cut-off mark
Frequency evidence, comprising:
It is identified if there is multiple groups positive, then obtains multiple first sub-video datas, each first sub-video data respectively
Corresponding one group of positive mark；
Splice the multiple first sub-video data, obtains the first video data.
Further, as shown in Figure 8, further includes: face characteristic processing module 770, limit movement processing module 780 and device
Tool processing module 790.
Face characteristic processing module 770, for after determining the first video data according to instructional video, according to described
Facial image in one video data determines the first expressive features；
The second expressive features are determined according to the face characteristic of user；
The second error correction data is determined according to first expressive features and second expressive features；
Export second error correction data.
It further, further include limit movement processing module 780, for determining first according to first video data
After human body coordinate data:
The limit for obtaining user acts coordinate data；
If the first human body coordinate data and limit movement coordinate data mismatch, dynamic according to the limit
Make coordinate data and adjust the first human body coordinate data, to make the movement limit of the first human body coordinate data matching user.
Further, further include instrument processing module 790, for according to instructional video determine the first video data it
Afterwards, comprising:
Instrument characteristics and the first instrument coordinate data are determined according to the first video data；
The instrument that user uses is identified according to the instrument characteristics, and obtains the second instrument coordinate of the used instrument of user
Data；
Third error correction data is determined according to the first instrument coordinate data and the second instrument coordinate data；
Export the third error correction data.
Further, the second video acquiring module 730 is used for: obtaining the second video data and described of the user
The corresponding depth information of two video datas；
User's 3 D human body coordinate data is determined according to second video data and the depth information；
Correspondingly, error correction data determining module 750 is used for:
Obtain the corresponding target 3 D human body coordinate data of the first human body coordinate data；
The 4th error correction number is determined according to the target 3 D human body coordinate data and user's 3 D human body coordinate data
According to.
The movement error correction device of the human body attitude provided in the embodiment of the present application, first the first video determining module 710 are used
In determining the first video data according to instructional video；First coordinate determining module 720, for determining mould according to first video
First video data that block 710 determines determines the first human body coordinate data；Then, the second video acquiring module 730, is used for
The second video data of user is obtained, second video data includes imitation figure of the user according to first video data
Picture；Second coordinate determining module 740, second video data for being obtained according to second video acquiring module 730
Determine the second human body coordinate data；Finally, error correction data determining module 750, for according to the first coordinate determining module 720
The second human body coordinate data that determining the first human body coordinate data and the second coordinate determining module 740 determine
Determine the first error correction data；Output module 760 is entangled for exporting the error correction data determining module 750 determines described first
Wrong data.Exist after the three-dimensional data of standard operation is manually entered in the related technology, it is dynamic using the three-dimensional data of standard and user
The three-dimensional data of work carries out the scheme than error correction, but the three-dimensional data needs of program Plays movement are manually defeated by programmer
Entering, the corresponding limbs state of every group of three-dimensional data is made of due to body-building movement multiple limbs states, one
Body-building movement needs to input a large amount of standard operation three-dimensional data, and then greatly improves make-up time and cost.The application is implemented
The movement error correction method for the human body attitude that example provides can determine error correction data, root based on the imitation image of instructional video and user
It can determine the first video data according to instructional video, the first human body coordinate data determined according to the first video data, the first human body is sat
Mark data are manually entered without programmer, therefore can quickly determine the first human body coordinate data, so that error correction is more
It is light to be easily achieved, the second video data of user can be obtained by front camera, and determine according to the second video data
Two human body coordinate datas, the second human body coordinate data can accurately embody user's limb action, sit by comparing the first human body
After marking data and the second human body coordinate data determination and exporting the first error correction data, error correcting prompt can be provided for user, accurately
Human body attitude is corrected, improve body-building effect.
Method provided by the aforementioned all embodiments of the application can be performed in above-mentioned apparatus, and it is corresponding to have the execution above method
Functional module and beneficial effect.The not technical detail of detailed description in the present embodiment, reference can be made to the aforementioned all implementations of the application
Method provided by example.
Fig. 9 is the structural schematic diagram of another terminal device provided by the embodiments of the present application.As shown in figure 9, the terminal can
To include: shell (not shown), memory 801, central processing unit (Central Processing Unit, CPU) 802
(also known as processor, hereinafter referred to as CPU), the computer program that is stored on memory 801 and can be run on processor 802,
Circuit board (not shown) and power circuit (not shown).Circuit board is placed in the space interior that shell surrounds；
CPU802 and the setting of memory 801 are on circuit boards；Power circuit, for each circuit or the device power supply for terminal；Storage
Device 801, for storing executable program code；CPU802 by read in memory 801 executable program code that stores come
Run program corresponding with executable program code.
Terminal further include: Peripheral Interface 803, voicefrequency circuit 806, is raised RF (Radio Frequency, radio frequency) circuit 805
Sound device 811, power management chip 808, input/output (I/O) subsystem 809, touch screen 812, other input/control devicess
810 and outside port 804, these components communicated by one or more communication bus or signal wire 807.
It should be understood that graphic terminal 800 is only an example of terminal, and terminal device 800 can be with
With than shown in the drawings more or less component, two or more components can be combined, or can have
Different component configurations.Various parts shown in the drawings can include one or more signal processings and/or dedicated integrated
It is realized in the combination of hardware, software or hardware and software including circuit.
Just provided in this embodiment below to be described in detail for a kind of terminal device, the terminal device is with intelligent hand
For machine.
Memory 801, memory 801 can be accessed by CPU802, Peripheral Interface 803 etc., and memory 801 may include height
Fast random access memory can also include nonvolatile memory, such as one or more disk memories, flash memories
Part or other volatile solid-state parts.
The peripheral hardware that outputs and inputs of equipment can be connected to CPU802 and memory by Peripheral Interface 803, Peripheral Interface 803
801。
I/O subsystem 809, I/O subsystem 809 can by the input/output peripheral in equipment, such as touch screen 812 and its
His input/control devices 810, is connected to Peripheral Interface 803.I/O subsystem 809 may include display controller 8091 and be used for
Control one or more input controllers 8092 of other input/control devicess 810.Wherein, one or more input controllers
8092 receive electric signal from other input/control devicess 810 or send electric signal to other input/control devicess 810, other
Input/control devices 810 may include physical button (push button, rocker buttons etc.), dial, slide switch, control stick,
Click idler wheel.It is worth noting that input controller 8092 can with it is following any one connect: front camera, postposition image
The indicating equipment of head, keyboard, infrared port, USB interface and such as mouse, special front camera include depth camera
Head.
Wherein, according to the working principle of touch screen and transmission information medium classification, touch screen 812 can for resistance-type,
Capacitor induction type, infrared-type or surface acoustic wave type.Classify according to mounting means, touch screen 812 can be with are as follows: external hanging type, built-in
Formula or monoblock type.Classify according to technical principle, touch screen 812 can be with are as follows: vector pressure sensing technology touch screen, resistive technologies touching
Touch screen, capacitance technology touch screen, infrared technology touch screen or surface acoustic wave technique touch screen.
Touch screen 812, touch screen 812 are the input interface and output interface between user terminal and user, will be visual defeated
It is shown to user out, visual output may include figure, text, icon, video etc..Optionally, touch screen 812 is touching user
The electric signal (electric signal of such as contact surface) triggered on screen, is sent to processor 802.
Display controller 8091 in I/O subsystem 809 receives electric signal from touch screen 812 or sends out to touch screen 812
Electric signals.Touch screen 812 detects the contact on touch screen, and the contact that display controller 8091 will test is converted to and is shown
The interaction of user interface object on touch screen 812, i.e. realization human-computer interaction, the user interface being shown on touch screen 812
Object can be the icon of running game, the icon for being networked to corresponding network etc..It is worth noting that equipment can also include light
Mouse, light mouse are the extensions for the touch sensitive surface for not showing the touch sensitive surface visually exported, or formed by touch screen.
RF circuit 805 is mainly used for establishing the communication of intelligent sound box Yu wireless network (i.e. network side), realizes intelligent sound box
Data receiver and transmission with wireless network.Such as transmitting-receiving short message, Email etc..
Voicefrequency circuit 806 is mainly used for receiving audio data from Peripheral Interface 803, which is converted to telecommunications
Number, and the electric signal is sent to loudspeaker 811.
Loudspeaker 811 is reduced to for intelligent sound box to be passed through RF circuit 805 from the received voice signal of wireless network
Sound simultaneously plays the sound to user.
Power management chip 808, the hardware for being connected by CPU802, I/O subsystem and Peripheral Interface are powered
And power management.
In the present embodiment, central processing unit 802 is used for:
The first video data is determined according to instructional video；
The first human body coordinate data is determined according to first video data；
The second video data of user is obtained, second video data includes user according to first video data
Imitate image；
The second human body coordinate data is determined according to second video data；
The first error correction data is determined according to the first human body coordinate data and the second human body coordinate data；
Export first error correction data.
It is further, described that first video data is determined according to instructional video, comprising:
Instructional video is obtained according to destination address；
The positive mark of the instructional video is obtained, the positive mark includes at least one set of origin identification and cut-off mark
Know；
The first video data is obtained according to the origin identification and cut-off mark.
It is further, described that first video data is obtained according to the origin identification and cut-off mark, comprising:
It is identified if there is multiple groups positive, then obtains multiple first sub-video datas, each first sub-video data respectively
Corresponding one group of positive mark；
Splice the multiple first sub-video data, obtains the first video data.
Further, after determining the first video data according to instructional video, comprising:
The first expressive features are determined according to the facial image in first video data；
The second expressive features are determined according to the face characteristic of user；
The second error correction data is determined according to first expressive features and second expressive features；
Export second error correction data.
Further, after determining the first human body coordinate data according to first video data, comprising:
The limit for obtaining user acts coordinate data；
If the first human body coordinate data and limit movement coordinate data mismatch, dynamic according to the limit
Make coordinate data and adjust the first human body coordinate data, to make the movement limit of the first human body coordinate data matching user.
Further, after determining the first video data according to instructional video, comprising:
Instrument characteristics and the first instrument coordinate data are determined according to the first video data；
The instrument that user uses is identified according to the instrument characteristics, and obtains the second instrument coordinate of the used instrument of user
Data；
Third error correction data is determined according to the first instrument coordinate data and the second instrument coordinate data；
Export the third error correction data.
Further, second video data for obtaining user, including；
Obtain the second video data and the corresponding depth information of second video data of the user；
User's 3 D human body coordinate data is determined according to second video data and the depth information；
Correspondingly, described determine the first error correction according to the first human body coordinate data and the second human body coordinate data
Data, comprising:
Obtain the corresponding target 3 D human body coordinate data of the first human body coordinate data；
The 4th error correction number is determined according to the target 3 D human body coordinate data and user's 3 D human body coordinate data
According to.
The embodiment of the present application also provides a kind of storage medium comprising terminal device executable instruction, and terminal device is executable
It instructs when being executed by terminal device processor for executing a kind of movement error correction method of human body attitude, this method comprises:
The first video data is determined according to instructional video；
The first human body coordinate data is determined according to first video data；
The second video data of user is obtained, second video data includes user according to first video data
Imitate image；
The second human body coordinate data is determined according to second video data；
The first error correction data is determined according to the first human body coordinate data and the second human body coordinate data；
Export first error correction data.
It is further, described that first video data is determined according to instructional video, comprising:
Instructional video is obtained according to destination address；
The positive mark of the instructional video is obtained, the positive mark includes at least one set of origin identification and cut-off mark
Know；
The first video data is obtained according to the origin identification and cut-off mark.
It is further, described that first video data is obtained according to the origin identification and cut-off mark, comprising:
It is identified if there is multiple groups positive, then obtains multiple first sub-video datas, each first sub-video data respectively
Corresponding one group of positive mark；
Splice the multiple first sub-video data, obtains the first video data.
Further, after determining the first video data according to instructional video, comprising:
The first expressive features are determined according to the facial image in first video data；
The second expressive features are determined according to the face characteristic of user；
The second error correction data is determined according to first expressive features and second expressive features；
Export second error correction data.
Further, after determining the first human body coordinate data according to first video data, comprising:
The limit for obtaining user acts coordinate data；
If the first human body coordinate data and limit movement coordinate data mismatch, dynamic according to the limit
Make coordinate data and adjust the first human body coordinate data, to make the movement limit of the first human body coordinate data matching user.
Further, after determining the first video data according to instructional video, comprising:
Instrument characteristics and the first instrument coordinate data are determined according to the first video data；
The instrument that user uses is identified according to the instrument characteristics, and obtains the second instrument coordinate of the used instrument of user
Data；
Third error correction data is determined according to the first instrument coordinate data and the second instrument coordinate data；
Export the third error correction data.
Further, second video data for obtaining user, including；
Obtain the second video data and the corresponding depth information of second video data of the user；
User's 3 D human body coordinate data is determined according to second video data and the depth information；
Correspondingly, described determine the first error correction according to the first human body coordinate data and the second human body coordinate data
Data, comprising:
Obtain the corresponding target 3 D human body coordinate data of the first human body coordinate data；
The 4th error correction number is determined according to the target 3 D human body coordinate data and user's 3 D human body coordinate data
According to.
The computer storage medium of the embodiment of the present application, can be using any of one or more computer-readable media
Combination.Computer-readable medium can be computer-readable signal media or computer readable storage medium.It is computer-readable
Storage medium for example may be-but not limited to-the system of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, device or
Device, or any above combination.The more specific example (non exhaustive list) of computer readable storage medium includes: tool
There are electrical connection, the portable computer diskette, hard disk, random access memory (RAM), read-only memory of one or more conducting wires
(ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-
ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.In this document, computer-readable storage
Medium can be any tangible medium for including or store program, which can be commanded execution system, device or device
Using or it is in connection.
Computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including but unlimited
In electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be that computer can
Any computer-readable medium other than storage medium is read, which can send, propagates or transmit and be used for
By the use of instruction execution system, device or device or program in connection.
The program code for including on computer-readable medium can transmit with any suitable medium, including --- but it is unlimited
In wireless, electric wire, optical cable, RF etc. or above-mentioned any appropriate combination.
Can with one or more programming languages or combinations thereof come write for execute the application operation computer
Program code, programming language include object oriented program language-such as Java, Smalltalk, C++, are also wrapped
Include conventional procedural programming language-such as " C " language or similar programming language.Program code can be complete
Ground executes on the user computer, partly executes on the user computer, executing as an independent software package, partially existing
Part executes on the remote computer or executes on a remote computer or server completely on subscriber computer.It is being related to
In the situation of remote computer, remote computer can pass through the network of any kind --- including local area network (LAN) or wide area
Net (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (such as utilize ISP
To be connected by internet).
Certainly, a kind of storage medium comprising computer executable instructions, computer provided by the embodiment of the present application
The application any embodiment institute can also be performed in the movement error-correction operation for the human body attitude that executable instruction is not limited to the described above
Offer using the relevant operation in recommended method.
Note that above are only the preferred embodiment and institute's application technology principle of the application.It will be appreciated by those skilled in the art that
The application is not limited to specific embodiment described here, be able to carry out for a person skilled in the art it is various it is apparent variation,
The protection scope readjusted and substituted without departing from the application.Therefore, although being carried out by above embodiments to the application
It is described in further detail, but the application is not limited only to above embodiments, in the case where not departing from the application design, also
It may include more other equivalent embodiments, and scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. a kind of movement error correction method of human body attitude characterized by comprising
The first video data is determined according to instructional video；
The first human body coordinate data is determined according to first video data；
The second video data of user is obtained, second video data includes imitation of the user according to first video data
Image；
The second human body coordinate data is determined according to second video data；
The first error correction data is determined according to the first human body coordinate data and the second human body coordinate data；
Export first error correction data.
2. the movement error correction method of human body attitude according to claim 1, which is characterized in that described true according to instructional video
Fixed first video data, comprising:
Instructional video is obtained according to destination address；
The positive mark of the instructional video is obtained, the positive mark includes at least one set of origin identification and cut-off mark；
The first video data is obtained according to the origin identification and cut-off mark.
3. the movement error correction method of human body attitude according to claim 2, which is characterized in that described to be marked according to the starting
Know and cut-off mark obtain the first video data, comprising:
It is identified if there is multiple groups positive, then obtains multiple first sub-video datas respectively, each first sub-video data is corresponding
One group of positive mark；
Splice the multiple first sub-video data, obtains the first video data.
4. the movement error correction method of human body attitude according to claim 1, which is characterized in that determined according to instructional video
After first video data, comprising:
The first expressive features are determined according to the facial image in first video data；
The second expressive features are determined according to the face characteristic of user；
The second error correction data is determined according to first expressive features and second expressive features；
Export second error correction data.
5. the movement error correction method of human body attitude according to claim 1, which is characterized in that according to first video
Data determine after the first human body coordinate data, comprising:
The limit for obtaining user acts coordinate data；
If the first human body coordinate data and limit movement coordinate data mismatch, is acted and sat according to the limit
The first human body coordinate data described in data point reuse is marked, to make the movement limit of the first human body coordinate data matching user.
6. the movement error correction method of human body attitude according to claim 1, which is characterized in that determined according to instructional video
After first video data, comprising:
Instrument characteristics and the first instrument coordinate data are determined according to the first video data；
The instrument that user uses is identified according to the instrument characteristics, and obtains the second instrument number of coordinates of the used instrument of user
According to；
Third error correction data is determined according to the first instrument coordinate data and the second instrument coordinate data；
Export the third error correction data.
7. the movement error correction method of human body attitude according to claim 1 to 6, which is characterized in that the acquisition
The second video data of user, including；
Obtain the second video data and the corresponding depth information of second video data of the user；
User's 3 D human body coordinate data is determined according to second video data and the depth information；
Correspondingly, described determine the first error correction number according to the first human body coordinate data and the second human body coordinate data
According to, comprising:
Obtain the corresponding target 3 D human body coordinate data of the first human body coordinate data；
The 4th error correction data is determined according to the target 3 D human body coordinate data and user's 3 D human body coordinate data.
8. a kind of movement error correction device of human body attitude characterized by comprising
First video determining module, for determining the first video data according to instructional video；
First coordinate determining module, first video data for being determined according to the first video determining module determine the
One human body coordinate data；
Second video acquiring module, for obtaining the second video data of user, second video data include user according to
The imitation image of first video data；
Second coordinate determining module, second video data for being obtained according to second video acquiring module determine
Two human body coordinate datas；
Error correction data determining module, for according to the first coordinate determining module determine the first human body coordinate data and
The second human body coordinate data that the second coordinate determining module determines determines the first error correction data；
Output module, first error correction data determined for exporting the error correction data determining module.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The movement error correction method of the human body attitude as described in any in claim 1-7 is realized when row.
10. a kind of terminal, including memory, processor and storage are on a memory and can be in the computer journey of processor operation
Sequence, which is characterized in that the processor realizes human body appearance as claimed in claim 1 when executing the computer program
The movement error correction method of state.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811379006.9A CN109331455A (en) | 2018-11-19 | 2018-11-19 | Movement error correction method, device, storage medium and the terminal of human body attitude |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811379006.9A CN109331455A (en) | 2018-11-19 | 2018-11-19 | Movement error correction method, device, storage medium and the terminal of human body attitude |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109331455A true CN109331455A (en) | 2019-02-15 |
Family
ID=65316461
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811379006.9A Pending CN109331455A (en) | 2018-11-19 | 2018-11-19 | Movement error correction method, device, storage medium and the terminal of human body attitude |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109331455A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109872297A (en) * | 2019-03-15 | 2019-06-11 | 北京市商汤科技开发有限公司 | Image processing method and device, electronic equipment and storage medium |
| CN110427864A (en) * | 2019-07-29 | 2019-11-08 | 腾讯科技（深圳）有限公司 | A kind of image processing method, device and electronic equipment |
| CN112237730A (en) * | 2019-07-17 | 2021-01-19 | 腾讯科技（深圳）有限公司 | Body-building action correcting method and electronic equipment |
| CN113409651A (en) * | 2020-03-16 | 2021-09-17 | 上海史贝斯健身管理有限公司 | Live broadcast fitness method and system, electronic equipment and storage medium |
| CN113641856A (en) * | 2021-08-12 | 2021-11-12 | 三星电子（中国）研发中心 | Method and apparatus for outputting information |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6236940B1 (en) * | 1995-09-08 | 2001-05-22 | Prolink, Inc. | Display monitor for golf cart yardage and information system |
| US6813586B1 (en) * | 1999-09-07 | 2004-11-02 | Phatrat Technology, Inc. | Event and sport performance methods and systems |
| CN103310193A (en) * | 2013-06-06 | 2013-09-18 | 温州聚创电气科技有限公司 | Method for recording important skill movement moments of athletes in gymnastics video |
| CN103390174A (en) * | 2012-05-07 | 2013-11-13 | 深圳泰山在线科技有限公司 | Physical education assisting system and method based on human body posture recognition |
| CN103637786A (en) * | 2013-10-29 | 2014-03-19 | 上海大学 | System and method for acquiring and detecting human body posture and physical energy information |
| CN107220596A (en) * | 2017-05-11 | 2017-09-29 | 西安电子科技大学 | Estimation method of human posture based on cascade mechanism for correcting errors |
-
2018
- 2018-11-19 CN CN201811379006.9A patent/CN109331455A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6236940B1 (en) * | 1995-09-08 | 2001-05-22 | Prolink, Inc. | Display monitor for golf cart yardage and information system |
| US6813586B1 (en) * | 1999-09-07 | 2004-11-02 | Phatrat Technology, Inc. | Event and sport performance methods and systems |
| CN103390174A (en) * | 2012-05-07 | 2013-11-13 | 深圳泰山在线科技有限公司 | Physical education assisting system and method based on human body posture recognition |
| CN103310193A (en) * | 2013-06-06 | 2013-09-18 | 温州聚创电气科技有限公司 | Method for recording important skill movement moments of athletes in gymnastics video |
| CN103637786A (en) * | 2013-10-29 | 2014-03-19 | 上海大学 | System and method for acquiring and detecting human body posture and physical energy information |
| CN107220596A (en) * | 2017-05-11 | 2017-09-29 | 西安电子科技大学 | Estimation method of human posture based on cascade mechanism for correcting errors |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109872297A (en) * | 2019-03-15 | 2019-06-11 | 北京市商汤科技开发有限公司 | Image processing method and device, electronic equipment and storage medium |
| CN112237730A (en) * | 2019-07-17 | 2021-01-19 | 腾讯科技（深圳）有限公司 | Body-building action correcting method and electronic equipment |
| CN110427864A (en) * | 2019-07-29 | 2019-11-08 | 腾讯科技（深圳）有限公司 | A kind of image processing method, device and electronic equipment |
| CN113409651A (en) * | 2020-03-16 | 2021-09-17 | 上海史贝斯健身管理有限公司 | Live broadcast fitness method and system, electronic equipment and storage medium |
| CN113409651B (en) * | 2020-03-16 | 2024-04-16 | 上海史贝斯健身管理有限公司 | Live broadcast body building method, system, electronic equipment and storage medium |
| CN113641856A (en) * | 2021-08-12 | 2021-11-12 | 三星电子（中国）研发中心 | Method and apparatus for outputting information |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109331455A (en) | Movement error correction method, device, storage medium and the terminal of human body attitude | |
| CN110531860B (en) | Animation image driving method and device based on artificial intelligence | |
| CN106254848B (en) | A kind of learning method and terminal based on augmented reality | |
| CN102789313B (en) | User interaction system and method | |
| CN104049721B (en) | Information processing method and electronic equipment | |
| JP2022502783A (en) | Image fusion method, model training method, image fusion device, model training device, terminal device, server device, and computer program | |
| US9129478B2 (en) | Attributing user action based on biometric identity | |
| KR102260721B1 (en) | Electronic device and method for executing a musical performance in the electronic device | |
| US10636417B2 (en) | Method and apparatus for performing voice recognition on basis of device information | |
| CN110389659A (en) | The system and method for dynamic haptic playback are provided for enhancing or reality environment | |
| WO2019087564A1 (en) | Information processing device, information processing method, and program | |
| CN109064387A (en) | Image special effect generation method, device and electronic equipment | |
| JPWO2018142756A1 (en) | Information processing apparatus and information processing method | |
| CN108109209A (en) | A kind of method for processing video frequency and its device based on augmented reality | |
| JP2012181809A (en) | Apparatus controller, apparatus control method, apparatus control program and integrated circuit | |
| KR20160065671A (en) | Device and method for outputting response | |
| CN110443769A (en) | Image processing method, image processing apparatus and terminal device | |
| CN109426343A (en) | Cooperation training method and system based on virtual reality | |
| CN108491076A (en) | Display control method and related product | |
| CN111225237B (en) | Sound and picture matching method of video, related device and storage medium | |
| CN108563327A (en) | Augmented reality method, apparatus, storage medium and electronic equipment | |
| CN109819167A (en) | A kind of image processing method, device and mobile terminal | |
| CN109254752A (en) | 3D sound effect treatment method and Related product | |
| CN113168282A (en) | Electronic device and method for generating augmented reality emoticons | |
| CN107967667A (en) | Generation method, device, terminal device and the storage medium of sketch |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190215 |