CN102243687A - Physical education teaching auxiliary system based on motion identification technology and implementation method of physical education teaching auxiliary system - Google Patents
Physical education teaching auxiliary system based on motion identification technology and implementation method of physical education teaching auxiliary system Download PDFInfo
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Abstract
The invention provides a physical education teaching auxiliary system based on a motion identification technology and an implementation method of the physical education teaching auxiliary system. The system is applicable to a personal computer (PC) or an embedded host. The system comprises a movement data collection module, a movement data acquisition module, an identification and training module and a virtual teaching environment module. The device is characterized in that: a micro-inertia measurement unit and an inertia parameter extraction unit are arranged in the movement data collection module; and a movement information resolving unit transmits data which is output by the inertia parameter extraction unit to a multi-sensor data fusion unit for resolving. The movement situation of a target is reflected comprehensively in an inertia tracking mode and an optical tracking mode, so a tracking range is effectively expanded, measurement accuracy is improved, and the problems that the integral information of the target cannot be acquired in the inertia tracking mode, complicated movement identification cannot be performed and sensitivity is poor are solved. A brand new teaching mode is provided for physical education teaching, and a physical education teaching method is digitalized, multi-media and scientifically standardized.
Description
Technical field
The present invention relates to man-machine interaction, action recognition and computer-aided instruction field, relate in particular to a kind of construction method of physical education backup system.
Background technology
At present, the method for motion tracking is divided into according to the difference of sensing element: inertia tracking, optical tracking, power and mechanical type are followed the trail of, electromagnetic type is followed the trail of, acoustics is followed the trail of or the like.At present, be inertia tracer technique and optical tracking technology in field of human-computer interaction motion tracking technology relatively more commonly used.The inertia tracer technique by Inertial Measurement Unit is set, measures data such as acceleration, angular velocity on target, use mathematical tool to resolve based on this, obtains the motion conditions of target.The characteristics that inertia is followed the trail of are to realize simply strong interference immunity; Shortcoming is to obtain the motion feature of tracked target all sidedly, can only finite sum reflects the movement characteristic of tracked target partly.The optical tracking technology is by the task that motion tracking is finished in the supervision and the tracking of specific luminous point on the target.In theory, for any one point in space, as long as it can then according to the same image and the camera parameters of two shot by camera in a flash, promptly can determine this locus of this point constantly simultaneously by two video camera findings.When video camera is taken continuously with sufficiently high speed, from image sequence, just can obtain the movement locus of this point.What wherein treatment of picture adopted is the three-dimensional image reconstruction technique, promptly by the camera record image, forms dummy object by digitized processing, demarcates by three dimensions then, determines the locus of object.The characteristics of optical tracking technology are the motion conditions that can reflect object all sidedly, the precision height; Shortcoming is to realize comparatively difficulty, and the scope of following the trail of is less.
CN10115888 discloses a kind of virtual sports system and its implementation based on computer vision, be used for multi-purpose computer, utilize computer vision to discern the motion state and the pattern of human body and sports apparatus, and pattern fed back to computing machine, by the processing of computing machine, the role who controls in the virtual sports makes corresponding action.This invention can improve the popularity of nationwide fitness programs better, but shortcoming is less for the identification range of actual act.
Summary of the invention
The purpose of this invention is to provide a kind of physical education backup system and its implementation based on the action recognition technology, utilize human-computer interaction technology and optical tracking to follow the trail of the method that combines with inertia, can effectively enlarge the motion tracking scope and in time feed back movable information, realize the collection and the processing of interior special exercise information in a big way, and it is applied to the auxiliary physical education of computer virtual.
The technical solution adopted for the present invention to solve the technical problems is: a kind of physical education backup system based on the action recognition technology, be used for PC or embedded host, it comprises exercise data acquisition module, exercise data acquisition module, identification and training module, virtual instruction environment module composition
Described exercise data acquisition module further comprises: the specific wavelength pointolite, be no less than two cameras;
Described exercise data acquisition module further comprises: image characteristics extraction unit, three-dimensional fix unit, movable information resolve unit, multi-sensor data integrated unit;
Described identification and training module further comprise: pattern data acquisition module, training module, identification unit;
Described virtual instruction environment module comprises a pattern java standard library, an action resolution unit, a virtual instruction environment, a display device;
It is characterized in that: in described exercise data acquisition module, still be provided with a micro inertial measurement unit and an inertial parameter extraction unit, micro inertial measurement unit and measured target binding, be used to measure the inertial parameter of measured target, handle for the exercise data acquisition module, described micro inertial measurement unit is connected with described inertial parameter extraction unit signal input part by wireless signal; Described movable information resolves the unit data transmission of inertial parameter extraction unit output is resolved processing to the multi-sensor data integrated unit.
Described exercise data acquisition module, the position of wherein said three-dimensional fix unit by using gauge point imaging in two cameras, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, described multi-sensor data integrated unit adopts based on the multi-sensor data blending algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to moving target and deals with, and obtains the pattern data of target.
Described virtual instruction environment module, wherein:
Described pattern java standard library is used for resolving for the action resolution unit model of pattern; Described pattern java standard library comprises particular athletic activity pattern java standard library, nonspecific pattern java standard library and continuous action model bank;
Described action resolution unit is used to resolve the identification result of pattern data;
Described virtual instruction environment is man-machine interaction platform, is used to provide the physical education scheme;
Described display device is used to feed back analysis result, the demonstration interactive action state of athletic performance pattern identification, and its input end is connected with computing machine;
Described particular athletic activity pattern java standard library, based on the elemental motion of sports item, the elemental motion, tennis elemental motion, golf swing, bowling that comprises table tennis deliver action, run lift leg action etc.;
Described nonspecific pattern java standard library is the action model storehouse according to physical education requirement customization special applications, comprises the action of pommel horse sportsman elemental motion, gymnastics, the application of physical education animation game class etc.;
Described continuous action model bank, the combination maneuver library of forming by action that designs for auxiliary physical education specific function, it comprises the complete action of a cover such as gymnastics, dancing, wushu, gymnastic qigong based on specific action model bank and nonspecific model bank.
A kind of construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology, it may further comprise the steps:
A, with the binding of gauge point and measured target, camera is installed in the dead ahead of appointed area, be used to catch the appointed area image, obtain the inertial parameter of gauge point motion;
B, capturing digital image are also imported multi-purpose computer, obtain the digital picture of target travel; Gather the inertial parameter of gauge point motion;
C, to the inertial parameter gathered with digital picture is resolved and Multi-sensor Fusion, obtain the gauge point mode of motion;
D, discern its motor pattern according to the gauge point mode of motion, send virtual teaching environment of physical education to, and the corresponding interactive action state of feedback output, interactive action state to output is added up, and compare with default physical education index and resolve, obtain moving aspects such as amendment scheme such as position, speed, angle, and with result's output on display device.
Described step C also comprises: in the image characteristics extraction unit, at first extract the characteristic composition of target travel by two value-based algorithms, characteristic composition is asked for its center of gravity, obtain the characteristic composition center; Then, set up the corresponding relation between the feature according to calculating to selected feature;
Described step C also comprises: to gauge point mode of motion and the inertial parameter that obtains among the described step B, by the multi-sensor data blending algorithm of D-S evidence theory, obtain reflecting the consistance data of target travel feature.
Described step D also comprises:
D1, the various sample pattern data of collection mark the sample pattern data that collect;
D2, go out the proper vector of its essential characteristic of reflection from described sample pattern extracting data one by one;
D3, divide according to described proper vector under category regions, make the proper vector that only comprises similar sample in each different classes of zone after dividing, set up sorter from proper vector to mapping relations the affiliated classification;
D4, pattern data to be detected are handled, extracted its proper vector;
D5, the proper vector of operation mode data to be detected is input to described sorter, sorter is differentiated according to its proper vector, obtains the identification result of these operation mode data to be detected.
The identification result of D6, pattern data is input in virtual instruction environment and the action resolution unit, by display device, and feedback output movement state.
Described step D2 also comprises:
D21, described sample pattern data are carried out pre-service, obtain training data;
D22, from training data, extract the characteristic component of reflection training data essential characteristic;
D23, described characteristic component is made up, obtain described proper vector.
Described step D4 also comprises:
D41, described pattern data to be detected are carried out pre-service, obtain Identification Data;
D42, from Identification Data, extract the characteristic component of reflection Identification Data essential characteristic;
D43, described characteristic component is made up, obtain described proper vector.
Described step D6 also comprises:
D61, self-defined different classes of standard operation pattern are set up the pattern java standard library;
D62, standard operation pattern and sports teaching procedure are customized for teaching plan, and import in the virtual teaching environment of physical education;
D63, identification result is input in the virtual teaching environment of physical education, realizes the man-machine interaction motion state; With the pattern java standard library is reference standard, and identification result is resolved, and obtains moving amendment scheme;
D64, will move amendment scheme and pattern data identification result and be input to display device.
Beneficial effect of the present invention: it makes reflection target travel situation after comprehensive having increased the inertia trace mode under the original optical tracking mode owing to adopt, effectively enlarged tracking range, improved the precision of measuring, solve inertia and followed the trail of the Motion Recognition that to obtain whole object information, can not do complexity, the problem of susceptibility difference, also solved the problem that poor, the effective tracking range of optical tracking technology reduction authenticity is little and stop influence simultaneously.The present invention also has very strong practicality, for physical education provides a kind of brand-new teaching pattern, allows the sports teaching method be tending towards digitizing, multimedization and scientific and standardization.
Below with reference to drawings and Examples, the present invention is carried out comparatively detailed explanation.
Description of drawings
Fig. 1 is the physical culture assisted teaching system schematic block diagram that the present invention is based on the action recognition technology.
Fig. 2 is an exercise data acquisition module schematic block diagram of the present invention.
Fig. 3 is an exercise data acquisition module schematic block diagram of the present invention.
Fig. 4 is identification of the present invention and training module schematic block diagram.
Fig. 5 is a virtual instruction environment module schematic block diagram of the present invention.
Fig. 6 is that schematic block diagram is amplified in the part of Fig. 5.
Fig. 7 is the schematic block diagram of general structure of the present invention.
Embodiment
As shown in Figure 2, described exercise data acquisition module 1 further comprises: specific wavelength pointolite 11, be no less than two cameras 12;
As shown in Figure 3, described exercise data acquisition module 2 further comprises: image characteristics extraction unit 21, three-dimensional fix unit 22, movable information resolve unit 23, multi-sensor data integrated unit 24;
Exercise data acquisition module 2, wherein said three-dimensional fix unit 22 utilizes the position of gauge point imaging in two cameras 12, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, described multi-sensor data integrated unit 24 adopts based on the multi-sensor data blending algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to moving target and deals with, and obtains the pattern data of target.
As shown in Figure 4, described identification and training module 3 further comprise: pattern data acquisition module 31, training module 32, identification unit 33;
As shown in Figure 5, described virtual instruction environment module 4 comprises a pattern java standard library 41, an action resolution unit 42, a virtual instruction environment 43, a display device 44;
Described virtual instruction environment module 4, wherein: described pattern java standard library 41 is used for resolving for the action resolution unit model of pattern; Described action resolution unit 42 is used to resolve the identification result of pattern data; Described virtual instruction environment 43 is man-machine interaction platform, is used to provide the physical education scheme; Described demonstration 44 equipment are used to feed back analysis result, the demonstration interactive action state of athletic performance pattern identification, and its input end is connected with computing machine;
As shown in Figure 2, in described exercise data acquisition module 1, still be provided with 13 yuan of micro-inertia measuring lists and an inertial parameter extraction unit 14, micro inertial measurement unit 13 and measured target binding, be used to measure the inertial parameter of measured target, handle for exercise data acquisition module 2, described micro inertial measurement unit 13 is connected with described inertial parameter extraction unit 14 signal input parts by wireless signal; Described movable information resolves the data transmission of the 23 pairs of inertial parameter extraction units in unit, 14 outputs and resolves processing to multi-sensor data integrated unit 24.
As shown in Figure 6, described pattern java standard library 41 comprises particular athletic activity pattern java standard library 45, nonspecific pattern java standard library 46 and continuous action model bank 47.
Described particular athletic activity pattern java standard library 45, based on the elemental motion of sports item, the elemental motion, tennis elemental motion, golf swing, bowling that comprises table tennis deliver action, run lift leg action etc.
Described nonspecific pattern java standard library 46 is the action model storehouses according to physical education requirement customization special applications, comprises the action of pommel horse sportsman elemental motion, gymnastics, the application of physical education animation game class etc.
Described continuous action model bank 47, the combination maneuver library of forming by action that designs for auxiliary physical education specific function, it comprises the complete action of a cover such as gymnastics, dancing, wushu, gymnastic qigong based on specific action model bank and nonspecific model bank.
Exercise data acquisition module 1 is mainly used in digital picture and the inertial parameter of gathering moving target, specific wavelength pointolite 11 is for sending monochromatic pointolite in this module, image capture device is the visible image capturing head, micro inertial measurement unit 13 is connected with inertial parameter extraction unit 14 signal input parts with the measured target binding and by wireless signal, the light signal of specific wavelength pointolite 11 is then by camera collection, camera 12 output terminals are connected with image characteristics extraction unit 21 input ends, movable information resolution unit 23 and image characteristics extraction unit 21 in the exercise data input motion data acquisition module 2 that exercise data acquisition module 1 is gathered are for exercise data acquisition module 2 analyzing and processing.
Target is in described display device 44 positive motions, to measure one group of exercise data with the described micro inertial measurement unit 13 of target bind, after inertial parameter extraction unit 14 is handled, obtain the motional inertia parameter, be sent to described movable information by wireless transport module and resolve unit 23; Specific wavelength pointolite 11 is for sending monochromatic pointolite in the exercise data acquisition module 1, image capture device is to be no less than two visible image capturing head, the light signal of specific wavelength pointolite is then by camera collection, and camera 12 output terminals are connected with image characteristics extraction unit 21 input ends.Movable information resolution unit 23 and image characteristics extraction unit 21 in the exercise data input motion data acquisition module 2 that exercise data acquisition module 1 is gathered are for exercise data acquisition module 2 analyzing and processing.
Movable information resolves the 23 pairs of data that obtain in unit and resolves and the result is sent to multi-sensor data integrated unit 24; The 21 pairs of video images that obtain in image characteristics extraction unit carry out the characteristic composition that two value-based algorithms obtain moving target, three-dimensional fix unit 22 passes through operation transform, obtain the three dimensional space coordinate of moving target, and be sent to multi-sensor data integrated unit 24; Multi-sensor data integrated unit 24 adopts the data message that obtains based on the multi-sensor data blending algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to moving target and deals with, and obtains the pattern data of target.
Identification and training module 3 are gathered exercises pattern sample data by pattern data acquisition module 31, carry out pre-service by 32 pairs of sample mode data of training module, obtain training data.Sorter among Fig. 4 extracts the proper vector of reflection data essential characteristic and according to proper vector it is classified from training data, set up the sorter from proper vector to mapping relations the affiliated classification; 33 pairs of identification units are analyzed the pattern data to be detected that obtain through exercise data acquisition module 2 and are carried out pre-service, obtain Identification Data, from Identification Data, extract proper vector and be input in the described sorter of Fig. 4, sorter is differentiated according to its proper vector, obtains the identification result to pattern data to be identified.
Self-defined different classes of standard operation pattern, set up pattern java standard library 41, have: as the elemental motion of table tennis, tennis elemental motion, golf swing, bowling is delivered and is moved, that runs lifts the particular athletic activity pattern java standard library 45 based on the elemental motion of sports item such as leg action, as pommel horse sportsman elemental motion, gymnastics, the actions that physical education animation game class is used etc. require the nonspecific pattern java standard library 46 of customization special applications according to physical education, and based on specific action model bank and nonspecific model bank for the continuous action model storehouse of forming by action 47 that auxiliary physical education specific function designs, comprise gymnastics, dancing, wushu, the complete action of one cover such as gymnastic qigong.
Standard operation pattern and sports teaching procedure are customized for teaching plan, and import in the virtual teaching environment of physical education; Identification result is input in the virtual instruction environment 43, realizes the man-machine interaction motion state; With the action criteria library is reference standard, is resolved by action resolution unit 42 pairs of identification results, obtains moving amendment scheme (as aspects such as position, speed, angles), and with result's output at display device 44.
It makes reflection target travel situation after comprehensive having increased the inertia trace mode under the original optical tracking mode owing to adopt, effectively enlarged tracking range, improved the precision of measuring, solve inertia and followed the trail of the Motion Recognition that to obtain whole object information, can not do complexity, the problem of susceptibility difference, also solved the problem that poor, the effective tracking range of optical tracking technology reduction authenticity is little and stop influence simultaneously.The present invention also has very strong practicality, for physical education provides a kind of brand-new teaching pattern, allows the sports teaching method be tending towards digitizing, multimedization and scientific and standardization.
Claims (10)
1. the physical education backup system based on the action recognition technology is used for PC or embedded host, and it comprises exercise data acquisition module, exercise data acquisition module, identification and training module, virtual instruction environment module composition,
Described exercise data acquisition module further comprises: the specific wavelength pointolite, be no less than two cameras;
Described exercise data acquisition module further comprises: image characteristics extraction unit, three-dimensional fix unit, movable information resolve unit, multi-sensor data integrated unit;
Described identification and training module further comprise: pattern data acquisition module, training module, identification unit;
Described virtual instruction environment module comprises a pattern java standard library, an action resolution unit, a virtual instruction environment, a display device;
It is characterized in that: in described exercise data acquisition module, still be provided with a micro inertial measurement unit and an inertial parameter extraction unit, micro inertial measurement unit and measured target binding, be used to measure the inertial parameter of measured target, handle for the exercise data acquisition module, described micro inertial measurement unit is connected with described inertial parameter extraction unit signal input part by wireless signal; Described movable information resolves the unit data transmission of inertial parameter extraction unit output is resolved processing to the multi-sensor data integrated unit.
2. a kind of physical education backup system as claimed in claim 1 based on the action recognition technology, it is characterized in that: described exercise data acquisition module, the position of wherein said three-dimensional fix unit by using gauge point imaging in two cameras, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, described multi-sensor data integrated unit adopts based on the multi-sensor data blending algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to moving target and deals with, and obtains the pattern data of target.
3. a kind of physical education backup system based on the action recognition technology as claimed in claim 1 is characterized in that: described virtual instruction environment module, wherein:
Described pattern java standard library is used for resolving for the action resolution unit model of pattern; Described pattern java standard library comprises particular athletic activity pattern java standard library, nonspecific pattern java standard library and continuous action model bank;
Described action resolution unit is used to resolve the identification result of pattern data;
Described virtual instruction environment is man-machine interaction platform, is used to provide the physical education scheme;
Described display device is used to feed back analysis result, the demonstration interactive action state of athletic performance pattern identification, and its input end is connected with computing machine;
Described particular athletic activity pattern java standard library, based on the elemental motion of sports item, the elemental motion, tennis elemental motion, golf swing, bowling that comprises table tennis deliver action, run lift leg action etc.;
Described nonspecific pattern java standard library is the action model storehouse according to physical education requirement customization special applications, comprises the action of pommel horse sportsman elemental motion, gymnastics, the application of physical education animation game class etc.;
Described continuous action model bank, the combination maneuver library of forming by action that designs for auxiliary physical education specific function, it comprises the complete action of a cover such as gymnastics, dancing, wushu, gymnastic qigong based on specific action model bank and nonspecific model bank.
4. construction method based on the virtual physical culture teaching auxiliary system of action recognition technology, it may further comprise the steps:
A, with the binding of gauge point and measured target, camera is installed in the dead ahead of appointed area, be used to catch the appointed area image, obtain the inertial parameter of gauge point motion;
B, capturing digital image are also imported multi-purpose computer, obtain the digital picture of target travel; Gather the inertial parameter of gauge point motion;
C, to the inertial parameter gathered with digital picture is resolved and Multi-sensor Fusion, obtain the gauge point mode of motion;
D, discern its motor pattern according to the gauge point mode of motion, send virtual teaching environment of physical education to, and the corresponding interactive action state of feedback output, interactive action state to output is added up, and compare with default physical education index and resolve, obtain moving aspects such as amendment scheme such as position, speed, angle, and with result's output on display device.
5. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 4, it is characterized in that: described step C also comprises: in the image characteristics extraction unit, at first extract the characteristic composition of target travel by two value-based algorithms, characteristic composition is asked for its center of gravity, obtain the characteristic composition center; Then, set up the corresponding relation between the feature according to calculating to selected feature;
6. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 4, it is characterized in that: described step C also comprises: to gauge point mode of motion and the inertial parameter that obtains among the described step B, by the multi-sensor data blending algorithm of D-S evidence theory, obtain reflecting the consistance data of target travel feature.
7. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 4, it is characterized in that: described step D also comprises:
D1, the various sample pattern data of collection mark the sample pattern data that collect;
D2, go out the proper vector of its essential characteristic of reflection from described sample pattern extracting data one by one;
D3, divide according to described proper vector under category regions, make the proper vector that only comprises similar sample in each different classes of zone after dividing, set up sorter from proper vector to mapping relations the affiliated classification;
D4, pattern data to be identified are handled, extracted its proper vector;
D5, the proper vector of pattern data to be identified is input to described sorter, sorter is differentiated according to its proper vector, obtains the identification result to these pattern data to be identified.
The identification result of D6, pattern data is input in virtual instruction environment and the action resolution unit, by display device, and feedback output movement state.
8. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 7, it is characterized in that: described step D2 also comprises:
D21, described sample pattern data are carried out pre-service, obtain training data;
D22, from training data, extract the characteristic component of reflection training data essential characteristic;
D23, described characteristic component is made up, obtain described proper vector.
9. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 7, it is characterized in that: described step D4 also comprises:
D41, described pattern data to be identified are carried out pre-service, obtain Identification Data;
D42, from Identification Data, extract the characteristic component of reflection Identification Data essential characteristic;
D43, described characteristic component is made up, obtain described proper vector.
10. the construction method of the virtual physical culture teaching auxiliary system based on the action recognition technology as claimed in claim 7, it is characterized in that: described step D6 also comprises:
D61, according to the proper vector of Identification Data, self-defined different classes of standard operation pattern is set up the pattern java standard library;
D62, standard operation pattern and sports teaching procedure are customized for teaching plan, and import in the virtual teaching environment of physical education;
D63, identification result is input in the virtual teaching environment of physical education real man-machine interaction motion state; With the standard operation storehouse is reference standard, and identification result is resolved, and obtains moving amendment scheme;
D64, will move amendment scheme and pattern data identification result and be input to display device.
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2011
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