CN102426477A - Gesture detecting method and detecting device - Google Patents
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Abstract
The invention discloses a gesture detecting method and a detecting device. The detecting method comprises a data acquisition process, a data processing process and a data transmission process; in the data acquisition process, a digital type triaxial acceleration sensor which is mounted on the back of a hand is adopted to detect vector motion acceleration values of a hand motion in three axes, i.e. an X axis, a Y axis and a Z axis, and a plurality of bending sensors which are mounted at movable joints of each finger are adopted to detect the bending motions of each finger; and in the data processing process, included angle values of the hand between the X axis direction, the Y axis direction and the Z axis direction and the gravity direction are obtained according to the vector motion acceleration values of the digital type triaxial acceleration sensor, the bending angle value of each bending sensor is obtained through calculating according to signals of the bending sensors, and a characteristic data array which represents gestures is composed of the included angle values between the X axis direction, the Y axis direction and the Z axis direction and the gravity direction and the data of the bending angle values of the bending sensors at key frames. The detecting device has low cost, high sampling accuracy and high processing efficiency and can be widely applied to the field of sign language recognition.
Description
Technical field
The present invention relates to the Sign Language Recognition field, especially a kind of gesture method for detecting and arrangement for detecting.
Background technology
High speed development along with The present computer technology; Increasing man-machine interactive system requires hand motion is realized high-precision seizure and reduction; Under three-dimensional virtual environment like man-machine interactive systems such as virtual reality systems; Require auxiliary hand motion detection equipment can catch in real time, accurately and restoring operation personnel's hand motion change procedure; A lot of high-risk environment are not suitable for personnel's site disposal, need remote control intelligent robot mechanical arm to carry out dangerous operation, and this situation needs accurately to control long-range intelligent robot manipulator behavior.Gesture identification method needs accurately to detect the movement locus of hand and finger, and each points posture change at the volley to calculate hand, and carries out digital quantification to this action variation, is convenient to the computer realization hand motion and reduces synchronously.Existing gesture detection equipment mainly contains following several kinds:
1, adopts the data glove of straight-line displacement formula sensor,, convert finger bend degree amount to through displacement through detecting the linear displacement transducer displacement that finger bend causes.This data glove generally is a machinery frame formula application structure, complicated in mechanical structure.
2, use the data glove of optical fibre bending sensor, the laser signal that causes when utilizing fibre-optical bending decay and interference detect the finger bend state, convert finger bend degree amount to according to the laser signal damping capacity.
3, use the data glove technology of acceleration transducer, there is a kind of data glove of using one group of acceleration transducer to measure each finger movement in the U.S., converts the motion state of finger to through the accekeration of the detection of the acceleration transducer on the finger.This method is very high to the dithering process requirement of finger, and shake is disturbed big.
4, utilize the data glove of visual analysis, identification point is installed on gloves, utilize camera to catch the motion of identification point, go out the motion state of gloves through the video analysis processing and identification.Peripherals is complicated, system expensive.
Summary of the invention
The technical matters that the present invention will solve is: a kind of hardware device is succinct, with low cost, treatment effeciency is high gesture method for detecting and arrangement for detecting are provided.
In order to solve the problems of the technologies described above, the technical scheme that the present invention adopted is:
A kind of gesture method for detecting may further comprise the steps:
Adopt the data acquisition flow of sensor detecting hand and finger motion;
The data-signal of sensor acquisition is converted to the flow chart of data processing of the characteristic data array of representing gesture;
The characteristic data array of representing gesture is transferred to the data transmission flow process on the backstage that gesture is discerned;
Said data acquisition flow adopts a digital 3-axis acceleration sensor that is installed on the back of the hand to detect the vector motion accekeration of hand exercise on three of X, Y, Z, adopts a plurality of bend sensors of respectively pointing the turning joint position that are installed in to detect bending motions that each is pointed; Said flow chart of data processing obtains the angle value of hand at X, Y, Z three direction of principal axis and gravity direction according to the vector motion accekeration of digital 3-axis acceleration sensor; Obtain the angle of bend value of each bend sensor according to the calculated signals of bend sensor, the angle value of said X, Y, Z three direction of principal axis and gravity direction and the angle of bend value of each bend sensor constitute the characteristic data array of representing gesture in the data of key frame.
Further, the number of said bend sensor is 5,9,14 or 17.
Further as preferred embodiment, said data acquisition flow, flow chart of data processing, data transmission flow process adopt the mode of operation of multi-threaded parallel through state machine.
A kind of gesture arrangement for detecting; Comprise that a pair of image data carries out the central processor unit of calculation process; Said central processor unit is connected with the memory module that sensor unit, power supply unit, data communication units and a storage need the systematic parameter of power down protection respectively through port; Sensor unit comprises a digital 3-axis acceleration sensor and a plurality of bend sensor; Said each bend sensor is connected to data sampling circuit through a signal conditioning circuit successively, and said digital 3-axis acceleration sensor is connected with the port of central processor unit with data acquisition circuit.
Further, the number of said bend sensor is 5,9,14 or 17.
Further, said data communication units is UART module, USB port module or bluetooth port module.
Further, said power supply unit is lithium battery and/or USB supply module.
The invention has the beneficial effects as follows: gesture method for detecting of the present invention is through combining the real-time detection to the motion change of hand and finger of bend sensor and digital 3-axis acceleration sensor; Obtain on X, Y, Z axle, constituting the characteristic data array of representing gesture in the data of key frame through data processing with the angle of bend value of gravity direction angle value and each bend sensor by acceleration transducer; Said gesture method for detecting can be to hand exercise posture and finger operation carrying out detecting real-time, and precision is high; Further, the pattern of said gesture method for detecting through adopting multi-threaded parallel to handle improved the work in series pattern of traditional data collection, data processing, data transmission, improved the efficient of data sampling, data processing and data transmission; Said gesture arrangement for detecting has combined acceleration transducer and bend sensor, and simple in structure, cost is low, and sampling precision is high, and treatment effeciency is high.
Description of drawings
Be described further below in conjunction with the accompanying drawing specific embodiments of the invention:
Fig. 1 is the basic flow sheet of gesture method for detecting;
Fig. 2 is that acceleration transducer of the present invention is at X, Y, Z three axial vector distribution plans;
Fig. 3 is that acceleration transducer of the present invention is at X, Y, Z three axial vectors and gravity angle distribution plan;
Fig. 4 is the bend sensor synoptic diagram;
Fig. 5 is the correspondence table of bend sensor and acceleration transducer and joint position, bending range.
Fig. 6 is the sensor distribution schematic diagram that adopts 6 sensor embodiment;
Fig. 7 is the sensor distribution schematic diagram that adopts 10 sensor embodiment;
Fig. 8 is the sensor distribution schematic diagram that adopts 15 sensor embodiment;
Fig. 9 is the sensor distribution schematic diagram that adopts 18 sensor embodiment;
Figure 10 is the process flow diagram of the preferred gesture method for detecting of the present invention;
Figure 11 is the theory diagram of gesture arrangement for detecting of the present invention;
Figure 12 is the hardware structure diagram of gesture arrangement for detecting of the present invention;
Figure 13 is bend sensor signal processing circuit circuit theory diagrams;
Figure 14 is bend sensor signal conditioning circuit circuit theory diagrams.
Embodiment
The gesture detecting mainly solves following two technical matterss:
1, the detecting of hand exercise posture: the detecting of hand exercise posture is meant the posture change in the hand exercise process; Comprise actions such as rotation, translation, inclination, upset; Mainly be meant the mass motion detecting of hand, adopt digital 3-axis acceleration sensor to confirm the space posture of hand among the present invention;
2, point the detecting of operation: the detecting of finger operation is meant the bending of each finger, stretching, extension, detects around operations such as moving (thumbs).
The present invention has developed a kind of gesture method for detecting and arrangement for detecting on the basis that combines digital 3-axis acceleration sensor and bend sensor.
With reference to Fig. 1, a kind of gesture method for detecting may further comprise the steps:
Adopt the data acquisition flow of sensor detecting hand and finger motion;
The data-signal of sensor acquisition is converted to the flow chart of data processing of the characteristic data array of representing gesture;
The characteristic data array of representing gesture is transferred to the data transmission flow process on the backstage that gesture is discerned.
Said data acquisition flow adopts a digital 3-axis acceleration sensor that is installed on the back of the hand to detect the vector motion accekeration of hand exercise on three of X, Y, Z, adopts a plurality of bend sensors of respectively pointing the turning joint position that are installed in to detect bending motions that each is pointed; Said flow chart of data processing obtains the angle value of hand at X, Y, Z three direction of principal axis and gravity direction according to the vector motion accekeration of digital 3-axis acceleration sensor; Obtain the angle of bend value of each bend sensor according to the calculated signals of bend sensor, the angle value of said X, Y, Z three direction of principal axis and gravity direction and the angle of bend value of each bend sensor constitute the characteristic data array of representing gesture in the data of key frame.
Said acceleration transducer can detect the vector motion accekeration of any moment hand on three of X, Y, Z simultaneously; With reference to Fig. 2; X, Y, three of Z form orthogonal 3 d space coordinate and are; The vector acceleration value that detects on three of X when static, Y, Z is the component accekeration of gravity on three; The vector acceleration value that detects on three of X during motion, Y, Z is the resultant acceleration value of acceleration of gravity and the component accekeration of acceleration of motion on three; The component accekeration of any time gravity on three of X, Y, Z do not influenced by acceleration of motion; Therefore any time in conjunction with the three-dimensional space motion algorithm, can calculate the resultant vector acceleration avg of acceleration of motion and acceleration of gravity according to X, Y, three vector acceleration value aX, aY, aZ that go up detecting of Z; Can calculate the size of the vector space angle of three of acceleration avg and X, Y, Z through trigonometric function relation; Position when setting the Z axle and overlapping with gravity is an initial reference position, and then the size according to the vector space angle of three of acceleration avg and X, Y, Z combines three-dimensional eight to limit mutually, can confirm the space posture of 3-axis acceleration sensor in real time.With reference to Fig. 3; Said acceleration transducer is respectively θ xg, θ yg, θ zg at X, Y, three angles with gravity direction of Z; Accekeration in X, Y, Z direction is respectively DataX, DataY, DataZ; Said DataX, DataY, DataZ are respectively the resultant acceleration values of gravity and motion component on three, and there are following specific trigonometric function relation in angle and acceleration:
F(θxg)?=atan?(?sqrt?(DataY?*?DataY?+?DataZ?*?DataZ)?/?DataX)）*?180?/?PI (1)
F(θyg?)=atan?(?sqrt?(DataX?*?DataX?+?DataZ?*?DataZ)?/?DataY)?)?*?180?/?PI (2)
F(θzg)?=atan?(?sqrt?(DataX?*?DataX?+?DataY?*?DataY)?/?DataZ)?)?*?180?/?PI (3)
Can calculate the angle of three of any time acceleration transducer X, Y, Z and gravity direction through above-mentioned formula (1) ~ (3); Because the accekeration on the detected X of acceleration transducer, Y, Z three direction of principal axis is a vector value; So the angle value of calculating is-90 ° ~+90 °; In conjunction with the direction vector of acceleration transducer acceleration on X, Y, Z three direction of principal axis, can confirm acceleration transducer motion posture at any time.In data handling procedure; Earlier acceleration transducer is carried out initialization action during use; With initialized state is RP; In motion process, the value of sense acceleration sensor vector acceleration on X, Y, Z three direction of principal axis is also done quadratic integral to the vector acceleration value in time, can calculate displacement and moving direction in X, Y, three directions of Z axle respectively.
With reference to Fig. 4; Said bend sensor adopt force-sensitive material detect the bending of finger, stretching, extension, around moving actions such as (thumbs); Through being installed in different bend sensors the key position of each finger motion degree of freedom; Realization is to the motion detecting on each finger degree of freedom direction, and the effect of said bend sensor is bending, the stretching, extension of finger, converts scalable electric signal to around moving actions such as (thumbs), and flow chart of data processing is through data analysis and algorithm process; Become band to represent the crooked angle value of bend sensor electrical signal conversion, the flexural property of bend sensor is seen following expression formula:
θbend?=μf(Ri)?+?H ……… (4)
Said θ bend is crooked angle value, and f (Ri) is a repeatedly function, and Ri is the increased resistance value of bend sensor, and μ is a flexural property curve system correction coefficient, and H is a flexural property migration coefficient.
The funtcional relationship of said f (Ri) is following:
f(Ri)?=?A*exp(Ri,5)?+?B*exp(Ri,4)?+?C*exp(Ri,3)?+?D*exp(Ri,2)?+?E*exp(Ri,1)…（5）
The data array of gesture identification is calculated by following formula:
And the process of a gesture identification on microcosmic, has comprised the data array of a continually varying gesture identification:
ψdhand=[φDhand1,φDhand2,φDhand3...φDhandN] (7)
According to expression formula (6) and (7), formed the two-dimentional dynamic gesture identification critical data array of (N+2) * M, N is a number of sensors, and M is the identification quantity of key frames, and the numerical value of M is difference with the complexity of gesture action.
Two dimension gesture identification characteristic data array is following:
Further, the number of said bend sensor is 5,9,14 or 17.
The corresponding relation of the initial value of the bend sensor of turning joint position distribution, numbering, bending range, angle of bend is with reference to Fig. 5 on each finger.
Introduce the distribution situation on finger and the back of the hand of sensor below in conjunction with Fig. 6 ~ Fig. 9, the phalanges structure is pointed in solid line representative among the figure, and circle is represented joint position, and crooked dotted line is represented bend sensor, and frame of broken lines is represented 3-axis acceleration sensor.
With reference to Fig. 6, adopt 5 bend sensors and 1 acceleration transducer to detect the motion of hand and finger in the present embodiment, comprise bend sensor 0,2,4,6,8 and acceleration transducer 17; Said bend sensor 0,2,4,6,8 is distributed in 5 finger-joint positions, is used to measure the bending of each finger, and acceleration transducer 17 is distributed in the actions such as upset, inclination and translation that the back of the hand position is used to measure hand.
With reference to Fig. 7, adopt 9 bend sensors and 1 acceleration transducer to detect the motion of hand and finger in the present embodiment, comprise bend sensor 0,2,4,6,8,10,11,12,13 and acceleration transducer 17; Said bend sensor 0,2,4,6,8 is distributed in 5 finger-joint positions; Be used to measure the bending of each finger; The position was used to measure the arms sideward lift of finger between said bend sensor 10,11,12,13 was distributed in and respectively points, and acceleration transducer 17 is distributed in the actions such as upset, inclination and translation that the back of the hand position is used to measure hand.
With reference to Fig. 8, adopt 14 bend sensors and 1 acceleration transducer to detect the motion of hand and finger in the present embodiment, comprise bend sensor 0,1,2,3,4,5,6,7,8,9,10,11,12,13, reach acceleration transducer 17; Said bend sensor 0,1,2,3,4,5,6,7,8,9 is distributed in 5 finger-joint positions; Be used to measure the bending of each finger; The position was used to measure the arms sideward lift of finger between said bend sensor 10,11,12,13 was distributed in and respectively points, and acceleration transducer 17 is distributed in the actions such as upset, inclination and translation that the back of the hand position is used to measure hand.
With reference to Fig. 9; Adopt 17 bend sensors and 1 acceleration transducer to detect the motion of hand and finger in the present embodiment; Comprise bend sensor 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16 and acceleration transducer 17; Said bend sensor 0,1,2,3,4,5,6,7,8,9 is distributed in 5 finger-joint positions; Be used to measure the bending of each finger; The position was used to measure the arms sideward lift of finger between said bend sensor 10,11,12,13 was distributed in and respectively points; Said bend sensor 14 is distributed in the bending that is used to measure the back of the hand between thumb and the back of the hand, and said bend sensor 15,16 is distributed in bending and the arms sideward lift that the wrist position is used to measure wrist, and acceleration transducer 17 is distributed in the actions such as upset, inclination and translation that the back of the hand position is used to measure hand.
Further as improving, said data acquisition flow, flow chart of data processing, data transmission flow process are passed through the mode of operation that state machine adopts multi-threaded parallel, and concrete workflow is with reference to Figure 10.
Under the mode of operation of multi-threaded parallel:
Three threads are separate, and are that concurrent working is that three threads are the work that moves simultaneously, adopt state machine to link up between the thread, and the course of work is following:
Thread 1: beginning data acquisition; Data acquisition finishes the back and finishes through 2 data acquisitions of state machine 1 notice thread, can begin data processing, and thread 1 continues beginning data acquisition for the second time then; This process repeats, and need not to wait for thread 2 completion data processing.The storage organization pattern of the The data chained list formation that thread 1 is gathered need not to worry that the data of gathering for the second time can override the data of gathering for the first time.When thread 2 beginning data processing, thread 1 beginning data acquisition for the second time.
Thread 2: owing to also there are not data to need to handle, always be in the state of the state machine 1 of waiting for thread 1, when receiving the state machine 1 of thread 1 when at first system begins; Begin to carry out the data processing first time; When data processing finishes for the first time, fall the current state machine 1 of handling data clearly, the data that notice thread 1 this group is gathered have been accomplished algorithm process; Finish through state machine 2 notice threads 3 data processing then; Can begin data transmission, so far thread 2 is accomplished data handling procedure for the first time, can begin data processing for the second time.The storage organization pattern of the The data chained list formation that thread 2 is finished dealing with need not to worry that the data of finishing dealing with for the second time can override the data of handling for the first time.When the thread 3 beginning data transmission first time, thread 2 beginnings are data handling procedures for the second time.
Thread 3: owing to also there are not data to need transmission, always be in the state of the state machine 2 of waiting for thread 2, when receiving the state machine 2 of thread 2 when at first system begins; Begin to carry out the data transmission first time; For the first time during DTD, fall the current state machine 2 that transmits data clearly, the data of notifying thread 2 these groups to handle well have been accomplished transmission; So far thread 3 is accomplished data transmission procedure for the first time, can begin data transmission for the second time.When the thread 3 beginning data transmission first time, thread 2 beginnings are data handling procedures for the second time, and thread 1 then begins to carry out data acquisition for the third time.
In this multi-threaded parallel mode of operation; Each thread is responsible for the single course of work; First data acquisition, data processing, data transmission procedure are close with conventional serial mode of operation efficient accomplishing; Begin from data acquisition for the third time, accomplish a data collection, data processing, data transmission procedure and compare with the conventional serial mode of operation, efficient will be enhanced about more than once.
With reference to Figure 11 and Figure 12; A kind of gesture arrangement for detecting; Comprise that a pair of image data carries out the central processor unit of calculation process; Said central processor unit is connected with the memory module that sensor unit, power supply unit, data communication units and a storage need the systematic parameter of power down protection respectively through port; Sensor unit comprises a digital 3-axis acceleration sensor and a plurality of bend sensor, and said each bend sensor is connected to data sampling circuit through a signal conditioning circuit successively, and said digital 3-axis acceleration sensor is connected with the port of central processor unit with data acquisition circuit.
Further, the number of said bend sensor is 5,9,14 or 17, the bend in one direction sensor that said bend sensor adopts the FLX-03 pressure sensitive material to make, and the crooked resistance of forward increases, and back-flexing resistance reduces.In equivalent electrical circuit design, bend sensor be simplified to a variohm model, like the R2 among Figure 13, Figure 14; The last output signal of R2 changes with the bend sensor angle of bend, and bend sensor output signal Y and angle of bend X are specific curved line relation:
Y?=?μ*(A0?+?B1*X?+?B2?*?exp(X,2)+?B3?*?exp(X,3)+?B4?*?exp(X,4)+?B5?*?exp(X,5)?)
In the following formula, Y is the bend sensor angle of bend, and μ is the correction coefficient of bend sensor, and by A0, B1 ~ B5 is the flexural property coefficient.
Figure 13, Figure 14 are respectively the sensor output signal treatment circuits of two kinds of different accuracy demands: low precision signal is handled and high-precision signal is handled,
Low precision signal is handled as Figure 13: bend sensor R2 is through carrying out dividing potential drop with precision resistance R1, exports signal directly as the input signal of data acquisition module.
High-precision signal treatment circuit such as Figure 14: bend sensor R2 output signal amplifies through amplifier A; But make the signal of the subtle change on the sensor be amplified to sensing range; Improve the input precision, can effectively remove the coupled interference of external electromagnetic behind the filtering circuit of amplifier output signal through resistance R 4, capacitor C composition.To adopting the high precision gesture arrangement for detecting of this gesture method for detecting, each bend sensor output signal all comprises the signal conditioning circuit like Figure 14.
Further, said data acquisition circuit adopts the multi-channel high-speed data acquisition chip TLV2553 of TI company, has 11 passage synchronous acquisition functions; The data of gathering are transferred to central processor unit through SPI and carry out data processing; Said acceleration transducer adopts the digital 3-axis acceleration sensor ADXL345 chip of ADI company, can measure the accekeration on three of the mutually orthogonal X, Y, Z simultaneously, the maximum detection amount+/-acceleration of 16g; Measurement data is transferred to central processor unit through the IIC interface and carries out data processing; Said central processor unit adopts the high-speed processor chip of NXP semiconductor ARM9 kernel, has good floating-point operation ability and DSP data-handling capacity, and said memory module adopts the eeprom chip of ATMEL; Have power down protection capability, be used to store key system perameter.
Further, said data communication units is UART module, USB port module or bluetooth port module.
Further, said power supply unit is lithium battery and/or USB supply module.
More than be that preferable enforcement of the present invention is specified; But the invention is not limited to said embodiment; Those of ordinary skill in the art make all equivalent variations or replacement under the prerequisite of spirit of the present invention, also can doing, and distortion that these are equal to or replacement all are included in the application's claim institute restricted portion.
Claims (7)
1. gesture method for detecting may further comprise the steps:
Adopt the data acquisition flow of sensor detecting hand and finger motion;
The data-signal of sensor acquisition is converted to the flow chart of data processing of the characteristic data array of representing gesture;
The characteristic data array of representing gesture is transferred to the data transmission flow process on the backstage that gesture is discerned;
It is characterized in that: said data acquisition flow adopts a digital 3-axis acceleration sensor that is installed on the back of the hand to detect the vector motion accekeration of hand exercise on three of X, Y, Z, adopts a plurality of bend sensors of respectively pointing the turning joint position that are installed in to detect bending motions that each is pointed; Said flow chart of data processing obtains the angle value of hand at X, Y, Z three direction of principal axis and gravity direction according to the vector motion accekeration of digital 3-axis acceleration sensor; Obtain the angle of bend value of each bend sensor according to the calculated signals of bend sensor, the angle value of said X, Y, Z three direction of principal axis and gravity direction and the angle of bend value of each bend sensor constitute the characteristic data array of representing gesture in the data of key frame.
2. a kind of gesture method for detecting according to claim 1 is characterized in that: the number of bend sensor is 5,9,14 or 17.
3. a kind of gesture method for detecting according to claim 1 is characterized in that: said data acquisition flow, flow chart of data processing, data transmission flow process adopt the mode of operation of multi-threaded parallel through state machine.
4. gesture arrangement for detecting; Comprise that a pair of image data carries out the central processor unit of calculation process; Said central processor unit is connected with the memory module that sensor unit, power supply unit, data communication units and a storage need the systematic parameter of power down protection respectively through port; It is characterized in that: sensor unit comprises a digital 3-axis acceleration sensor and a plurality of bend sensor; Said each bend sensor is connected to data sampling circuit through a signal conditioning circuit successively, and said digital 3-axis acceleration sensor is connected with the port of central processor unit with data acquisition circuit.
5. a kind of gesture arrangement for detecting according to claim 4 is characterized in that: the number of said bend sensor is 5,9,14 or 17.
6. a kind of gesture arrangement for detecting according to claim 4 is characterized in that: said data communication units is UART module, USB port module or bluetooth port module.
7. a kind of gesture arrangement for detecting according to claim 4 is characterized in that: said power supply unit is lithium battery and/or USB supply module.
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