CN106774889A - The gesture identification method and device of wearable device - Google Patents
The gesture identification method and device of wearable device Download PDFInfo
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- CN106774889A CN106774889A CN201611159978.8A CN201611159978A CN106774889A CN 106774889 A CN106774889 A CN 106774889A CN 201611159978 A CN201611159978 A CN 201611159978A CN 106774889 A CN106774889 A CN 106774889A
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
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Abstract
The invention discloses a kind of wearable gesture identifying device, including acceleration sensor module, microprocessor module, wireless communication module, wherein：Acceleration sensor module is used to obtain current gesture；Microprocessor module is used to contrast current gesture and preset standard gesture, and generates control signal in the case where contrast is consistent；Wireless communication module is used to transmit control signal to mobile terminal device.The present invention further discloses a kind of gesture identification method of wearable device, the method comprising the steps of：S1：Preset standard gesture；S2：Current gesture is obtained by acceleration sensor module；S3：Current gesture and preset standard gesture are contrasted by microprocessor module, and control signal is generated in the case where contrast is consistent；S4：Control signal is transmitted to mobile terminal device by wireless communication module.By the apparatus and method, the accuracy rate of gesture identification is effectively increased.
Description
Technical field
The present invention relates to the wearable gesture identifying device technical field of intelligence, more particularly to a kind of wearable smart machine hand
Gesture knows recognition methods and its device.
Background technology
The popularization of Intelligent mobile equipment and smart home makes the equipment based on Android operation system be liked by masses deeply,
And as the prevalence of brief philosophy of life, the Android device mode of operation of diversification are easier to allow people to receive, the present invention is carried
A kind of wearable gesture identifying device is supplied, there is provided a kind of more convenient Android device control method:Gesture identification
Control.
Because the posture of human hands action is complicated, it will usually with continuous action so that gesture identification turns into grinds at present
One of problem studied carefully.The method of current gesture identification has a lot, some use muscular movement sensors, by the electricity for detecting muscle
Position carries out gesture judgement, and also catching human hands using first-class optical image sensing device is imaged acts to judge gesture.
Most of knowledge method for distinguishing are all more complicated on the market now, and device volume is larger, uses inconvenience, gesture identification
Rate is not high.
Also there is the sensor that many wearable devices use MPU6050 as gesture identification on the market at present, but it is most normal
With mode be that the initial data of direct access MPU6050 is judged, so causing gesture identification rate not high.
The content of the invention
In view of the shortcomings of the prior art, it is an object of the invention to provide a kind of wearable gesture identifying device.
To achieve the above object, a kind of wearable gesture identifying device, including acceleration be the embodiment of the invention provides
Sensor assembly, microprocessor module, wireless communication module, wherein：
Acceleration sensor module is used to obtain current gesture information, and current gesture information is sent into microprocessor mould
Block；
Microprocessor module is used to contrast current gesture information and preset standard gesture information, and is contrasting consistent feelings
Control signal is generated under condition；
Wireless communication module is used to transmit control signal to mobile terminal device.
Compared with prior art, wearable gesture identifying device disclosed by the invention is obtained by acceleration sensor module
Current gesture information is taken, current gesture information and preset standard gesture information is contrasted by microprocessor module, contrast is consistent
In the case of generate control signal, control signal is transmitted to mobile terminal device by wireless communication module, solve existing skill
Art discrimination problem not high, effectively increases the accuracy rate of gesture identification.
According to another specific embodiment of the invention, acceleration sensor module includes three axis accelerometer, three axis accelerometer
Instrument, digital moving processor DMP modules and IIC interfaces, acceleration sensor module pass through IIC interfaces and microprocessor module
Connection.
According to another specific embodiment of the invention, wireless communication module includes bluetooth module, and bluetooth module passes through serial ports
It is connected with microprocessor module.
The embodiment of the present invention additionally provides a kind of gesture identification method of wearable device, including wearable device includes adding
Acceleration sensor module, microprocessor module, wireless communication module, method comprise the following steps：
S1：Preset standard gesture, microprocessor module is stored in by standard gesture information；
S2：Current gesture information is obtained by acceleration sensor module, current gesture information include acceleration information and
Quaternary number information；
S3：Current gesture information and preset standard gesture information are contrasted by microprocessor module, and it is consistent in contrast
In the case of generate control signal；
S4：Control signal is transmitted to mobile terminal device by wireless communication module.
Compared with prior art, the gesture identification method of wearable device disclosed by the invention passes through preset standard gesture,
Current gesture information is obtained by acceleration transducer, by microprocessor module by current gesture information and preset standard gesture
Information is contrasted, and when contrasting consistent, is generated control signal and is transmitted to mobile terminal device control signal by wireless communication module,
Prior art discrimination problem not high is this method solve, the gesture identification accuracy rate of wearable device is effectively increased.
According to another specific embodiment of the invention, step S3 specifically includes step：
S31：Acceleration information and quaternary number information coordinate are converted by microprocessor module, is obtained under XYZ coordinate system
3-axis acceleration.
S32：The waveform discrete data that 3-axis acceleration obtains current gesture is processed by microprocessor module.
S33：By microprocessor module contrast the waveform discrete data of current gesture and the waveform of preset standard gesture from
Dissipate data.
S34：In the waveform discrete data of current gesture and the consistent waveform discrete data contrast of default standard gesture,
3-axis acceleration is carried out by direction of displacement and displacement that quadratic integral obtains current gesture by microprocessor, and according to working as
The displacement of preceding gesture and direction generation control signal.
Acceleration information and quaternary number information processing are obtained waveform discrete data by the present invention by microprocessor module, are led to
Cross and judge whether the method that is matched with the waveform discrete data of preset standard gesture judges for the waveform discrete data of current gesture
User gesture, determines whether gesture is correct, improves the accurate of gesture identification again by carrying out quadratic integral to 3-axis acceleration
Rate.
According to another specific embodiment of the invention, preset standard gesture includes：Move upwards, move downward, transporting to the left
Move, move right.
According to another specific embodiment of the invention, step S1 comprises the following steps：
S11：The acceleration information and quaternary number information of each preset standard gesture are obtained by acceleration sensor module；
S12：The acceleration information of each preset standard gesture and quaternary number information coordinate are become by microprocessor module
Change, obtain the 3-axis acceleration under each preset standard gesture XYZ coordinate system；
S13：The 3-axis acceleration under each preset standard gesture XYZ coordinate system is processed by microprocessor module to obtain often
The waveform discrete data of one preset standard gesture.
According to another specific embodiment of the invention, acceleration sensor module includes three axis accelerometer, three axis accelerometer
Instrument, digital moving processor DMP modules and IIC interfaces, acceleration sensor module pass through IIC interfaces and microprocessor module
Connection.
According to another specific embodiment of the invention, wireless communication module includes bluetooth module, and bluetooth module passes through serial ports
It is connected with microprocessor module.
The gesture identification method and device of the wearable device that the present invention is provided, are obtained by acceleration sensor module and marked
Quasi- gesture 3-axis acceleration, quaternary number initial data, the waveform dispersion number by obtaining standard gesture after micro treatment module treatment
According to；During specific implementation, current gesture 3-axis acceleration, quaternary number are obtained by acceleration sensor module, by microprocessor
Resume module obtains the waveform discrete data of current gesture, and the waveform dispersion number of gesture before deserving is contrasted by microprocessor module
According to the waveform discrete data with preset standard gesture, so that it is determined that the direction of current gesture and displacement in this direction, according to
Comparing result, generates control signal, and transmit to mobile terminal device the control signal by without letter communication module.The present invention
Embodiment effectively increases the gesture identification accuracy rate of wearable device by preset standard gesture, the method for real time contrast.
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Brief description of the drawings
Fig. 1 is the structured flowchart of the wearable gesture identifying device of embodiment 1；
Fig. 2 is the flow chart of the gesture identification method of the wearable device of embodiment 2；
Fig. 3 is the flow chart of step S1 in Fig. 2；
Fig. 4 is the flow chart of step S3 in Fig. 2.
Specific embodiment
Embodiment 1
It is the structural representation of a kind of wearable gesture identifying device that the present embodiment is provided referring to Fig. 1.The present embodiment
The wearable gesture identifying device for providing includes acceleration sensor module 1, microprocessor module 2, wireless communication module 3,
Wherein：
Acceleration sensor module 1 is used to obtain current gesture information, and current gesture information is sent into microprocessor
Module 2；
Microprocessor module 2 is used to contrast current gesture information and preset standard gesture information, and consistent contrasting
In the case of generate control signal；
Wireless communication module 3 is used to transmit control signal to mobile terminal device.
In the present embodiment, acceleration sensor module 1 is used to obtain acceleration, four of preset standard gesture and current gesture
First number.Acceleration sensor module 1 include three axis accelerometer, three-axis gyroscope, digital moving processor DMP modules and
IIC interfaces, acceleration sensor module 1 is connected by IIC interfaces with microprocessor module 2, i.e., acceleration sensor module 1 is led to
Crossing IIC data/address bus will obtain acceleration, the quaternary number original data transmissions to microprocessor module 2 of gesture.Preferably, accelerate
Degree sensor assembly 1 is MPU6050 modules.DMP (Digital Motion Processing) module is that MPU6050 is carried
Digital moving processor, and InvenSense companies provide an embedded DMP Driver Library of MPU6050, by DMP storehouses
Drive MPU6050 to read initial data, be directly changed into the output of quaternary number.The process that quaternary number is resolved by formula is simplified,
Improve PDR.
In the present embodiment, microprocessor module 2 is used to contrast current gesture information with default gesture information, and to one
During cause, control signal is generated.Preferably, microprocessor module 2 is STM32F103 single-chip microcomputers.
In the present embodiment, wireless communication module 3 is used to transmit control signal to mobile terminal device.Wireless communication module
3 include bluetooth module, and bluetooth module is connected by serial ports with microprocessor module 2.Preferably, bluetooth module is CC2540, micro-
Processor module 2 realizes the data interaction with mobile terminal device by the bluetooth module.
In the present embodiment, it is preferable that mobile terminal device is Android device.
During specific implementation, the IIC and USART of STM32F103 single-chip microcomputers are initialized first, then by MPU6050
Module initialization, the digital moving processor DMP that STM32F103 single-chip microcomputers are passed through into DMP library initialization MPU6050 inside modules
Module, the acceleration of current gesture, quaternary number, STM32F103 single-chip microcomputers are obtained by digital moving processor DMP modules in real time
By IIC agreements read acceleration, quaternary number, and acceleration, quaternary number are carried out coordinate transform obtain under XYZ coordinate system three
3-axis acceleration treatment under XYZ coordinate system is obtained axle acceleration, STM32F103 single-chip microcomputers the waveform dispersion number of current gesture
According to, and the waveform discrete data of the waveform discrete data and preset standard gesture is contrasted, when contrasting consistent, output control letter
Number, the control signal to be transmitted to Android device by CC2540 bluetooth modules, Android device is done according to the control signal
Go out reaction.
Wearable gesture identifying device disclosed in the present embodiment is obtained by digital moving processor DMP modules works as remote holder
The acceleration of gesture, quaternary number, are contrasted current gesture information and preset standard gesture information by STM32F103 single-chip microcomputers, right
Than generating control signal in the case of consistent, control signal is transmitted to Android device by CC2540 bluetooth modules, solved
Prior art discrimination problem not high, effectively increases the accuracy rate of gesture identification.
Embodiment 2
It is a kind of gesture identification method of wearable device that the present embodiment is provided referring to Fig. 2.Wearable device includes adding
Acceleration sensor module, microprocessor module, wireless communication module, the method comprise the following steps：
S1：Preset standard gesture, microprocessor module is stored in by standard gesture information.
The step is used for preset standard gesture.Specifically, standard gesture includes：Move upwards, move downward, transporting to the left
Move, move right.
Referring to Fig. 3, the step comprises the following steps：
S11：The acceleration information and quaternary number information of each preset standard gesture are obtained by acceleration sensor module.
Specifically, in the present embodiment, acceleration sensor module includes three axis accelerometer, three-axis gyroscope, numeral fortune
Dynamic processor DMP modules and IIC interfaces, acceleration sensor module are connected by IIC interfaces with microprocessor module, that is, add
Acceleration sensor module will obtain acceleration, the quaternary number original data transmissions to microprocessor of gesture by IIC data/address bus
Module.Preferably, acceleration sensor module is MPU6050 modules.DMP (Digital Motion Processing) module
It is digital moving processor that MPU6050 is carried, and InvenSense companies provide an embedded DMP of MPU6050
Driver Library, drives MPU6050 to read initial data by DMP storehouses, is directly changed into the output of quaternary number.Simplify by Formula Solution
The process of quaternary number is calculated, PDR is improve.
S12：The acceleration information of each preset standard gesture and quaternary number information coordinate are become by microprocessor module
Change, obtain the 3-axis acceleration under each preset standard gesture XYZ coordinate system.
S13：The 3-axis acceleration under each preset standard gesture XYZ coordinate system is processed by microprocessor module to obtain often
The waveform discrete data of one preset standard gesture.
S2：Current gesture information is obtained by acceleration sensor module, current gesture information include acceleration information and
Quaternary number information.
S3：Current gesture information and preset standard gesture information are contrasted by microprocessor module, and it is consistent in contrast
In the case of generate control signal.
The step is used to contrast current gesture information and preset standard gesture information.In the present embodiment, it is preferable that microprocessor
Device module is STM32F103 single-chip microcomputers.
Referring to Fig. 4, the step comprises the following steps：
S31：Acceleration information and quaternary number information coordinate are converted by microprocessor module, is obtained under XYZ coordinate system
3-axis acceleration.
S32：The waveform discrete data that 3-axis acceleration obtains current gesture is processed by microprocessor module.
S33：By microprocessor module contrast the waveform discrete data of current gesture and the waveform of preset standard gesture from
Dissipate data.
S34：In the waveform discrete data of current gesture and the consistent waveform discrete data contrast of default standard gesture,
3-axis acceleration is carried out by direction of displacement and displacement that quadratic integral obtains current gesture by microprocessor, and according to working as
The displacement of preceding gesture and direction generation control signal.
S4：Control signal is transmitted to mobile terminal device by wireless communication module.
The step is used for transmission of control signals.Specifically, wireless communication module includes bluetooth module, bluetooth module is by string
Mouth is connected with microprocessor module.Preferably, bluetooth module is CC2540, microprocessor module by the bluetooth module realize with
The data interaction of mobile terminal device.
In the present embodiment, it is preferable that mobile terminal device is Android device.
During specific implementation, the three of preset standard gesture are obtained by digital moving processor DMP modules in MPU6050 modules
Axle acceleration, quaternary number initial data, the initial data for processing the preset standard gesture by STM32F103 single-chip microcomputers obtain pre-
The waveform discrete data of quasi- gesture is marked with, and it is mono- that the waveform discrete data of the preset standard gesture is stored in into STM32F103
In piece machine；The 3-axis acceleration of current gesture, four are obtained by digital moving processor DMP modules in MPU6050 modules in real time
First number, the waveform discrete data for obtaining current gesture is processed by microprocessor module, is contrasted by microprocessor module and deserved
The waveform discrete data of preceding gesture and the waveform discrete data of preset standard gesture, so that it is determined that the direction of current gesture and should
Displacement on direction, according to comparing result, generates control signal, and transmit to shifting the control signal by without letter communication module
Dynamic terminal device.
The present embodiment is by using digital moving processor DMP acquisition preset standard gestures in MPU6050 modules and currently
The 3-axis acceleration of gesture, quaternary number initial data, initial data is processed by STM32F103 single-chip microcomputers, obtains preset standard
The waveform discrete data of gesture and current gesture, and it is mono- that the waveform discrete data of preset standard gesture is pre-stored in into STM32F103
In piece machine, during specific implementation, the waveform discrete data of the current gesture that will be acquired in real time and the waveform of preset standard gesture
Discrete data is contrasted, and when contrasting consistent, generates control signal, controls Android device, and the present embodiment passes through preset standard hand
Gesture, the method for real time contrast effectively increases the gesture identification accuracy rate of wearable device.
Although the present invention is disclosed above with preferred embodiment, the scope of present invention implementation is not limited to.Any
The those of ordinary skill in field, is not departing from invention scope of the invention, when that can make a little improvement, i.e., every according to this hair
Bright done equal improvement, should be the scope of the present invention and is covered.
Claims (9)
1. a kind of wearable gesture identifying device, it is characterised in that including acceleration sensor module, microprocessor module,
Wireless communication module, wherein：
The acceleration sensor module is used to obtain current gesture information, and current gesture information is sent into the microprocessor
Device module；
The microprocessor module is used to contrast current gesture information and preset standard gesture information, and is contrasting consistent feelings
Control signal is generated under condition；
The wireless communication module is used to transmit the control signal to mobile terminal device.
2. wearable gesture identifying device as claimed in claim 1, it is characterised in that the acceleration sensor module bag
Include three axis accelerometer, three-axis gyroscope, digital moving processor DMP modules and IIC interfaces, the acceleration transducer mould
Block is connected by IIC interfaces with the microprocessor module.
3. wearable gesture identifying device as claimed in claim 1, it is characterised in that the wireless communication module includes indigo plant
Tooth module, the bluetooth module is connected by serial ports with the microprocessor module.
4. a kind of gesture identification method of wearable device, it is characterised in that the wearable device includes acceleration transducer
Module, microprocessor module, wireless communication module, methods described comprise the following steps：
S1：Preset standard gesture, microprocessor module is stored in by the standard gesture information；
S2：Current gesture information is obtained by acceleration sensor module, the current gesture information include acceleration information and
Quaternary number information；
S3：Current gesture information and preset standard gesture information are contrasted by microprocessor module, and is contrasting consistent feelings
Control signal is generated under condition；
S4：The control signal is transmitted to mobile terminal device by wireless communication module.
5. the gesture identification method of wearable device as claimed in claim 4, it is characterised in that step S3 specifically includes step
Suddenly：
S31：The acceleration information and the quaternary number information coordinate are converted by the microprocessor module, obtains XYZ
3-axis acceleration under coordinate system；
S32：The waveform discrete data that the 3-axis acceleration obtains the current gesture is processed by the microprocessor module；
S33：The waveform discrete data of the current gesture and the ripple of preset standard gesture are contrasted by the microprocessor module
Shape discrete data；
S34：In the waveform discrete data of current gesture and the consistent waveform discrete data contrast of default standard gesture, pass through
The 3-axis acceleration is carried out direction of displacement and displacement that quadratic integral obtains the current gesture by the microprocessor,
And displacement and direction generation control signal according to the current gesture.
6. the gesture identification method of wearable device as claimed in claim 5, it is characterised in that the preset standard gesture bag
Include：Move upwards, move downward, to left movement, move right.
7. the gesture identification method of wearable device as claimed in claim 6, it is characterised in that the step S1 includes as follows
Step：
S11：The acceleration information and quaternary number information of each preset standard gesture are obtained by acceleration sensor module；
S12：The acceleration information of each preset standard gesture and quaternary number information coordinate are become by microprocessor module
Change, obtain the 3-axis acceleration under each preset standard gesture XYZ coordinate system；
S13：The 3-axis acceleration under each preset standard gesture XYZ coordinate system is processed by microprocessor module to obtain often
The waveform discrete data of preset standard gesture described in.
8. the gesture identification method of wearable device as claimed in claim 4, it is characterised in that the acceleration transducer mould
Block includes three axis accelerometer, three-axis gyroscope, digital moving processor DMP modules and IIC interfaces, the acceleration sensing
Device module is connected by IIC interfaces with the microprocessor module.
9. the gesture identification method of wearable device as claimed in claim 4, it is characterised in that the wireless communication module bag
Bluetooth module is included, the bluetooth module is connected by serial ports with the microprocessor module.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107450672A (en) * | 2017-09-19 | 2017-12-08 | 曾泓程 | A kind of wrist intelligent apparatus of high discrimination |
| CN108648205A (en) * | 2018-05-07 | 2018-10-12 | 广州大学 | A kind of sub-pixel edge detection method |
| CN111193832A (en) * | 2020-04-10 | 2020-05-22 | 杭州脸脸会网络技术有限公司 | Method for calculating speed and direction of parabolic motion based on mobile phone gyroscope sensor |
| CN111857347A (en) * | 2020-07-24 | 2020-10-30 | 惠州Tcl移动通信有限公司 | Mobile terminal control method, system, storage medium and mobile terminal |
| CN112947771A (en) * | 2021-01-11 | 2021-06-11 | 上海龙旗科技股份有限公司 | Method, device and equipment for realizing space trajectory input |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020009972A1 (en) * | 2000-07-06 | 2002-01-24 | Brian Amento | Bioacoustic control system, method and apparatus |
| CN104914991A (en) * | 2015-03-17 | 2015-09-16 | 广州大学 | Wearable intelligent bracelet gesture recognition method and device |
| CN105302021A (en) * | 2015-10-23 | 2016-02-03 | 哈尔滨工业大学 | Wearable gesture control device for controlling movement of robot in human-computer collaborative remanufacturing |
| CN105872871A (en) * | 2016-03-31 | 2016-08-17 | 中国地质大学（武汉） | Multi-degree of freedom Bluetooth headset based on nine-axis attitude fusion algorithm |
| CN106020364A (en) * | 2016-06-30 | 2016-10-12 | 佛山科学技术学院 | Smart bracelet with searching function of mute mobile phone and hand gesture recognition method |
-
2016
- 2016-12-15 CN CN201611159978.8A patent/CN106774889B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020009972A1 (en) * | 2000-07-06 | 2002-01-24 | Brian Amento | Bioacoustic control system, method and apparatus |
| CN104914991A (en) * | 2015-03-17 | 2015-09-16 | 广州大学 | Wearable intelligent bracelet gesture recognition method and device |
| CN105302021A (en) * | 2015-10-23 | 2016-02-03 | 哈尔滨工业大学 | Wearable gesture control device for controlling movement of robot in human-computer collaborative remanufacturing |
| CN105872871A (en) * | 2016-03-31 | 2016-08-17 | 中国地质大学（武汉） | Multi-degree of freedom Bluetooth headset based on nine-axis attitude fusion algorithm |
| CN106020364A (en) * | 2016-06-30 | 2016-10-12 | 佛山科学技术学院 | Smart bracelet with searching function of mute mobile phone and hand gesture recognition method |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107450672A (en) * | 2017-09-19 | 2017-12-08 | 曾泓程 | A kind of wrist intelligent apparatus of high discrimination |
| CN107450672B (en) * | 2017-09-19 | 2024-03-29 | 曾泓程 | Wrist type intelligent device with high recognition rate |
| CN108648205A (en) * | 2018-05-07 | 2018-10-12 | 广州大学 | A kind of sub-pixel edge detection method |
| CN111193832A (en) * | 2020-04-10 | 2020-05-22 | 杭州脸脸会网络技术有限公司 | Method for calculating speed and direction of parabolic motion based on mobile phone gyroscope sensor |
| CN111857347A (en) * | 2020-07-24 | 2020-10-30 | 惠州Tcl移动通信有限公司 | Mobile terminal control method, system, storage medium and mobile terminal |
| CN112947771A (en) * | 2021-01-11 | 2021-06-11 | 上海龙旗科技股份有限公司 | Method, device and equipment for realizing space trajectory input |
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| CN106774889B (en) | 2020-09-11 |
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