CN107765855A - A kind of method and system based on gesture identification control machine people motion - Google Patents

A kind of method and system based on gesture identification control machine people motion Download PDF

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CN107765855A
CN107765855A CN201711009892.1A CN201711009892A CN107765855A CN 107765855 A CN107765855 A CN 107765855A CN 201711009892 A CN201711009892 A CN 201711009892A CN 107765855 A CN107765855 A CN 107765855A
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gesture
user
machine people
image
control
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胡江平
赵航
樊帮正
张榆平
朱宏
杨忠孝
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University of Electronic Science and Technology of China
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017Gesture based interaction, e.g. based on a set of recognized hand gestures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/22Matching criteria, e.g. proximity measures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • G06T7/246Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/44Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/107Static hand or arm
    • G06V40/113Recognition of static hand signs
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20Movements or behaviour, e.g. gesture recognition
    • G06V40/28Recognition of hand or arm movements, e.g. recognition of deaf sign language
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10016Video; Image sequence
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30196Human being; Person
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/107Static hand or arm
    • G06V40/117Biometrics derived from hands

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  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • Computer Vision & Pattern Recognition (AREA)
  • General Engineering & Computer Science (AREA)
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  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
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  • Evolutionary Computation (AREA)
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  • General Health & Medical Sciences (AREA)
  • Psychiatry (AREA)
  • Social Psychology (AREA)
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Abstract

The invention discloses a kind of method and system based on gesture identification control machine people motion.Methods described includes:User makes gesture, and obtains the image or video of user gesture;Described image is handled, acquisition possesses the representational gesture feature image of user gesture;Or the processing video, obtain user gesture and be intended to;The gesture feature image or user gesture are intended to match with Pre-defined gesture by gesture identification, after the match is successful, obtain control instruction corresponding with the Pre-defined gesture matched, and the control instruction is transmitted to controlled machine people;The present invention has the advantage that:Using new man-machine interaction mode, user only need to make in camera picture simple gesture can control machine people, simplify interaction, reduce interactive difficulty.

Description

A kind of method and system based on gesture identification control machine people motion
Technical field
It is more particularly to a kind of to be moved based on gesture identification control machine people the present invention relates to the control technology field of robot Method and system.
Background technology
With the development of science and technology, smart machine is also widely used among live and work, is provided for people The service such as diversified entertainment way and reduction workload.But some smart machine builds are larger, system is more complicated, program Operation is more complicated cumbersome, so as to considerably increase the difficulty that domestic consumer's study uses.So it can simply give intelligence machine People sends instruction, and intelligent robot makes corresponding actions again, simplifies interactive process and reduces interaction difficulty, becomes at present It is badly in need of the realistic problem solved.
Under the trend of human-computer interaction technology development, man-machine interaction mode can gradually easily facilitate operation, it is no longer necessary to The input equipments such as traditional mouse, keyboard, traditional screen display output are also not intended to be limited to certainly, I/O mode will It is varied.No longer be point-to-point input data in the current big data epoch, but add language, posture, The input datas such as environmental condition, to improve interactive efficiency.Interactive mode also can be gradually intelligent, is no longer with keyboard, mouse, hand The input data of the equipment such as plate slowly is write, but the manifestation mode such as body gesture, voice directly from user quickly obtains Interactive information, reduce interactive difficulty.The operation of interactive mode also can more hommization, traditional approach is to need user to go to fit Answer the interactive mode of machine, centered on machine, the thus difficulty of increased interaction, present interactive mode be using user as Center, interacted in a manner of meeting user, make full use of the cooperative cooperatings such as the vision, tactile, voice of people, realize hommization , free efficient input and output, greatly lift the experience of user.The application field of Gesture Recognition mainly has:Machine Device people, digital product, sign Language Recognition, remote control, virtual reality technology etc., at present robot control aspect should With being also a very concerned field.
In terms of comprehensive, new interactive mode can be people-oriented, using machine as multichannel, multi-mode, multimedia sense The other receiver of knowledge, transmission information is come by modes such as gesture, voice, body appearance, faces, and passing through Computer Identification and Analysis User view, then make suitable response.This respect research at present is quite a few, there is gesture identification, recognition of face, human body tracking etc. Gesture identification based on computer vision, it is that gesture motion image is obtained by equipment such as vision cameras, is carrying out digitized map As Treatment Analysis, it is able to identify gesture, then reaches the purpose of man-machine interaction.New interactive mode is more convenient, intelligence, efficiency Efficiently, the developing direction of human-computer interaction technology is also complied with.
The content of the invention
It is an object of the invention to using more convenient, intelligence, efficient man-machine interactive mode, there is provided one kind is based on hand Gesture identifies the method and system of control machine people, and user can make the motion that gesture carrys out control machine people, improve user with The interactive efficiency of robot and convenient degree.
In order to realize foregoing invention purpose, the invention provides the method based on gesture identification control machine people, including:
Step 1: user makes gesture, and obtain the image or video of user gesture;
Step 2: processing described image, the gesture feature image of acquisition user's static gesture;Or the processing video, The gesture for obtaining user's dynamic gesture is intended to;
Step 3: carrying out gesture identification, the gesture feature image or user gesture are intended to and Pre-defined gesture Match somebody with somebody, after the match is successful, obtain control instruction corresponding with the Pre-defined gesture matched, and the control instruction is transmitted to controlled Robot.
Preferably, methods described also includes establishing gesture ATL, specially sets the Pre-defined gesture, each is pre- Define gesture and correspond to corresponding control instruction;The gesture ATL includes static gesture ATL and dynamic gesture ATL.
Preferably, the gesture includes static gesture and dynamic gesture;The static gesture, including by temporarily it is static not Dynamic finger, palm or palm makes certain special shape or posture together with arm;The dynamic gesture, including by one section The gesture for the time-varying that a series of continuous static gestures in time are formed.
Preferably, the step of processing described image, it is specially:Pass through filtering process, Morphological scale-space, color space Changed with skin color segmentation and separate from the static gesture image gesture area of user's static gesture, and to the hand Gesture area carries out profile description, obtains the gesture contour images of user's static gesture.
Preferably, the video of the processing user gesture, including Camshift tracings, obtain dynamic gesture and are intended to:When When user gesture is appeared in the range of vision camera, gesture is just captured, and is positioned, then captures next two field picture again The position of middle palm, the moving direction of palm is judged by alternate position spike, to obtain dynamic gesture intention.
The present invention also provides a kind of system based on gesture identification control machine people motion, including:
Vision camera, the image or video of the gesture made for obtaining user;
Graphics processing unit, for handling described image, obtain the gesture feature image of user's static gesture, or processing The video, the gesture for obtaining user's dynamic gesture are intended to;
Computing unit is controlled, for being intended to match with Pre-defined gesture by the gesture feature image or gesture, is matched After success, control instruction corresponding with the Pre-defined gesture matched is obtained, and the control instruction is transmitted to controlled machine people.
Further, described image processing unit and control computing unit are integrated into a control device.
Preferably, the control device is desktop computer or server.
Further, the vision camera, graphics processing unit and control computing unit are integrated into a control and set It is standby.
Preferably, the control device is notebook computer, tablet personal computer or smart mobile phone.
Compared with prior art, the beneficial effects of the present invention are:User only needs to make in camera picture simply Gesture can control machine people, simplify interaction, reduce interactive difficulty.Meanwhile the height collection of intelligent movable equipment Into with it is portable, make the required hardware device of the present invention more integrated, portable, contribute to user to be convenient for carrying, expand this hair The bright scope of application, and possess the prospect of being widely applied.
Brief description of the drawings
Fig. 1 is the flow chart of the embodiment of method and system one of gesture identification control machine people of the present invention.
Fig. 2 is the static gesture figure of the embodiment of method and system one of gesture identification control machine people of the present invention.
Fig. 3 is the robot control flow chart of the embodiment of method and system one of gesture identification control machine people of the present invention.
Fig. 4 is the robot course Parameter Map of the embodiment of method and system one of gesture identification control machine people of the present invention.
The system schematic of the embodiment of method and system one of Fig. 5 gesture identification control machine people of the present invention.
Fig. 6 is the static gesture control machine people of the embodiment of method and system one of gesture identification control machine people of the present invention Move example 1.
Fig. 7 is the static gesture control machine people of the embodiment of method and system one of gesture identification control machine people of the present invention Move example 2.
Fig. 8 is the dynamic gesture control machine people of the embodiment of method and system one of gesture identification control machine people of the present invention Move example 1.
Fig. 9 is the dynamic gesture control machine people of the embodiment of method and system one of gesture identification control machine people of the present invention Move example 2.
Marked in figure:1- vision cameras, 2- graphics processing units, 3- control computing units.
Embodiment
Below in conjunction with the accompanying drawings and embodiment the present invention is described in further detail.But this should not be interpreted as to the present invention The scope of above-mentioned theme is only limitted to following embodiment.
Referring to Fig. 1, the method based on gesture identification control machine people disclosed in one embodiment of the invention is applied to control and moved The typical case scene of mobile robot movement is described in detail.
Step S100, user gesture is obtained
User is interacted with system, and Pre-defined gesture, the vision shooting are made in the vision camera picture Head obtains images of gestures or video;The vision camera can intelligently detect whether vision camera has been switched on, such as Open, images of gestures and video are directly obtained by vision camera, if not opening, first open vision camera, then taken the photograph by vision As head obtains images of gestures and video;Static gesture control can also be carried out by the selection of user or dynamic gesture controls, To control the working method of the vision camera:When selecting static gesture control, then user is obtained by vision camera Static gesture image;When selecting dynamic gesture control, then user's dynamic gesture video is obtained by vision camera.
In the preferred embodiment of the invention, it is to carry out static gesture control that the vision camera, which can be identified intelligently, Or dynamic gesture control:When the gesture that user makes in vision camera picture, (for example, in 2 seconds) are not sent out in the short time Raw movement, then be considered as static gesture, carries out shooting image function;It is short when the gesture that user makes in vision camera picture (for example, in 2 seconds) are moved in time, then are considered as dynamic gesture, carry out shooting video capability.
Step S200, user gesture image or video are handled
By described image processing unit, user gesture result is obtained;
When user gesture is static gesture, then image procossing is carried out, to obtain the gesture feature figure of user's static gesture Picture;Specifically, changed by filtering process, Morphological scale-space, color space and skin color segmentation by the gesture of user's static gesture Area separates from the static gesture image, and carries out profile description to the gesture area, and it is quiet to obtain user The gesture contour images of state gesture;
When user gesture is dynamic gesture, then by Camshift tracings, the gesture for obtaining dynamic gesture is intended to:When When user gesture is appeared in the range of vision camera, gesture is just captured, and is positioned, then captures next two field picture again The position of middle palm, the moving direction of palm is judged by alternate position spike, to obtain the gesture of dynamic gesture intention;
The CamShift tracings are only the preferred gesture tracking method of one embodiment of the invention.World's left-hand seat at present Gesture tracking mainly has three:Kalman filtering (Kalman filter) tracing, light stream (optic flow) tracing and CamShift tracings, the gesture tracking method can be completed at the step S200 images of the method for one embodiment of the invention The gesture for managing the acquisition dynamic gesture of unit is intended to function, and under disturbance factor, CamShift tracings can be realized Tracking to user gesture, experiment effect is preferable, therefore selects CamShift tracings as currently preferred gesture tracking Method.
Step S300, gesture identification
By controlling computing unit, the gesture feature image or gesture are intended to match with Pre-defined gesture, matched After success, control instruction corresponding with the Pre-defined gesture matched is obtained, then transmits the control instruction to robot.
In the preferred embodiment of the invention, gesture identification result can also be shown by display screen.
The method of one embodiment of the invention also includes establishing gesture ATL, specially sets the Pre-defined gesture, often A kind of Pre-defined gesture corresponds to corresponding control instruction;The gesture ATL includes static gesture ATL and dynamic gesture mould Plate storehouse.
It is the static gesture ATL in one embodiment of the invention referring to table 1, Fig. 2, when gesture is " 1 refers to ", identification knot Fruit is " 1 ", and control machine people does the motion for moving forward a certain distance;When gesture is " 2 refer to ", recognition result is " 2 ", control Robot processed moves right the motion of a certain distance;When gesture is " 3 refer to ", recognition result is " 3 ", and control machine people does It is moved to the left the motion of a certain distance;When gesture is " 4 refer to ", recognition result is " 4 ", and control machine people, which does, to be retreated necessarily The motion of distance;When gesture is " palm ", recognition result is " 5 ", and control machine people stops current action, is parked in original place, Wait instructs next time;
In the preferred embodiment of the invention, in order to reduce serious forgiveness, the degree of accuracy is improved, each gesture can repeat to enroll (for example, repeating admission 100 or more) similar gesture is as template.
Table 1
It is the dynamic gesture ATL in one embodiment of the invention referring to table 2.When hand is to left, recognition result is “Left!", control machine people is moved to the left the motion of a certain distance;When hand is to during right translation, recognition result is “Right!", control machine people moves right the motion of a certain distance;When hand translates up, recognition result is “Ahead!", control machine people does the motion for moving forward a certain distance;When subordinate translates, recognition result is " Back!", Control machine people does the motion for retreating a certain distance backward;When hand makes fit, recognition result is " Stop!", control Robot stops current action, is parked in original place, and wait instructs next time.
Table 2
The controlled machine people obtains and performs control command.Referring to Fig. 3,4, the fortune of the robot of one embodiment of the invention Dynamic control is realized:Using the initial initial point of robot as origin, direct north is the positive direction of principal axis of Y, with Y-axis turn clockwise 90 ° for X just Direction of principal axis axle, global coordinate system is established, the information of robot controller is transferred to after system identification gesture, wherein reference coordinate is Referring to target in the information of transmission, relative to the position of robot, θ is target location relative coordinate and global coordinate system X positive axis institute shape Into angle, then by controller control machine people move, finally reach objective after be such as not connected to new instruction, machine Device people will stop moving;The initial velocity of robot is first to set in advance, can control two by controlling to adjust rotating speed thereafter The speed of wheel.
It is as follows that robot motion implements step:
The first step:Machine after the angle α of robot forward direction and direct north, motion before the motion of calculating electronic compass feedback The angle Φ of people's target point and direct north, α and Φ difference e (t) is calculated, if not equal to 0, rotated in place, until Untill difference is 0, to determine direction of advance;
Second step:Sampled during advance, judge whether angle α and Φ difference e (t) exceed error threshold, Robot both sides vehicle wheel rotational speed is adjusted by PID again, to realize that the robot for making deviation returns correct navigation channel, until arriving Up to target point.
Fig. 5 is a kind of system construction drawing based on gesture identification control machine people motion that one embodiment of the invention provides, The system includes:Vision camera 1, graphics processing unit 2, control computing unit 3;
The vision camera 1, for obtaining the image or video of user gesture, it can be monocular, binocular or three Mesh camera.Monocular cam, which can be used only, in the present invention can complete the acquisition of user gesture image or video, so as to To reduce the hardware cost of measuring system.
Described image processing unit 2, for handling described image or video, when user gesture is static gesture When, the gesture feature image of user's static gesture is obtained by image procossing, when user gesture is dynamic gesture, is passed through The gesture that CamShift tracings obtain dynamic gesture is intended to.
The control computing unit 3, for the gesture feature image or gesture to be intended to match with Pre-defined gesture, After the match is successful, control instruction corresponding with the Pre-defined gesture matched is obtained, then passes control instruction by communication module Transport to controlled machine people.Specifically, the control computing unit 3 can be provided with storage device, can be deposited in advance by performing Storage programmed instruction (for example, application program of gesture control robot) in the storage device obtains gesture identification result, and And the ATL of the Pre-defined gesture is also stored in the storage device of the control computing unit 3.
More clearly illustrate the mistake for passing through gesture control robot motion below in conjunction with the example of one embodiment of the invention Journey.
Referring to Fig. 6, when user makes static gesture, user makes the gesture of " 1 refers to ", and system is imaged by the vision First 1 capture user gesture image, described image processing unit 2 pre-process to images of gestures, and the control computing unit 3 will Gesture feature image after processing is matched with Pre-defined gesture, and it is " 1 " that result is identified after the match is successful, is obtained simultaneously Corresponding control instruction is " travelling forward ", and the controller of the robot is transferred to by communication module, passes through controller Control machine people makes the action of advance.
Referring to Fig. 7, when user makes static gesture, user makes the gesture of " 2 refer to ", and system is imaged by the vision First 1 capture user gesture image, described image processing unit 2 pre-process to images of gestures, and the control computing unit 3 will Gesture feature image after processing is matched with Pre-defined gesture, and it is " 2 " that result is identified after the match is successful, is obtained simultaneously Corresponding control instruction is " moving right ", and the controller of the robot is transferred to by communication module, passes through controller Control machine people makes the action walked to the right.
Referring to Fig. 8, user makes the gesture of " to left ", and system captures user gesture by the vision camera 1, By the CamShift tracings of described image processing unit 2 determine user gesture be intended to, then by control computing unit 3 with Pre-defined gesture is matched, and it is " Left that result is identified after the match is successful!", while obtain corresponding control instruction and be " to left movement ", and be transferred to by communication module the controller of the robot, by controller control machine people make to The action that a left side is walked.
Referring to Fig. 9, user makes the gesture of " translation downwards ", and system captures user gesture by the vision camera 1, The gesture for determining user by the CamShift tracings of graphics processing unit 2 is intended to, then by controlling computing unit 3 with making a reservation for Adopted gesture is matched, and after the match is successful, it is " Back to be identified result!", while obtain corresponding control instruction for " after Move back ", and the controller of the robot is transferred to by communication module, the dynamic of retrogressing is made by controller control machine people Make.
It should be appreciated that " embodiment " or " preferred embodiment " that specification is previously mentioned in the whole text means have with embodiment During special characteristic, structure or the characteristic of pass are included at least one embodiment of the present invention.Therefore, go out everywhere in entire disclosure Existing " in one embodiment " or " in a preferred embodiment " not necessarily refers to identical embodiment.In addition, these are specific Feature, structure or characteristic can in any suitable manner combine in one or more embodiments, also, the present invention it is each In individual embodiment, the size of the sequence number of above-mentioned each process is not meant to the priority of execution sequence, and the execution sequence of each process should Determined with its function and internal logic, the implementation process without tackling the embodiment of the present invention forms any restriction.
In embodiment provided herein, it should be understood that the method and system provided, can be by others side Formula is realized.Apparatus embodiments described above are only schematical, for example, described image processing unit, control calculate list Member can be combined into One function unit, or described image processing unit is segmented into static gesture processing unit and dynamic hand Gesture processing unit, the connection between these units can also be directly connected to by communication interface, can also pass through radio communication INDIRECT COUPLING.And the Pre-defined gesture and corresponding control instruction can also be other control instructions, for example, with When family is by gesture control television set, " 1 refers to " can correspond to the instruction of " switching on and shutting down ", and " 2 refer to " can correspond to " increase volume " Instruction, " 3 refer to " can correspond to the instruction of " reduction volume ", and " 4 refer to " can correspond to the instruction of " a upper channel ", and " 5 refer to " can be with The instruction of corresponding " next channel ".
Also, the method and system of one embodiment of the invention is realized in the form of hardware adds software.Thus propose, at this In invention preferred embodiment, a computer equipment can be used (for example, personal computer, tablet personal computer or intelligent hand Machine), and by operating in the application program on the smart machine (application program carries human-computer interaction interface), described in completion Vision camera, graphics processing unit and the function of controlling computing unit.Wherein, the vision camera can be notebook electricity Brain, tablet personal computer, the camera built in smart mobile phone, or the camera that desktop computer, server are external;At described image Unit and control computing unit are managed, can be personal computer, server, tablet personal computer or smart mobile phone, and these set The application program of standby upper operation.In summary, method and system of the invention possesses high integration, portable degree, and the present invention Gather around and have broad application prospects.
" one embodiment of the invention " and " preferred embodiment of the invention " described above are only the sides of being preferable to carry out of the present invention Formula, be not intended to limit the invention, it is noted that for made within the principle of the art any modification, equally replace Change and improve, be regarded as within protection scope of the present invention.

Claims (10)

  1. A kind of 1. method based on gesture identification control machine people motion, it is characterised in that including:
    Step 1: user makes gesture, and obtain the image or video of user gesture;
    Step 2: processing described image, the gesture feature image of acquisition user's static gesture;Or the processing video, obtain The gesture of user's dynamic gesture is intended to;
    Step 3: carrying out gesture identification, the gesture feature image or gesture are intended to match with Pre-defined gesture, matched into After work(, control instruction corresponding with the Pre-defined gesture matched is obtained, and the control instruction is transmitted to controlled machine people.
  2. 2. according to the method for claim 1, it is characterised in that also include establishing gesture ATL, specially described in setting Pre-defined gesture, each Pre-defined gesture correspond to corresponding control instruction;The gesture ATL includes static gesture template Storehouse and dynamic gesture ATL.
  3. 3. according to the method for claim 1, it is characterised in that the gesture, including static gesture and dynamic gesture;It is described Static gesture, including by temporary transient actionless finger, palm or palm together with arm make certain special shape or Posture;The dynamic gesture, include the hand for the time-varying being made up of a series of continuous static gestures in a period of time Gesture.
  4. 4. according to the method for claim 1, it is characterised in that described the step of handling described image, be specially:Pass through filter Ripple processing, Morphological scale-space, color space and skin color segmentation conversion are by the gesture area of user's static gesture from described quiet Separated in state images of gestures, and profile description is carried out to the gesture area, obtain the gesture profile of user's static gesture Image.
  5. 5. according to the method for claim 1, it is characterised in that described the step of handling user gesture video, including Camshift tracings, obtain dynamic gesture and be intended to:When user gesture is appeared in the range of vision camera, hand is just captured Gesture, and positioned, the position of palm in next two field picture is then captured again, and the mobile side of palm is judged by alternate position spike To obtain the gesture of dynamic gesture intention.
  6. A kind of 6. system based on gesture identification control machine people motion, it is characterised in that including:
    Vision camera, the image or video of the gesture made for obtaining user;
    Graphics processing unit, for handling described image, obtain the gesture feature image of user's static gesture;Or processing institute Video is stated, the gesture for obtaining user's dynamic gesture is intended to;
    Computing unit is controlled, for being intended to match with Pre-defined gesture by the gesture feature image or gesture, is matched into After work(, control instruction corresponding with the Pre-defined gesture matched is obtained, and the control instruction is transmitted to controlled machine people.
  7. 7. system according to claim 6, it is characterised in that described image processing unit and control computing unit are integrated into One control device.
  8. 8. system according to claim 7, it is characterised in that the control device is desktop computer or server.
  9. 9. system according to claim 6, it is characterised in that the vision camera, graphics processing unit and control meter Calculate unit and be integrated into a control device.
  10. 10. system according to claim 9, it is characterised in that the control device be notebook computer, tablet personal computer or Smart mobile phone.
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CN108762250A (en) * 2018-04-27 2018-11-06 深圳市商汤科技有限公司 The control method and device of equipment, equipment, computer program and storage medium
CN109327760A (en) * 2018-08-13 2019-02-12 北京中科睿芯科技有限公司 A kind of intelligent sound and its control method for playing back
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CN111158457A (en) * 2019-12-31 2020-05-15 苏州莱孚斯特电子科技有限公司 Vehicle-mounted HUD (head Up display) human-computer interaction system based on gesture recognition
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CN113171472A (en) * 2020-05-26 2021-07-27 中科王府(北京)科技有限公司 Disinfection robot
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