CN109634415B - It is a kind of for controlling the gesture identification control method of analog quantity - Google Patents

It is a kind of for controlling the gesture identification control method of analog quantity Download PDF

Info

Publication number
CN109634415B
CN109634415B CN201811507799.8A CN201811507799A CN109634415B CN 109634415 B CN109634415 B CN 109634415B CN 201811507799 A CN201811507799 A CN 201811507799A CN 109634415 B CN109634415 B CN 109634415B
Authority
CN
China
Prior art keywords
gesture
continuous
finger
hand
identification
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201811507799.8A
Other languages
Chinese (zh)
Other versions
CN109634415A (en
Inventor
李祝强
杜国铭
李美娟
赵雪洁
刘璐
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Top Technology Co Ltd
Original Assignee
Harbin Top Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Harbin Top Technology Co Ltd filed Critical Harbin Top Technology Co Ltd
Priority to CN201811507799.8A priority Critical patent/CN109634415B/en
Publication of CN109634415A publication Critical patent/CN109634415A/en
Application granted granted Critical
Publication of CN109634415B publication Critical patent/CN109634415B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/60Type of objects
    • G06V20/64Three-dimensional objects
    • 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

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Psychiatry (AREA)
  • Social Psychology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • User Interface Of Digital Computer (AREA)
  • Image Analysis (AREA)

Abstract

The invention proposes a kind of for controlling the gesture identification control method of analog quantity, the hand 3d space data that the present invention utilizes depth camera LeapMotion to provide, according to the positional relationship and direction relations progress static gesture identification between joint each in single-frame images;The variation of joint data carries out dynamic hand gesture recognition in multiple image;And the continuous gesture identification based on continuous multiple frames image, in terms of continuous gesture identification, eliminating the shake as caused by manpower operating reason or LeapMotion data error leads to the interruption of continuous gesture, to realize the Analog control of continuous gesture.

Description

It is a kind of for controlling the gesture identification control method of analog quantity
Technical field
The invention belongs to gesture identification control technology fields, more particularly to a kind of for controlling the gesture identification of analog quantity Control method.
Background technique
Gesture has the characteristics that non-contact, manipulation is convenient as a kind of important way of human-computer interaction, and existing gesture is known Other method mainly divides the method based on wearable device and vision.Method based on wearable device is to track hand using sensor The motion profile and timing information of portion in space, advantage is can to obtain accurate hand data, the disadvantage is that needing to dress each The complicated equipment of kind, influences the naturality of man-machine interaction experience.The method of view-based access control model is mainly based upon monocular cam and depth Camera is spent, monocular cam is lost depth information when obtaining image, can only identify the gesture of particular category, such as static Hand-type gesture;Be concentrated mainly in terms of depth camera static gesture identification, hand left and right brandish identification, control amount is also led If some switching values, however need to carry out some equipment continuous Analog control in real life, such as equipment Volume, temperature etc..
In addition, there is also some other problems when being controlled using gesture, it is on the one hand to exist between each gesture Certain similitude;It on the other hand is during dynamic gesture, since everyone motor habit and finger movement are successive Sequence is different, can usually generate the coupling of gesture, i.e., can include other dynamic gestures during some dynamic gesture.On The solution for stating problem not only relies on specific recognition methods, it is also necessary to perform some processing in control logic, become to gesture Some states during changing make the rejecting of corresponding constraint and interference gesture.
Summary of the invention
The invention aims to solve the problems of the prior art, a kind of gesture knowledge for controlling analog quantity is provided Sex control method.
The present invention is achieved by the following technical solutions, and the present invention proposes a kind of for controlling the gesture identification of analog quantity Control method,
Step 1 acquires hand 3d space data using camera, obtains a complete gesture motion;
The complete gesture motion is resolved into static gesture, dynamic gesture and continuous gesture by step 2;
Step 3, according between joint each in single-frame images positional relationship and direction relations carry out static gesture identification;
Step 4 is recognizing the laggard Mobile state gesture identification of static gesture or continuous gesture identification;If quiet recognizing The laggard Mobile state gesture identification of state gesture thens follow the steps 5;If carrying out continuous gesture identification after recognizing static gesture Execute step 7;
Step 5 carries out dynamic hand gesture recognition, if recognizing dynamic gesture thens follow the steps 6;If do not recognized dynamic State gesture then executes the corresponding operation of static gesture;
Step 6 carries out continuous gesture identification, if recognizing continuous gesture, by the static gesture recognized, dynamic hand Gesture and continuous gesture are merged, and gesture fusion results are obtained, and execute corresponding operation according to gesture fusion results;If no It recognizes continuous gesture and then executes the corresponding operation of dynamic hand gesture recognition result;
If step 7 recognizes continuous gesture, corresponding operation is executed according to the recognition result of continuous gesture;If Continuous gesture is not recognized, thens follow the steps 5.
Further, the static gesture includes digital 1 gesture, digital 2 gestures, digital 3 gestures and digital 5 gestures;Institute Stating dynamic gesture includes that two finger kneading gestures, three finger kneading gestures, gesture of clenching fist and palm brandish gesture;The continuous gesture packet Include horizontal plane linear motion gesture and horizontal plane circular motion gesture.
Further, digital 2 gesture is that thumb is stretched flat with index finger, remaining finger grips;Digital 3 gesture is thumb Refer to, index finger and middle finger are stretched flat, remaining finger grips;Described two refer to that kneading gesture is from digital 2 gestures to finger tip contacts;Described three Refer to that kneading gesture is from digital 3 gestures to finger tip contacts;The palm brandish gesture be the five fingers be stretched flat XOY plane it is suitable/inverse time Needle is brandished;The horizontal plane linear motion gesture is that three finger kneadings are slided along the x axis;The horizontal plane circular motion gesture is Two refer to that kneading is slided in XOZ plane around the fixed center of circle.
Further, the static gesture identification is based on the distance between each joint of hand and the centre of the palm ratio in single-frame images Example and direction relations between each finger bone direction and centre of the palm direction vector distinguish.
Further, the dynamic hand gesture recognition is based on the variation of distance, hand between finger fingertip each in multiple image Refer to that finger tip is identified to the change in location of the variation of the distance between the centre of the palm and the centre of the palm in space, the multiframe is discontinuous Frame.
Further, the continuous gesture identification is to carry out gesture analysis based on continuous frame sequence.
Further, the hand joint data of adjacent 5 frame image are continuously acquired in continuous gesture identification, then by phase Corresponding joint data weighting is averaged, finally using the average value collectively as the hand joint data of 5 frame images, to disappear Except the shake of data.
The hand 3d space data that the present invention utilizes depth camera LeapMotion to provide, according to respectively being closed in single-frame images Positional relationship and direction relations between section carry out static gesture identification;The variation of joint data carries out dynamic hand in multiple image Gesture identification;And the continuous gesture identification based on continuous multiple frames image eliminates in terms of continuous gesture identification since manpower is grasped Making shake caused by reason or LeapMotion data error leads to the interruption of continuous gesture, to realize the mould of continuous gesture Analog quantity control.
Detailed description of the invention
Fig. 1 is of the present invention a kind of for controlling the gesture identification control method flow chart of analog quantity.
Specific embodiment
Technical solution in the embodiment of the present invention that following will be combined with the drawings in the embodiments of the present invention carries out clear, complete Ground description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on this Embodiment in invention, every other reality obtained by those of ordinary skill in the art without making creative efforts Example is applied, shall fall within the protection scope of the present invention.
As shown in Figure 1, the present invention propose it is a kind of for controlling the gesture identification control method of analog quantity,
Step 1 acquires hand 3d space data using camera, obtains a complete gesture motion;
The complete gesture motion is resolved into static gesture, dynamic gesture and continuous gesture by step 2;
Step 3, according between joint each in single-frame images positional relationship and direction relations carry out static gesture identification;
Step 4 is recognizing the laggard Mobile state gesture identification of static gesture or continuous gesture identification;If quiet recognizing The laggard Mobile state gesture identification of state gesture thens follow the steps 5;If carrying out continuous gesture identification after recognizing static gesture Execute step 7;
Step 5 carries out dynamic hand gesture recognition, if recognizing dynamic gesture thens follow the steps 6;If do not recognized dynamic State gesture then executes the corresponding operation of static gesture;
Step 6 carries out continuous gesture identification, if recognizing continuous gesture, by the static gesture recognized, dynamic hand Gesture and continuous gesture are merged, and gesture fusion results are obtained, and execute corresponding operation according to gesture fusion results;If no It recognizes continuous gesture and then executes the corresponding operation of dynamic hand gesture recognition result;
If step 7 recognizes continuous gesture, corresponding operation is executed according to the recognition result of continuous gesture;If Continuous gesture is not recognized, thens follow the steps 5.
The static gesture includes digital 1 gesture, digital 2 gestures, digital 3 gestures and digital 5 gestures;The dynamic gesture Gesture is brandished including two finger kneading gestures, three finger kneading gestures, gesture of clenching fist and palm;The continuous gesture includes that horizontal plane is straight Line motion gesture and horizontal plane circular motion gesture.
Digital 1 gesture is stretched flat for index finger, remaining finger grips;Digital 2 gesture is that thumb is stretched flat with index finger, Remaining finger grips;Digital 3 gesture is that thumb, index finger and middle finger are stretched flat, remaining finger grips;Digital 5 gesture is five Finger is stretched flat;Described two refer to that kneading gesture is from digital 2 gestures to finger tip contacts;Described three refer to that kneading gesture is from digital 3 gestures To finger tip contacts;The gesture of clenching fist is to hold with a firm grip from digital 5 gestures to the five fingers;It is that the five fingers are stretched flat that the palm, which brandishes gesture, XOY plane is suitable/it brandishes counterclockwise;The horizontal plane linear motion gesture is that three finger kneadings are slided along the x axis;The horizontal plane Circular motion gesture is that two fingers are mediated in XOZ plane around fixed center of circle sliding.
Static gesture identification is based on the distance between each joint of hand and the centre of the palm ratio in single-frame images and respectively Direction relations between finger bone direction and centre of the palm direction vector (being pierced by perpendicular to palm plane and from the centre of the palm) carry out area Point.Such as digital 1 gesture, the distance between index finger tip to the centre of the palm to be significantly greater than other finger fingertips between the centre of the palm away from From while index finger most end bone (bone close to the centre of the palm) direction is perpendicular to centre of the palm vector, and the direction of other fingers bones It is almost parallel with centre of the palm direction vector, the identification of digital 1 gesture can be completed based on above-mentioned two condition.
The dynamic hand gesture recognition is based on the variation of distance, finger fingertip to the palm between finger fingertip each in multiple image The change in location of the variation of the distance between heart and the centre of the palm in space is identified that the multiframe is discontinuous frame.It is specific right It should be related to as shown in table 1.
1 dynamic gesture explanation of table
Described two refer to the identification process of kneading gesture are as follows: obtain present frame swivel of hand data, calculate thumb tip and index finger The distance between finger tip assert that the gesture is two finger kneading gestures, such as if the distance is less than a certain threshold value (preferably 30) Fruit is greater than a certain threshold value and then reacquires data or terminate process.
It is described three refer to kneading gesture identification process are as follows: obtain present frame swivel of hand data, calculate present frame under thumb with Index finger tip distance and thumb and middle fingertip distance, and calculate distance it is cumulative and;Obtain the 30th frame swivel of hand data in the past, meter Calculate thumb and index finger tip distance and thumb and middle fingertip distance under the 30th frame in the past, and calculate distance it is cumulative and;Judgement refers to The relative value and absolute value of sharp distance change, if relative value is that the distance of the 30th frame in the past adds up and subtract the distance of present frame It is cumulative to be greater than a certain threshold value (preferably 0.5) divided by the value of the cumulative sum of the distance of the 30th frame of past with after, also, absolute value was The distance for going the distance of the 30th frame to add up and subtract present frame adds up and is greater than a certain threshold value (preferably 60), and count is incremented, works as meter When number is greater than 10, determine that the gesture is that three fingers are mediated.
The identification process of the gesture of clenching fist are as follows: obtain present frame swivel of hand data, calculate separately the five fingers finger tip to the centre of the palm The distance between, calculate distance it is cumulative and;The 30th frame swivel of hand data in the past are obtained, calculate separately the five fingers finger tip between the centre of the palm Distance, calculate distance it is cumulative and;Judge distance change percentage, i.e., the distance of the 30th frame is cumulative in the past and subtracts present frame Distance is cumulative to be greater than a certain numerical value (preferably 0.4) divided by the value of the cumulative sum of the distance of the 30th frame of past with after, then it is assumed that the hand Gesture is gesture of clenching fist, and data are reacquired if being not more than or terminate process.
The identification process for brandishing gesture are as follows: obtain the 30th frame centre of the palm coordinate (x30, y30, z30) in the past, obtained Remove the 15th frame centre of the palm coordinate (x15, y15, z15), obtain present frame centre of the palm coordinate (x, y, z), calculate the 30th frame in the past and The 15th frame centre of the palm XOY plane direction of motion vector (x15-x30, y15-y30) of past calculates the 15th frame and present frame hand in the past Centre of the palm XOY plane direction of motion vector (x-x15, y-y15) calculates Outer Product of Vectors T, horizontal distance D and vertical range H, T= (x15-x30) * (y-y15)-(y15-y30) * (x-x15), D=│ x-x30 │, H=│ y-y30 │, if D is big greater than 80 and H Judge that T is equal to 0, is also less than 0 greater than 0 in 80, otherwise terminate process, terminates process if T is equal to 0, if T is greater than 0, then it represents that gesture is brandished counterclockwise, if T is less than 0, then it represents that brandish gesture clockwise.
The continuous gesture identification is to carry out gesture analysis based on continuous frame sequence.It is most main in continuous gesture identification What is wanted is exactly some stability, that is, the gesture motion identified cannot generate shake, while corresponding control strip will be with the movement of hand Consistent (following effect).Therefore in the Key dithering that the first step of identification is exactly data, the present invention is main in terms of Key dithering Shake is eliminated using the mean value smoothing method of continuous 5 frame image and improves stability, that is, continuously acquires the hand of adjacent 5 frame image Portion joint data, then corresponding joint data weighting is averaged, finally using the average value collectively as 5 frame images Hand joint data.
The continuous gesture includes linear horizontal plane linear motion and nonlinear horizontal plane circular motion.
It is described linear motion gesture recognition methods specifically: obtain 1-5 frame hand data, obtain thumb, index finger and Middle fingertip coordinate mean value smoothing x_T, x_I and x_M;6-10 frame hand data are obtained, thumb, index finger and middle fingertip are obtained Coordinate mean value smoothing x1_T, x1_I and x1_M;Thumb, index finger and middle fingertip displacement are calculated according to the result that above-mentioned steps obtain Accumulated value SumDis_T+=x_T-x1_T, SumDis_I+=x_I-x1_I and SumDis_M+=x_M-x1_M;Three are displaced Accumulated value carries out range estimation, if meeting SumDis_T > 5, SumDis_I > 5 and SumDis_M > 5, gesture simultaneously To be slided to X-axis positive direction;If meeting SumDis_T < -5, SumDis_I < -5 and < -5 SumDis_M, hand simultaneously Gesture is to slide to X-axis negative direction.
The recognition methods of the circular motion gesture specifically: judge whether to initialize the center of circle, if it is obtain continuous 5 Frame centre of the palm coordinate, and centre of the palm coordinate is smoothed to a bit, radius and initial angle are set, so that it is determined that central coordinate of circle (ox, oy, oz);Continuous 5 frame centre of the palm coordinate is obtained if not initializing the center of circle, and centre of the palm coordinate is smoothed to a bit (x, y, z);According to Central coordinate of circle and the centre of the palm coordinate for being smoothed to any calculate direction vector (x-ox, z-oz);It calculates between direction vector and-Z axis Included angle A lpha;Compare x and ox coordinate size, if x > ox, exports circumferential angle Alpha, if x < ox, exports circle All angle 360-Alpha.
Classification describes the recognition methods of various gestures in gesture identification, however a complete gesture control side Method can generate interference and misrecognition, especially in difference due to the similitude and coupling between gesture comprising various gestures When switching between gesture, misrecognition probability be will increase.That singly deposits can not settle the matter once and for all from recognition methods, therefore It needs to use restraint in control logic, the switching of especially different gesture states.By a complete gesture point in the present invention Solution is pocessed at the gesture of multiple and different types, and level is straight after reducing interfering with each other between gesture, such as two finger kneadings Line moves this gesture, has been split into static 2 gesture of number, dynamic two finger kneading gesture and horizontal plane straight line Motion gesture three parts, first with static gesture recognition detection to digital 2 gestures in control logic, after completing identification State under connecing just only there are two types of, refer to one is two and mediate, another kind is that (including hand is from LeapMotion without any movement Disappear in visual field), if detecting two finger kneading gestures on this basis, next state again only there are two types of, one is water Flat line motion gesture, another kind are without any movement (including hand disappears from LeapMotion visual field).So being based on Above-mentioned control logic all becomes the branch of only two states comprising the complicated gesture state of many branches, by this Control logic solves interfering with each other between gesture, improves the stability of gestural control system.
Now by taking multimedia player as an example, illustrate specific implementation step of the invention, player corresponding to corresponding gesture Function is as shown in table 2.
2 player function of table and corresponding gesture
Step a: judging player status, if closed state executes step b, if open state executes step c;
Step b: 1 gesture of static number opens player, executes step c;
Step c: determining whether to the operation (i.e. change player status) that corresponding function is done to player, if you do not need to The operation of corresponding function executes step d, if necessary to corresponding feature operation, executes step e;
Step d: player current state is maintained, and executes step c;
Step e: static gesture identification is carried out, and executes step f;
Step f: whether there are execution linear motion gesture instruction or circular motion gesture instruction, if executing step without instruction Rapid g executes step h, if there is instructing and being circular motion instruction, executes step if there is instructing and instructing for linear motion i;
Step g: carrying out dynamic hand gesture recognition, brandish gesture if detected, step j is executed, if detecting hand of clenching fist Gesture executes k, if detecting two finger kneading gestures, issues circular gesture and instructs and execute step f, if detecting that three fingers are mediated Gesture issues linear motion gesture instruction and executes step f, if dynamic gesture, which is not detected, executes step c;
Step h: player progress adjusts (linear motion gesture), executes step c;
Step i: volume adjustment (circular motion gesture) executes step c;
Step j: program switching executes step c;
Step k: closing player, executes step a;
Above to provided by the present invention a kind of for controlling the gesture identification control method of analog quantity, detailed Jie has been carried out It continues, used herein a specific example illustrates the principle and implementation of the invention, and the explanation of above embodiments is only It is to be used to help understand method and its core concept of the invention;At the same time, for those skilled in the art, according to this hair Bright thought, there will be changes in the specific implementation manner and application range, in conclusion the content of the present specification should not manage Solution is limitation of the present invention.

Claims (5)

1. a kind of for controlling the gesture identification control method of analog quantity, it is characterised in that:
Step 1 acquires hand 3d space data using camera, obtains a complete gesture motion;
The complete gesture motion is resolved into static gesture, dynamic gesture and continuous gesture by step 2;
Step 3, according between joint each in single-frame images positional relationship and direction relations carry out static gesture identification;
Step 4 is recognizing the laggard Mobile state gesture identification of static gesture or continuous gesture identification;If recognizing static hand The laggard Mobile state gesture identification of gesture thens follow the steps 5;It is executed if carrying out continuous gesture identification after recognizing static gesture Step 7;
Step 5 carries out dynamic hand gesture recognition, if recognizing dynamic gesture thens follow the steps 6;If not recognizing dynamic hand Gesture then executes the corresponding operation of static gesture;
Step 6, carry out continuous gesture identification, if recognizing continuous gesture, by the static gesture recognized, dynamic gesture and Continuous gesture is merged, and gesture fusion results are obtained, and executes corresponding operation according to gesture fusion results;If do not identified The corresponding operation of dynamic hand gesture recognition result is then executed to continuous gesture;
If step 7 recognizes continuous gesture, corresponding operation is executed according to the recognition result of continuous gesture;If no Continuous gesture is recognized, thens follow the steps 5;
The static gesture includes digital 1 gesture, digital 2 gestures, digital 3 gestures and digital 5 gestures;The dynamic gesture includes Two finger kneading gestures, three finger kneading gestures, gesture of clenching fist and palm brandish gesture;The continuous gesture includes horizontal plane straight line fortune Gesture of starting and horizontal plane circular motion gesture;
Digital 1 gesture is stretched flat for index finger, remaining finger grips;Digital 2 gesture is that thumb is stretched flat with index finger, remaining hand Finger gripping is tight;Digital 3 gesture is that thumb, index finger and middle finger are stretched flat, remaining finger grips;Digital 5 gesture is stretched for the five fingers It is flat;Described two refer to that kneading gesture is from digital 2 gestures to finger tip contacts;Described three refer to that kneading gesture is from digital 3 gestures to finger Point contact;The gesture of clenching fist is to hold with a firm grip from digital 5 gestures to the five fingers;The palm brandishes gesture, and to be that the five fingers are stretched flat flat in XOY Face is suitable/it brandishes counterclockwise;The horizontal plane linear motion gesture is that three finger kneadings are slided along the x axis;The horizontal plane circumference Motion gesture is that two fingers are mediated in XOZ plane around fixed center of circle sliding.
2. according to the method described in claim 1, it is characterized by: static gesture identification is based on hand in single-frame images Direction relations between the distance between each joint and the centre of the palm ratio and each finger bone direction and centre of the palm direction vector come into Row is distinguished.
3. according to the method described in claim 2, it is characterized by: the dynamic hand gesture recognition is based on each hand in multiple image Refer between finger tip the distance between the variation of distance, finger fingertip to the centre of the palm change in location of variation and the centre of the palm in space into Row identification, the multiframe are discontinuous frame.
4. according to the method described in claim 3, it is characterized by: the continuous gesture identification be based on continuous frame sequence come Carry out gesture analysis.
5. according to the method described in claim 4, it is characterized by: continuously acquiring adjacent 5 frame in continuous gesture identification The hand joint data of image, then corresponding joint data weighting is averaged, finally using the average value collectively as 5 The hand joint data of frame image, to eliminate the shake of data.
CN201811507799.8A 2018-12-11 2018-12-11 It is a kind of for controlling the gesture identification control method of analog quantity Active CN109634415B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811507799.8A CN109634415B (en) 2018-12-11 2018-12-11 It is a kind of for controlling the gesture identification control method of analog quantity

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811507799.8A CN109634415B (en) 2018-12-11 2018-12-11 It is a kind of for controlling the gesture identification control method of analog quantity

Publications (2)

Publication Number Publication Date
CN109634415A CN109634415A (en) 2019-04-16
CN109634415B true CN109634415B (en) 2019-10-18

Family

ID=66072551

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811507799.8A Active CN109634415B (en) 2018-12-11 2018-12-11 It is a kind of for controlling the gesture identification control method of analog quantity

Country Status (1)

Country Link
CN (1) CN109634415B (en)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110109547A (en) * 2019-05-05 2019-08-09 芋头科技(杭州)有限公司 Order Activiation method and system based on gesture identification
CN113553884B (en) * 2020-04-26 2023-04-18 武汉Tcl集团工业研究院有限公司 Gesture recognition method, terminal device and computer-readable storage medium
CN112084898B (en) * 2020-08-25 2024-02-09 西安理工大学 Assembly operation action recognition method based on static and dynamic separation
CN112446291B (en) * 2020-10-26 2024-07-12 杭州易现先进科技有限公司 Gesture recognition method, device, electronic device and storage medium
CN112509668A (en) * 2020-12-16 2021-03-16 成都翡铭科技有限公司 Method for identifying whether hand is gripping or not
CN112926423B (en) 2021-02-07 2023-08-25 青岛小鸟看看科技有限公司 Pinch gesture detection and recognition method, device and system
CN113126753B (en) * 2021-03-05 2023-04-07 深圳点猫科技有限公司 Implementation method, device and equipment for closing equipment based on gesture
CN113741701A (en) * 2021-09-30 2021-12-03 之江实验室 Brain nerve fiber bundle visualization method and system based on somatosensory gesture control
CN114063772B (en) * 2021-10-26 2024-05-31 深圳市鸿合创新信息技术有限责任公司 Gesture recognition method, device, equipment and medium

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102609093A (en) * 2012-02-16 2012-07-25 中国农业大学 Method and device for controlling video playing by using gestures
CN103455794A (en) * 2013-08-23 2013-12-18 济南大学 Dynamic gesture recognition method based on frame fusion technology
CN104571482A (en) * 2013-10-22 2015-04-29 中国传媒大学 Digital device control method based on somatosensory recognition
CN104750397A (en) * 2015-04-09 2015-07-01 重庆邮电大学 Somatosensory-based natural interaction method for virtual mine
CN105334960A (en) * 2015-10-22 2016-02-17 四川膨旭科技有限公司 Vehicle-mounted intelligent gesture recognition system
CN106934333A (en) * 2015-12-31 2017-07-07 芋头科技(杭州)有限公司 A kind of gesture identification method and system
CN106990840A (en) * 2017-03-27 2017-07-28 联想(北京)有限公司 control method and control system
CN107272899A (en) * 2017-06-21 2017-10-20 北京奇艺世纪科技有限公司 A kind of VR exchange methods, device and electronic equipment based on dynamic gesture
CN107578023A (en) * 2017-09-13 2018-01-12 华中师范大学 Man-machine interaction gesture identification method, apparatus and system
CN107765855A (en) * 2017-10-25 2018-03-06 电子科技大学 A kind of method and system based on gesture identification control machine people motion
CN108549489A (en) * 2018-04-27 2018-09-18 哈尔滨拓博科技有限公司 A kind of gestural control method and system based on hand form, posture, position and motion feature
CN108629272A (en) * 2018-03-16 2018-10-09 上海灵至科技有限公司 A kind of embedded gestural control method and system based on monocular cam
CN108646910A (en) * 2018-03-20 2018-10-12 重庆邮电大学 A kind of Three-Dimensional Dynamic finger text input system and method based on depth image

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8086971B2 (en) * 2006-06-28 2011-12-27 Nokia Corporation Apparatus, methods and computer program products providing finger-based and hand-based gesture commands for portable electronic device applications
RU2013147803A (en) * 2013-10-25 2015-04-27 ЭлЭсАй Корпорейшн GESTURE RECOGNITION SYSTEM WITH FINITE AUTOMATIC CONTROL OF INDICATOR DETECTION UNIT AND DYNAMIC GESTURE DETECTION UNIT
CN105930785B (en) * 2016-04-15 2017-05-03 潍坊科技学院 Intelligent concealed-type interaction system
CN108537147B (en) * 2018-03-22 2021-12-10 东华大学 Gesture recognition method based on deep learning
CN108572734A (en) * 2018-04-23 2018-09-25 哈尔滨拓博科技有限公司 A kind of gestural control system based on infrared laser associated image

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102609093A (en) * 2012-02-16 2012-07-25 中国农业大学 Method and device for controlling video playing by using gestures
CN103455794A (en) * 2013-08-23 2013-12-18 济南大学 Dynamic gesture recognition method based on frame fusion technology
CN104571482A (en) * 2013-10-22 2015-04-29 中国传媒大学 Digital device control method based on somatosensory recognition
CN104750397A (en) * 2015-04-09 2015-07-01 重庆邮电大学 Somatosensory-based natural interaction method for virtual mine
CN105334960A (en) * 2015-10-22 2016-02-17 四川膨旭科技有限公司 Vehicle-mounted intelligent gesture recognition system
CN106934333A (en) * 2015-12-31 2017-07-07 芋头科技(杭州)有限公司 A kind of gesture identification method and system
CN106990840A (en) * 2017-03-27 2017-07-28 联想(北京)有限公司 control method and control system
CN107272899A (en) * 2017-06-21 2017-10-20 北京奇艺世纪科技有限公司 A kind of VR exchange methods, device and electronic equipment based on dynamic gesture
CN107578023A (en) * 2017-09-13 2018-01-12 华中师范大学 Man-machine interaction gesture identification method, apparatus and system
CN107765855A (en) * 2017-10-25 2018-03-06 电子科技大学 A kind of method and system based on gesture identification control machine people motion
CN108629272A (en) * 2018-03-16 2018-10-09 上海灵至科技有限公司 A kind of embedded gestural control method and system based on monocular cam
CN108646910A (en) * 2018-03-20 2018-10-12 重庆邮电大学 A kind of Three-Dimensional Dynamic finger text input system and method based on depth image
CN108549489A (en) * 2018-04-27 2018-09-18 哈尔滨拓博科技有限公司 A kind of gestural control method and system based on hand form, posture, position and motion feature

Also Published As

Publication number Publication date
CN109634415A (en) 2019-04-16

Similar Documents

Publication Publication Date Title
CN109634415B (en) It is a kind of for controlling the gesture identification control method of analog quantity
Zhou et al. A novel finger and hand pose estimation technique for real-time hand gesture recognition
CN104238736B (en) Utilize the device, method and system for grasping Object identifying movement
Baldauf et al. Markerless visual fingertip detection for natural mobile device interaction
CN101901052B (en) Target control method based on mutual reference of both hands
KR101360149B1 (en) Method for tracking finger motion based on sensorless and apparatus thereof
CN103294996A (en) 3D gesture recognition method
JP7212067B2 (en) Image synthesizing method and apparatus
Wu et al. Robust fingertip detection in a complex environment
US10013070B2 (en) System and method for recognizing hand gesture
CN105589553A (en) Gesture control method and system for intelligent equipment
CN107357414B (en) Click action recognition method and device
CN109543644B (en) Multi-modal gesture recognition method
CN105335711A (en) Fingertip detection method in complex environment
CN110837792A (en) Three-dimensional gesture recognition method and device
CN107450717B (en) Information processing method and wearable device
EP3095072A1 (en) Contour-based classification of objects
CN110069125B (en) Virtual object control method and device
Vančo et al. Evaluation of static hand gesture algorithms
Li et al. Hand gesture tracking and recognition based human-computer interaction system and its applications
JP2014106603A (en) Information terminal device
AlSaedi et al. An efficient hand gestures recognition system
Panduranga et al. Dynamic hand gesture recognition system: a short survey
CN103400118A (en) Gesture control method capable of adaptively adjusting mapping relation
Zhang et al. Research on gesture recognition based on improved template matching algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant