CN206270980U - A kind of motion capture gloves for gesture identification - Google Patents
A kind of motion capture gloves for gesture identification Download PDFInfo
- Publication number
- CN206270980U CN206270980U CN201621064325.7U CN201621064325U CN206270980U CN 206270980 U CN206270980 U CN 206270980U CN 201621064325 U CN201621064325 U CN 201621064325U CN 206270980 U CN206270980 U CN 206270980U
- Authority
- CN
- China
- Prior art keywords
- attitude
- sensing module
- attitude sensing
- motion capture
- joint
- 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.)
- Active
Links
Landscapes
- Position Input By Displaying (AREA)
Abstract
The utility model belongs to human-computer interaction technique field, discloses a kind of motion capture gloves for gesture identification, and the finger position at each joint two ends of glove bulk is respectively mounted an attitude sensing module；Attitude sensing module is at least integrated with a three axis MEMS gyro, 3 axis MEMS accelerometer and magnetic sensor and sensing microprocessor；Each attitude sensing module is connected by socket with glove bulk, and socket is mounted on the soft arranging wire of glove bulk inside arrangement, and each attitude sensing module is connected by soft arranging wire with the hub.The utility model is provided in motion capture gloves, using conveniently replaced attitude sensing module hardware plan, when the failure of a certain attitude sensing module causes attitude detection result mistake, user easily can change to it, due to that the complex operations such as need not weld, the maintenance difficulties and maintenance cost of dynamic hunter's set are reduced.
Description
Technical field
The utility model belongs to human-computer interaction technique field, is caught more particularly, to a kind of action for gesture identification
Catch gloves.
Background technology
Gesture motion is important interactive mode during people interact with the external world.People use gesture to act and carry out table
Up to thought, perceive objective world and complete various operations.With the fast development of virtual reality technology, by using motion capture
Equipment gathers human body gesture information, can greatly enrich the design content of virtual reality, increases the playability of content, improves people
The efficiency of machine interaction, widens the range of application of virtual reality system.
Data glove is to carry out the very important input equipment of hand motion capture in current virtual reality system, and it can be with
The flexible gesture attitudes vibration of tracking measurement wearer, is sent to processing unit in real time, finally weighs in the display system
Existing hand exercise.The high speed development of virtual reality technology promotes the application of hand motion capture technology.Motion capture gloves with
By means of its naturally efficient human-computer interaction mode, in Entertainment, animation, operation teaching, Sign Language Recognition, visualization science
It is used widely in the fields such as research, robot control.Traditional gesture motion measuring system mainly has mechanical and optical profile type
Two major classes.Mechanical such as Dexta Robotics hand motion capture equipment Dexmo, optical profile type such as Leap Motion companies
Visual identity gesture-capture.Mechanical gesture-capture system principle and structure are relative complex, and maintenance cost is high and is received in the presence of motion
Limit.Optical profile type gesture-capture system operating mode is complicated, is influenceed greatly by light condition and obstruction conditions, while by big using scope
Small limitation.
Compared with the sensing technology used in traditional gesture-capture system, MEMS (Micro-Electro-
Mechanic System, MEMS) sensor have small volume, lightweight, reliability high, low cost, be easy to large-scale production etc.
Advantage.Recently as the popularization of MEMS technology and the decline of its price, MEMS possesses wide future in engineering applications, especially
It is significant to the virtual reality system application of volume and cost sensitivity.Inertia is used art describes one kind
Senser element carries out the data glove of hand gestures detection.Each integrated microsensor of the data glove is by one three
Axle MEMS gyroscope, 3 axis MEMS accelerometer and magnetic sensor composition, and embedded Multi-sensor Fusion algorithm and be used for
The attitudes vibration in each joint is measured, and then realizes the resolving of gesture attitude.But the data glove is former based on inertia sensing
Reason, its integrated attitude heading reference system encapsulation on circuit boards, and is connected to data acquisition and control module by wire.The party
Attitude heading reference system is still and is realized on circuit boards by by the attachment of single gyroscope, accelerometer and Magnetic Sensor in case,
When some sensor goes wrong causes attitude heading reference system unavailable, changing attitude heading reference system will be inconvenient.
Utility model content
For the disadvantages described above or Improvement requirement of prior art, the utility model provides a kind of for the dynamic of gesture identification
Make seizure gloves, its object is to use conveniently replaced attitude sensing module hardware plan, reduce the maintenance of dynamic hunter's set
Difficulty and maintenance cost, and further eliminate because the initial attitude quaternary number of attitude sensing module caused by installation deviation is missed
Difference, realizes that high-precision gesture motion catches.
To achieve these goals, the utility model provides a kind of motion capture gloves for gesture identification, including
Attitude sensing module, glove bulk and the hub of glove bulk end is arranged on, wherein：
Finger position at each joint two ends of the glove bulk is respectively mounted an attitude sensing module；
The attitude sensing module is at least integrated with a three axis MEMS gyro, 3 axis MEMS accelerometer and three axle magnetic
Sensor and sensing microprocessor；The three-axis gyroscope is used to measure the angular speed of hand exercise, and three axis accelerometer is used for
The acceleration of hand exercise is measured, earth's magnetic field size when magnetic sensor is used to measure hand exercise under different azimuth is passed
Sense microprocessor is used to merge the data of multisensor measurement, obtains the attitude of each joint motions of hand and exports attitude quaternary
Number；
Described each attitude sensing module is connected by socket with the glove bulk, and the socket is mounted on the gloves
On the soft arranging wire of body interior arrangement, each attitude sensing module is connected by soft arranging wire with the hub.
In one embodiment of the present utility model, the hub internal is integrated with calibration microprocessor and launches with signal
Module, wherein：
The calibration microprocessor is used to receive each joint attitude quaternion of each attitude sensing module collection；
The signal emission module is used to for each joint attitude quaternion to be transferred to corresponding display device, realizes
Gesture motion catches.
In one embodiment of the present utility model, the calibration microprocessor is additionally operable to each joint attitude quaternary
Number carries out position deviation calibration.
In one embodiment of the present utility model, the calibration microprocessor is according to initial deviation quaternary number to described each
Each joint attitude quaternion of attitude sensing module collection carries out position deviation calibration.
In one embodiment of the present utility model, the calibration microprocessor closes up when keeping flat naturally according to five fingers
The output quaternary number of the initial quaternary number of theory and each attitude sensing module under each local joint coordinate system calculates described first
Beginning deviation quaternary number.
In one embodiment of the present utility model, the initial deviation quaternary numberForIts
Middle i=1,2...16, it is describedIt is the output quaternary number of attitude sensing module, it is describedKept flat for five fingers close up naturally
When each local joint coordinate system under the initial quaternary number of theory.
In one embodiment of the present utility model, the attitude sensing module has 16.
In one embodiment of the present utility model, 15 attitude sensing modules are placed between every finger-joint, the
16 attitude sensing modules are arranged at the back of the hand or palm.
Compared with prior art, the utility model has the advantages that：
(1) during the utility model provides motion capture gloves, the attitude sensing module for using is directly clamped among PLCC sockets
On, PLCC sockets are then mounted on the flexible base board on gloves, and the small size of sensing module meets the demand of hand flexible motion；
(2) during the utility model provides motion capture gloves, using conveniently replaced attitude sensing module hardware side
Case, when the failure of a certain attitude sensing module causes attitude detection result mistake, user easily can change to it, by
In that the complex operations such as need not weld, the maintenance difficulties and maintenance cost of dynamic hunter's set are reduced.Also, user can freely select
Whether need install whole attitude sensing modules, the occasion for not needing all fingers movable information can be according to reality if selecting
The appropriate usage quantity for reducing gesture module；
(3) during the utility model provides motion capture gloves, attitude sensing module exports the hand represented with quaternary number
Attitude information, due to describing hand joint motion using quaternary number, quaternary number does not exist singular point during description rotary motion,
The resolving instability problem caused when the angle of pitch is close near ± 90 ° using Eulerian angles method for expressing can be avoided；
(4) the utility model provides motion capture gloves, in subsequent calibration procedure, can be with the method table of quaternary number
Show the initial inclined of module installation, and calibrated for error by attitude sensing module, can eliminate because installation deviation causes
Initial attitude sensing module attitude quaternion error, eliminate the influence of initial installation deviation to hand motion capture, improve
The certainty of measurement of attitude sensing system, realizes that high-precision gesture motion catches, it is ensured that the availability of dynamic hunter's set.
Brief description of the drawings
Fig. 1 is the hardware architecture diagram of motion capture gloves in the utility model embodiment；
Fig. 2 is attitude sensing module and HUB folding connection diagrams in the utility model embodiment；
Fig. 3 is the initial installation deviation schematic diagram of attitude sensing system in the utility model embodiment.
Specific embodiment
In order that the purpose of this utility model, technical scheme and advantage become more apparent, below in conjunction with accompanying drawing and implementation
Example, is further elaborated to the utility model.It should be appreciated that specific embodiment described herein is only used to explain
The utility model, is not used to limit the utility model.Additionally, institute in the utility model disclosed below each implementation method
As long as the technical characteristic being related to does not constitute conflict and can just be mutually combined each other.
For the problem above of prior art, the utility model devises a kind of motion capture hand for gesture identification
Set, the attitude sensing system mounting structure of the snap socket formula that the gloves use can be mounted, when a certain attitude sensing system occurs
During problem, attitude sensing system module can be directly changed and without involving the connecting wire between attitude sensing system, the later stage
Safeguard simpler convenience.And the movable information different from describing hand joint using Eulerian angles in the prior art, this reality
Moved with the new middle hand joint that described using quaternary number, singular point problem when quaternary number is in the absence of description rotary motion,
The resolving instability problem caused when the angle of pitch is close near ± 90 ° using Eulerian angles method for expressing can be avoided.
The hardware composition of the motion capture gloves for gesture identification that the utility model is provided is as shown in figure 1, main bag
Include attitude sensing module, glove bulk and be arranged on the parts such as the hub HUB of glove bulk end.The hand bone of people can
To be divided into 16 pieces, the finger position at each joint two ends is respectively mounted an attitude sensing module on gloves.Specifically, can be by 15
Individual attitude sensing module is placed between every finger-joint, and the 16th attitude sensing module is arranged at the back of the hand or palm.Appearance
The integrated three axis MEMS gyro of state sensing module, 3 axis MEMS accelerometer, magnetic sensor and sensing microprocessor.
Three-axis gyroscope is used for measuring the angular speed of hand exercise；Three axis accelerometer is used for measuring the acceleration of hand exercise；Three axles
The earth's magnetic field size under different azimuth during Magnetic Sensor measurement hand exercise；Sensing microprocessor is responsible for multisensor measurement number
According to fusion, obtain the attitude of each joint motions of hand and export attitude quaternion.
As shown in Fig. 2 each attitude sensing module passes through socket (such as special pin chip package (Plastic
Leaded Chip Carrier, PLCC) socket) it is connected with glove bulk.The PLCC sockets are mounted in the glove bulk
On the soft arranging wire of portion's arrangement, each attitude sensing module is connected by soft arranging wire with the HUB host nodes for being arranged on glove bulk end.
HUB host nodes have been internally integrated calibration microprocessor and signal emission module, and calibration microprocessor receives each attitude sensing module
Each joint attitude quaternion of collection, and just described each joint attitude quaternion is transferred to accordingly by signal emission module
On display device, realize that gesture motion catches.
Hand-type, size yet with everyone will not be just the same, the position of attitude heading reference system after putting on one's gloves
Ideal position might not be in.This initial installation site deviation attitude data during hand exercise can be caused inaccurate and
Accurate hand gestures cannot be obtained.Because there is initial position error after putting on one's gloves, sensor can not be fixed to reason
Think position, as shown in figure 3, wearing dynamic hunter be difficult to ensure that when covering the installation site of attitude sensing module completely with finger-joint
Coordinate system is completely superposed, and the initial installation deviation of attitude sensing module can cause hand gestures measurement error, it is therefore necessary to pass through
The compensation of the initial installation deviation of attitude sensing module is realized in certain calibration, reduces motion capture error during finger motion.
Therefore the utility model further provides the site error calibration method based on the conversion of quaternary number cross product, by this
The pose calibrating calibration method of utility model can eliminate inclined between attitude sensing module installation site attitude and ideal position
Difference, enables the attitude of attitude sensing module to reflect the motion of human finger motion, and then realize accurate gesture-capture.
To achieve these goals, the calibration microprocessor is additionally operable to carry out position to each joint attitude quaternion
Deviation calibration.Specifically, each joint attitude quaternary that can be gathered to each attitude sensing module according to initial deviation quaternary number
Number carries out position deviation calibration.
The attitude sensing module calibration method that the utility model is used for：
Assuming that the initial quaternary number of theory that five fingers close up when keeping flat under each local joint coordinate system naturally isThe output quaternary number of attitude sensing module isInitial deviation quaternary number isTheoretical initial quaternary number, attitude sensing module output quaternary number and initial deviation quaternary number meet pass
System：
WhereinRepresent that the multiplication of quaternary number is calculated, i.e.,:
Initial deviation quaternary number can further be obtained
During hand finger motion, the quaternary number measured by inertial attitude sensor-based systemCan obtain
To real joint motions quaternary number
Dynamic hunter covers the calculating of the calibration process and initial deviation quaternary number of integrated whole attitude sensing systems above
Completed by the microprocessor that can be integrated in HUB, and virtual reality of rear end etc. is further transferred to by HUB needs hand
In gesture action message application scenarios.
As it will be easily appreciated by one skilled in the art that preferred embodiment of the present utility model is the foregoing is only, not
It is used to limit the utility model, all any modifications made within spirit of the present utility model and principle, equivalent and changes
Enter, should be included within protection domain of the present utility model.
Claims (8)
1. a kind of motion capture gloves for gesture identification, it is characterised in that including attitude sensing module, glove bulk and
The hub of glove bulk end is arranged on, wherein：
Finger position at each joint two ends of the glove bulk is respectively mounted an attitude sensing module；
The attitude sensing module is at least integrated with a three axis MEMS gyro, 3 axis MEMS accelerometer and three axle magnetic sensing
Device and sensing microprocessor；The three-axis gyroscope is used to measure the angular speed of hand exercise, and three axis accelerometer is used to measure
The acceleration of hand exercise, earth's magnetic field size when magnetic sensor is used to measure hand exercise under different azimuth is sensed micro-
Processor is used to merge the data of multisensor measurement, obtains the attitude of each joint motions of hand and exports attitude quaternion；
Described each attitude sensing module is connected by socket with the glove bulk, and the socket is mounted on the glove bulk
On the soft arranging wire of inside arrangement, each attitude sensing module is connected by soft arranging wire with the hub.
2. the motion capture gloves of gesture identification are used for as claimed in claim 1, it is characterised in that the hub internal collection
Microprocessor and signal emission module are calibrated into having, wherein：
The calibration microprocessor is used to receive each joint attitude quaternion of each attitude sensing module collection；
The signal emission module is used to for each joint attitude quaternion to be transferred to corresponding display device, realizes gesture
Motion capture.
3. the motion capture gloves of gesture identification are used for as claimed in claim 2, it is characterised in that the calibration microprocessor
It is additionally operable to carry out position deviation calibration to each joint attitude quaternion.
4. the motion capture gloves of gesture identification are used for as claimed in claim 3, it is characterised in that the calibration microprocessor
Position deviation calibration is carried out to each joint attitude quaternion that each attitude sensing module is gathered according to initial deviation quaternary number.
5. the motion capture gloves of gesture identification are used for as claimed in claim 4, it is characterised in that the calibration microprocessor
Close up the initial quaternary number of theory and each attitude sensing under each local joint coordinate system when keeping flat naturally according to five fingers
The output quaternary number of module calculates the initial deviation quaternary number.
6. motion capture gloves for gesture identification as described in claim 4 or 5, it is characterised in that the initial deviation
Quaternary numberForWherein i=1,2...16, describedIt is the output quaternary of attitude sensing module
Number, it is describedIt is the initial quaternary number of theory under each local joint coordinate system when five fingers close up naturally to be kept flat.
7. the motion capture gloves of gesture identification are used for as claimed in claim 1 or 2, it is characterised in that the attitude sensing
Module has 16.
8. the motion capture gloves of gesture identification are used for as claimed in claim 1 or 2, it is characterised in that 15 attitudes sensings
Module is placed between every finger-joint, and the 16th attitude sensing module is arranged at the back of the hand or palm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201621064325.7U CN206270980U (en) | 2016-09-19 | 2016-09-19 | A kind of motion capture gloves for gesture identification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201621064325.7U CN206270980U (en) | 2016-09-19 | 2016-09-19 | A kind of motion capture gloves for gesture identification |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN206270980U true CN206270980U (en) | 2017-06-20 |
Family
ID=59037188
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201621064325.7U Active CN206270980U (en) | 2016-09-19 | 2016-09-19 | A kind of motion capture gloves for gesture identification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN206270980U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107752174A (en) * | 2017-12-04 | 2018-03-06 | 成都思悟革科技有限公司 | A kind of gloves based on electromagnetic field motion capture technology |
| CN113920809A (en) * | 2021-10-29 | 2022-01-11 | 航天科工武汉磁电有限责任公司 | Mixed reality teaching system for ship fire-fighting training |
-
2016
- 2016-09-19 CN CN201621064325.7U patent/CN206270980U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107752174A (en) * | 2017-12-04 | 2018-03-06 | 成都思悟革科技有限公司 | A kind of gloves based on electromagnetic field motion capture technology |
| CN107752174B (en) * | 2017-12-04 | 2024-03-19 | 成都思悟革科技有限公司 | Glove based on electromagnetic field motion capture technology |
| CN113920809A (en) * | 2021-10-29 | 2022-01-11 | 航天科工武汉磁电有限责任公司 | Mixed reality teaching system for ship fire-fighting training |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106445130B (en) | A kind of motion capture gloves and its calibration method for gesture identification | |
| CN103226398B (en) | Based on the data glove of micro-inertia sensor network technology | |
| CN108268129B (en) | Method and apparatus for calibrating a plurality of sensors on a motion capture glove and motion capture glove | |
| TWI474265B (en) | Moving trajectory calibration method and moving trajectory generation method | |
| CN104223613B (en) | Intelligent bracelet display control program and Intelligent bracelet | |
| CN108279773B (en) | Data glove based on MARG sensor and magnetic field positioning technology | |
| CN203039726U (en) | Human body three-dimensional posture identifying system | |
| CN102426477A (en) | Gesture detecting method and detecting device | |
| CN104778746A (en) | Method for performing accurate three-dimensional modeling based on data glove by using natural gestures | |
| Choi et al. | Development of a low-cost wearable sensing glove with multiple inertial sensors and a light and fast orientation estimation algorithm | |
| CN105068657B (en) | The recognition methods of gesture and device | |
| CN109737941A (en) | A kind of human action method for catching | |
| CN106970705A (en) | Motion capture method, device and electronic equipment | |
| CN206270980U (en) | A kind of motion capture gloves for gesture identification | |
| Sama et al. | 3dID: a low-power, low-cost hand motion capture device | |
| CN109343713B (en) | Human body action mapping method based on inertial measurement unit | |
| CN102306054A (en) | Attitude sensing equipment and positioning method and device thereof and method and device for controlling mouse pointer | |
| CN212341836U (en) | Data glove and virtual reality system | |
| CN106843481A (en) | A kind of three dimensions Freehandhand-drawing device and method based on gesture control | |
| CN110236560A (en) | Six axis attitude detecting methods of intelligent wearable device, system | |
| CN111102973A (en) | Multi-sensor attitude detection system | |
| CN109032387A (en) | A method of pen body posture is detected with electromagnetic location dual sensor by ultrasonic wave | |
| CN207690015U (en) | A kind of gesture recognition system based on nine axle sensors | |
| CN211956499U (en) | Gesture capturing and positioning device | |
| CN110209270A (en) | A kind of data glove, data glove system, bearing calibration and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |