CN202662011U - Physical education teaching auxiliary system based on motion identification technology - Google Patents
Physical education teaching auxiliary system based on motion identification technology Download PDFInfo
- Publication number
- CN202662011U CN202662011U CN 201120122435 CN201120122435U CN202662011U CN 202662011 U CN202662011 U CN 202662011U CN 201120122435 CN201120122435 CN 201120122435 CN 201120122435 U CN201120122435 U CN 201120122435U CN 202662011 U CN202662011 U CN 202662011U
- Authority
- CN
- China
- Prior art keywords
- action
- unit
- physical education
- pattern
- module
- 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.)
- Expired - Fee Related
Links
- 230000033001 locomotion Effects 0.000 title claims abstract description 54
- 238000000605 extraction Methods 0.000 claims abstract description 18
- 230000004927 fusion Effects 0.000 claims abstract description 17
- 238000012549 training Methods 0.000 claims abstract description 15
- 238000005259 measurement Methods 0.000 claims abstract description 12
- 238000012545 processing Methods 0.000 claims description 8
- 230000000386 athletic effect Effects 0.000 claims description 7
- 230000003993 interaction Effects 0.000 claims description 7
- 230000037147 athletic performance Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000002452 interceptive effect Effects 0.000 claims description 3
- 238000000034 method Methods 0.000 abstract description 10
- 230000003287 optical effect Effects 0.000 abstract description 9
- 238000013480 data collection Methods 0.000 abstract 2
- 230000035945 sensitivity Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 7
- 239000000284 extract Substances 0.000 description 2
- 239000000700 radioactive tracer Substances 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000875 corresponding effect Effects 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
Images
Landscapes
- Processing Or Creating Images (AREA)
Abstract
The utility model provides a physical education teaching auxiliary system based on a motion identification technology. 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 system 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 that the 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 utility model relates to man-machine interaction, action recognition and computer-aided instruction field, relates in particular to a kind of constructing system of physical education backup system.
Background technology
At present, be inertia tracer technique and optical tracking technology in field of human-computer interaction motion tracking technology relatively more commonly used.Inertia tracer technique: by in target Inertial Measurement Unit being set, measure the data such as acceleration, angular velocity, use based on this mathematical tool to resolve, obtain 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 all sidedly the motion feature of tracked target, can only finite sum reflects partly the movement characteristic of tracked target.Optical tracking technology: by the Monitor and track of specific luminous point on the target being finished the task of motion tracking.In theory, for any one point in space, as long as it can simultaneously by two video camera findings, then according to same in a flash image and the camera parameters of two shot by camera, namely can determine this constantly locus of this point.When video camera is taken continuously with sufficiently high speed, from image sequence, just can obtain this motion of point track.What wherein the processing of image was adopted is the three-dimensional image reconstruction technique, namely by the camera record image, forms dummy object by digitized processing, then demarcates by three dimensions, determines the locus of object.The characteristics of optical tracking technology are the motion conditions that can reflect all sidedly object, and precision is high; Shortcoming is to realize comparatively difficulty, and the scope of following the trail of is less.
CN10115888 discloses a kind of virtual sports system based on computer vision and its implementation, be used for multi-purpose computer, utilize computer vision to identify 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 in the motion of control virtual sports makes corresponding action.Its weak point: the identification range for actual act is less, and the action criteria degree is inadequate.
The utility model content
The purpose of this utility model provides a kind of physical education backup system based on the action recognition technology, solution utilizes 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, collection and the processing of special exercise information in realizing in a big way are applied to the auxiliary physical culture problems in teaching of computer virtual.
The technical scheme that its technical matters that solves the utility model adopts is: a kind of physical education backup system based on the action recognition technology, be used for PC or embedded host, it comprises that exercise data acquisition module, motion capture module, identification and training module, virtual instruction environment module form;
Described exercise data acquisition module further comprises: the specific wavelength pointolite, be no less than two cameras;
Described motion capture module further comprises: image characteristics extraction unit, three-dimensional fix unit, movable information resolve unit, Fusion 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 for measuring the inertial parameter of measured target, for the motion capture resume 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 Fusion unit.
Described motion capture module, wherein said three-dimensional fix unit by using gauge point becomes the position of image in two cameras, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, described Fusion unit adopts based on the Multisensor Data Fusion 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 action resolution unit is used for resolving the identification result of pattern data; Described virtual instruction environment is man-machine interaction platform, is used for providing the physical education scheme; Described display device is used for analysis result, the demonstration interactive action state of feedback athletic performance pattern identification, and its input end is connected with computing machine;
Described pattern java standard library comprises particular athletic activity pattern java standard library, nonspecific pattern java standard library and continuous action model bank.
Described particular athletic activity pattern java standard library, take the elemental motion of sports item as main, elemental motion, tennis elemental motion, golf swing, the 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 that is formed 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.
The beneficial effects of the utility model: owing to adopting inertia to follow the trail of and optical tracking dual mode concentrated expression target travel situation, effectively enlarged tracking range, improved the precision of measuring, solve inertia and followed the trail of the poor problem of motion identification, susceptibility that to obtain whole object information, can not do complexity, also solved the problem that poor, the effective tracking range of optical tracking technology rediscover is little and stop impact simultaneously.The utility model 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 standard.
Below with reference to drawings and Examples, invention is described in detail.
Description of drawings
Fig. 1 is that the utility model is based on the physical culture assisted teaching system schematic block diagram of action recognition technology.
Fig. 2 is the utility model exercise data acquisition module schematic block diagram.
Fig. 3 is the utility model motion capture module schematic block diagram.
Fig. 4 is the utility model identification and training module schematic block diagram.
Fig. 5 is the utility model virtual instruction environment module schematic block diagram.
Fig. 6 is that schematic block diagram is amplified in the part of Fig. 5.
Fig. 7 is the schematic block diagram of the utility model general structure.
Embodiment
Such as Fig. 1, shown in Figure 7, a kind of physical education backup system based on the action recognition technology is used for PC or embedded host, and it comprises that exercise data acquisition module 1, motion capture module 2, identification and training module 3, virtual instruction environment module 3 form;
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 motion capture module 2 further comprises: image characteristics extraction unit 21, three-dimensional fix unit 22, movable information resolve unit 23, Fusion unit 24;
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 for resolving the identification result of pattern data; Described virtual instruction environment 43 is man-machine interaction platform, is used for providing the physical education scheme; Described demonstration 44 equipment are used for analysis result, the demonstration interactive action state of feedback 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 for measuring the inertial parameter of measured target, process for motion capture 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 Fusion 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, take the elemental motion of sports item as main, elemental motion, tennis elemental motion, golf swing, the 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 that is formed 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.
Method of work of the present utility model, 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 processed, 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 gathers are for motion capture 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 Fusion 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 Fusion unit 24; Fusion unit 24 adopts the data message that obtains based on the Multisensor Data Fusion 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 gather 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 motion capture 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: such as the elemental motion of table tennis, tennis elemental motion, golf swing, bowling is delivered and is moved, that runs lifts leg action etc. take the elemental motion of sports item as main particular athletic activity pattern java standard library 45, such 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 47 that is formed by action 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 in the input virtual sports teaching environment; Identification result is input in the virtual instruction environment 43, realizes the man-machine interaction motion state; Take the action criteria pattern base as reference standard, resolved by action resolution unit 42 pairs of identification results, obtain moving amendment scheme (such 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 adopting, effectively enlarged tracking range, improved the precision of measuring, solve inertia and followed the trail of the poor problem of motion identification, susceptibility that to obtain whole object information, can not do complexity, also solved the problem that poor, the effective tracking range of optical tracking technology rediscover is little and stop impact 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 standard.
Claims (7)
1. the physical education backup system based on the action recognition technology is used for PC or embedded host, and it comprises that exercise data acquisition module, motion capture module, identification and training module, virtual instruction environment module form,
Described exercise data acquisition module further comprises: the specific wavelength pointolite, be no less than two cameras;
Described motion capture module further comprises: image characteristics extraction unit, three-dimensional fix unit, movable information resolve unit, Fusion 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 for measuring the inertial parameter of measured target, for the motion capture resume 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 Fusion unit.
2. a kind of physical education backup system based on the action recognition technology as claimed in claim 1, it is characterized in that: described motion capture module, wherein said three-dimensional fix unit by using gauge point becomes the position of image in two cameras, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, described Fusion unit adopts based on the Multisensor Data Fusion 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 action resolution unit is used for resolving the identification result of pattern data;
Described virtual instruction environment is man-machine interaction platform, is used for providing the physical education scheme;
Described display device is used for analysis result, the demonstration interactive action state of feedback athletic performance pattern identification, and its input end is connected with computing machine.
4. a kind of physical education backup system based on the action recognition technology as claimed in claim 3, it is characterized in that: described pattern java standard library comprises particular athletic activity pattern java standard library, nonspecific pattern java standard library and continuous action model bank.
5. a kind of physical education backup system based on the action recognition technology as claimed in claim 4, it is characterized in that: described particular athletic activity pattern java standard library, take the elemental motion of sports item as main, elemental motion, tennis elemental motion, golf swing, the bowling that comprises table tennis deliver action, run lift leg action etc.
6. a kind of physical education backup system based on the action recognition technology as claimed in claim 4, it is characterized in that: described nonspecific pattern java standard library, be the action model storehouse according to physical education requirement customization special applications, comprise the action of pommel horse sportsman elemental motion, gymnastics, the application of physical education animation game class etc.
7. a kind of physical education backup system based on the action recognition technology as claimed in claim 4, it is characterized in that: described continuous action model bank, the combination maneuver library that is formed 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.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201120122435 CN202662011U (en) | 2011-04-22 | 2011-04-22 | Physical education teaching auxiliary system based on motion identification technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201120122435 CN202662011U (en) | 2011-04-22 | 2011-04-22 | Physical education teaching auxiliary system based on motion identification technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN202662011U true CN202662011U (en) | 2013-01-09 |
Family
ID=47456901
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201120122435 Expired - Fee Related CN202662011U (en) | 2011-04-22 | 2011-04-22 | Physical education teaching auxiliary system based on motion identification technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN202662011U (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104882036A (en) * | 2015-05-27 | 2015-09-02 | 江西理工大学 | Digital fitness teaching system |
| CN105424009A (en) * | 2015-12-17 | 2016-03-23 | 安徽寰智信息科技股份有限公司 | Binocular measuring device |
| CN105498188A (en) * | 2016-02-01 | 2016-04-20 | 郑州华信学院 | Physical activity monitoring device |
| CN106075856A (en) * | 2016-07-24 | 2016-11-09 | 鲁辰超 | Self-service trainer aircraft |
| CN106527698A (en) * | 2016-11-02 | 2017-03-22 | 陕西圣尔雅馨电子科技有限公司 | Immersive simulation training real-time correction system |
| CN109011490A (en) * | 2018-10-24 | 2018-12-18 | 深圳市衡泰信科技有限公司 | Golf sports ground sensing device and method based on infrared binocular high-speed camera |
| CN109589585A (en) * | 2018-12-11 | 2019-04-09 | 东莞市强艺体育器材有限公司 | A kind of table tennis teaching method and system |
| CN112292720A (en) * | 2018-06-28 | 2021-01-29 | 韦斯特伯格控股公司 | Real-time golf swing training aid |
| CN113181619A (en) * | 2021-04-09 | 2021-07-30 | 青岛小鸟看看科技有限公司 | Exercise training method, device and system |
| CN113744300A (en) * | 2021-09-29 | 2021-12-03 | 宁波大学 | AI discerns sports trajectory data analysis system |
-
2011
- 2011-04-22 CN CN 201120122435 patent/CN202662011U/en not_active Expired - Fee Related
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104882036A (en) * | 2015-05-27 | 2015-09-02 | 江西理工大学 | Digital fitness teaching system |
| CN105424009A (en) * | 2015-12-17 | 2016-03-23 | 安徽寰智信息科技股份有限公司 | Binocular measuring device |
| CN105498188B (en) * | 2016-02-01 | 2018-09-07 | 郑州华信学院 | A kind of sports monitoring device |
| CN105498188A (en) * | 2016-02-01 | 2016-04-20 | 郑州华信学院 | Physical activity monitoring device |
| CN106075856A (en) * | 2016-07-24 | 2016-11-09 | 鲁辰超 | Self-service trainer aircraft |
| CN106527698B (en) * | 2016-11-02 | 2020-01-17 | 陕西圣尔雅馨电子科技有限公司 | Immersive simulation training real-time correction system |
| CN106527698A (en) * | 2016-11-02 | 2017-03-22 | 陕西圣尔雅馨电子科技有限公司 | Immersive simulation training real-time correction system |
| CN112292720A (en) * | 2018-06-28 | 2021-01-29 | 韦斯特伯格控股公司 | Real-time golf swing training aid |
| CN112292720B (en) * | 2018-06-28 | 2022-10-28 | 韦斯特伯格控股公司 | Real-time golf swing training aid |
| CN109011490A (en) * | 2018-10-24 | 2018-12-18 | 深圳市衡泰信科技有限公司 | Golf sports ground sensing device and method based on infrared binocular high-speed camera |
| CN109011490B (en) * | 2018-10-24 | 2021-02-02 | 深圳市衡泰信科技有限公司 | Golf sport ground sensing device and method based on infrared binocular high-speed camera shooting |
| CN109589585A (en) * | 2018-12-11 | 2019-04-09 | 东莞市强艺体育器材有限公司 | A kind of table tennis teaching method and system |
| CN113181619A (en) * | 2021-04-09 | 2021-07-30 | 青岛小鸟看看科技有限公司 | Exercise training method, device and system |
| US11872468B2 (en) | 2021-04-09 | 2024-01-16 | Qingdao Pico Technology Co., Ltd. | Sport training method and system and head-mounted VR device |
| CN113744300A (en) * | 2021-09-29 | 2021-12-03 | 宁波大学 | AI discerns sports trajectory data analysis system |
| CN113744300B (en) * | 2021-09-29 | 2024-05-28 | 宁波大学 | AI discernment sports track data analysis system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN202662011U (en) | Physical education teaching auxiliary system based on motion identification technology | |
| CN102243687A (en) | Physical education teaching auxiliary system based on motion identification technology and implementation method of physical education teaching auxiliary system | |
| CN107301370B (en) | A Limb Action Recognition Method Based on Kinect 3D Skeleton Model | |
| Kapur et al. | Gesture-based affective computing on motion capture data | |
| CN105551059A (en) | Power transformation simulation human body motion capturing method based on optical and inertial body feeling data fusion | |
| CN104992171A (en) | Method and system for gesture recognition and man-machine interaction based on 2D video sequence | |
| Elaoud et al. | Skeleton-based comparison of throwing motion for handball players | |
| CN103100205A (en) | Auxiliary device suitable for middle and primary school physical education evaluation and achieving method thereof | |
| Hachaj et al. | Effectiveness comparison of Kinect and Kinect 2 for recognition of Oyama karate techniques | |
| Chaves et al. | Human body motion and gestures recognition based on checkpoints | |
| Nie et al. | [Retracted] The Construction of Basketball Training System Based on Motion Capture Technology | |
| Chen et al. | Using real-time acceleration data for exercise movement training with a decision tree approach | |
| Schnürer et al. | Real-time 3D Pose Estimation from Single Depth Images. | |
| CN109758154A (en) | A kind of motion state determines method, apparatus, equipment and storage medium | |
| Choppin et al. | Marker-less tracking of human movement using Microsoft Kinect | |
| Bradshaw et al. | Tracking conductors hand movements using multiple wiimotes | |
| CN105225270A (en) | A kind of information processing method and electronic equipment | |
| Mu et al. | Slim-YOLO-PR_KD: an efficient pose-varied object detection method for underground coal mine | |
| Suo et al. | Digital human and embodied intelligence for sports science: advancements, opportunities and prospects | |
| Wang | Basketball sports posture recognition based on neural computing and visual sensor | |
| Li et al. | Gesture recognition based on Kinect v2 and leap motion data fusion | |
| Jain et al. | Gestarlite: An on-device pointing finger based gestural interface for smartphones and video see-through head-mounts | |
| CN203630717U (en) | Interaction system based on a plurality of light inertial navigation sensing input devices | |
| CN104680134B (en) | Quick human body detecting method | |
| TWM468728U (en) | Real time human body poses identification system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C17 | Cessation of patent right | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130109 Termination date: 20130422 |