CN109408037A - A kind of non-contacting mixing control method based on " hand+face expression+head pose " - Google Patents
A kind of non-contacting mixing control method based on " hand+face expression+head pose " Download PDFInfo
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- CN109408037A CN109408037A CN201811066599.3A CN201811066599A CN109408037A CN 109408037 A CN109408037 A CN 109408037A CN 201811066599 A CN201811066599 A CN 201811066599A CN 109408037 A CN109408037 A CN 109408037A
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 230000003993 interaction Effects 0.000 claims abstract description 48
- 238000001514 detection method Methods 0.000 claims abstract description 23
- 238000013461 design Methods 0.000 claims abstract description 15
- 230000002452 interceptive effect Effects 0.000 claims abstract description 15
- 210000003128 head Anatomy 0.000 claims description 47
- 238000002474 experimental method Methods 0.000 claims description 13
- 238000012360 testing method Methods 0.000 claims description 7
- 230000003321 amplification Effects 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 3
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- 239000008186 active pharmaceutical agent Substances 0.000 description 6
- 238000013473 artificial intelligence Methods 0.000 description 6
- 239000000700 radioactive tracer Substances 0.000 description 2
- 241000894006 Bacteria Species 0.000 description 1
- 206010044074 Torticollis Diseases 0.000 description 1
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- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/20—Software design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input 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
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
Abstract
The present invention relates to a kind of non-contacting mixing control methods based on " hand+face expression+head pose ", belong to the interaction gesture field in computer man-machine interacting.The invention includes the following steps: carrying out the identification of face critical point detection, the state of head pose, hand gesture first；Then customized facial gesture, head gesture, gesture interaction order；Mixing control method interactive interface is finally designed, and verifies the accuracy and accuracy of mixing control gesture.The present invention is using Face++ platform, Leap Motion as tool, face critical point detection and Leap Motion gestures detection according to Face++ platform design a set of new mixing interaction gesture, multimodal human-computer interaction is enriched, is of great significance to the development of computer man-machine interacting.
Description
Technical field
The present invention relates to a kind of non-contacting mixing control methods based on " hand+face expression+head pose ", in particular to
A kind of face critical point detection technology being combined under artificial intelligence, Leap Motion gesture tracer technique and it is based on JMF
Human face detection tech and dynamic gesture tracer technique are combined the one kind designed by the camera image acquisition technique of frame
The non-contacting mixing control method based on " hand+face expression+head pose ", the multichannel belonged in computer man-machine interacting are handed over
Mutual gesture scope.
Background technique
With the rapid development of artificial intelligence, the mankind are gradually into the AI epoch.Based on this trend, Baidu, Ali, Tencent,
The artificial intelligent platform such as Face++ develops rapidly, and the trend that a hundred flowers blossom occurs.The present invention is with Face++ platform
Based on face critical point detection technology, the mixing interaction control method that designs.
In recent years, as artificial intelligence is including recognition of face, Application on Voiceprint Recognition, speech recognition, gesture identification, posture knowledge
Not, there is the trend merged into each other in the progress of emotion recognition etc., intelligent algorithm and human-computer interaction.Because meeting the friendship of people
Mutual mode, multi-channel intelligent human-computer interaction (the Multi-Modal Human Computer based on artificial intelligence approach
Interaction, MMHCI) be considered as the following naturally human-computer interaction one of major way.
In today that artificial intelligence rapidly develops, the combination of artificial intelligence and human-computer interaction has become inevitable trend,
This will carry out huge prospect to the following man-machine interacting strip.Facial gesture and head pose are combined simultaneously, it can be preferably
Inquire into application value existing for new interaction channel.Realize the non-contacting mixing control based on " hand+face expression+head pose "
Method is of great significance for the exploration and research of multimodal human-computer interaction technology.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of non-contacting mixed based on " hand+face expression+head pose "
Combination control method carries out the identification of face critical point detection, the state of head pose, hand gesture first；Then customized face
Portion's gesture, head gesture, gesture interaction order；Mixing control method interactive interface is finally designed, and verifies mixing control gesture
Accuracy and accuracy.The technology reduces the dependence to touch-screen equipment, while solving people in computer man-machine interacting
With the confinement problems of the necessary close contact of computer.
The technical solution adopted by the present invention is that: a kind of non-contacting mixing control based on " hand+face expression+head pose "
Method includes the following steps:
(1) official website Face++ is first logged into, then register account number and logs on to oneself console, creation face is crucial
Point detection application；
(2) the camera environment based on JMF frame is configured, allows the available picture stream to camera, as " face table
The input source of feelings " and " head pose "；
(3) the face critical point detection application that code calls backstage creation, the face key point for needing to detect then are write
As shown in Fig. 2, obtaining eye state, mouth states and head pose detected value as shown in Figure 3；
(4) environment for configuring Leap Motion, can allow Leap Motion dynamically to obtain gesture, as gesture in this way
Input source；
(5) it writes code and realizes that the dynamic gesture of Leap Motion obtains in code；
(6) according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixes interaction hand
Gesture；
(7) computer interactive command corresponding to customized mixing interaction gesture；
(8) mixing gesture is carried out with customized interactive command corresponding, generates corresponding feedback effects；
(9) design mixing interaction gesture, which is applied, identifies mixing interaction gesture；
(10) accuracy and accuracy of contrived experiment verifying mixing interaction gesture；
The specific steps of the non-contacting mixing control method based on " hand+face expression+head pose " of one kind are such as
Under:
Step1, the official website Face++ is first logged into, then register account number and logs on to oneself console, then clicks
" application management " clicks " creation API key " creation face critical point detection application, generates " API key " and " API
Secret"；
Step2, camera environment of the configuration based on JMF frame, then write the data flow of Code obtaining camera and life
Input source at Image object, as " face expression " and " head pose "；
Step3, the face critical point detection application that code calls backstage creation is write, the face key point for needing to detect is such as
Shown in Fig. 2, left eye state (left_eye_status), right eye state (right_eye_status), mouth states are obtained
(mouthstatus) and head pose angle (headpose) detected value as shown in Figure 3；
Step4, the SDK file for downloading Leap Motion, and configure the environment of local system, can allow Leap in this way
Motion dynamically obtains gesture, the input source as gesture；
Step5, instantiation Controller object, and four kinds of gesture identifications of Leap Motion are opened, it enables a system to
The various gestures of Leap Motion are dynamically identified in code；
Step6, according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixing is handed over
Mutual gesture；
Computer interactive command corresponding to Step7, customized mixing interaction gesture, including choose, right click, left click, under
Sliding, upper cunning, left cunning, right cunning, amplification, diminution order；
Step8, customized mixing gesture is carried out with customized interactive command corresponding, and tests whether gesture one by one
Whether success is corresponded to order；
Step9, design mixing interaction gesture code are put into a target to mixing interaction gesture verifying in main interface,
According to the color of this target, size, position, whether Bei Xuanzhong state feeds back mixing gesture；
The accuracy of Step10, contrived experiment verifying mixing gesture.
Specifically, specific step is as follows by the Step10:
Step10.1, addition Correct parameter and Error parameter, every progress in interaction gesture code are mixed in Step9
Mixed once gesture identification, either correct or mistake, will all be recorded；
Step10.2, each gesture carry out 50 experiments, then the correct number with mistake of analysis obtains accuracy rate；
Step10.3, design accuracy experiment, design a main interface, the inside is put into five different targets in position, leads to
Cross the size for changing them and they the distance between, come test mixing gesture accuracy；
Step10.4, accuracy experimental result is analyzed, obtains the accuracy of mixing gesture.
The beneficial effects of the present invention are:
Present human-computer interaction is mainly based on contact, for example keyboard, mouse, handwriting pad etc., this mode are necessary
It is that hand is directly contacted with the device for receiving information, has thus fettered the flexibility of the freedom and message recipient part of manpower.
And usage scenario has some limitations, such as doctor should not use touch manner to computer operation during operation.It is non-
The effective application of contact human-computer interaction technology in medicine, can break through and reduce the office of conventional contact human-computer interaction technology
Limit, to constantly enhance the level of therapeutic treatment, the present invention has significant application value to medical domain, to the nothing of medical surgery
Bacterium operating environment has the non-contacting mixing control method based on " hand+face expression+head pose " of potentiality out of the ordinary to have just
In identification, natural, intuitive, simple characteristic can allow user that can interact in a more natural way with equipment, while to a certain degree
On enrich man-machine interactive mode, provide the user good experience.The invention enables user can get rid of it is specific
Physical equipment, thus allow man-machine information interaction seem more directly with nature.
Detailed description of the invention
Fig. 1 is that the present invention is based on the overview flow charts of the mixing control method of " hand+face expression+head pose "；
Fig. 2 is 106 critical point detection figures of face in the present invention；
Fig. 3 is the angle figure of head pose in the present invention.
Specific embodiment
Gather the drawings and specific embodiments below, the present invention is further illustrated.
Embodiment 1: as shown in Figure 1-3, a kind of non-contacting mixing controlling party based on " hand+face expression+head pose "
Method includes the following steps:
(1) official website Face++ is first logged into, then register account number and logs on to oneself console, creation face is crucial
Point detection application；
(2) the camera environment based on JMF frame is configured, allows the available picture stream to camera, as " face table
The input source of feelings " and " head pose "；
(3) the face critical point detection application that code calls backstage creation, the face key point for needing to detect then are write
As shown in Fig. 2, obtaining eye state, mouth states and head pose detected value as shown in Figure 3；
(4) environment for configuring Leap Motion, can allow Leap Motion dynamically to obtain gesture, as gesture in this way
Input source；
(5) it writes code and realizes that the dynamic gesture of Leap Motion obtains in code；
(6) according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixes interaction hand
Gesture；
(7) computer interactive command corresponding to customized mixing interaction gesture；
(8) mixing gesture is carried out with customized interactive command corresponding, generates corresponding feedback effects；
(9) design mixing interaction gesture, which is applied, identifies mixing interaction gesture；
(10) accuracy and accuracy of contrived experiment verifying mixing interaction gesture；
Specific step is as follows for the non-contacting mixing control method based on " hand+face expression+head pose " of one kind:
Step1, the official website Face++ is first logged into, then register account number and logs on to oneself console, then clicks
" application management " clicks " creation API key " creation face critical point detection application, generates " API key " and " API
Secret"；
Step2, camera environment of the configuration based on JMF frame, then write the data flow of Code obtaining camera and life
Input source at Image object, as " face expression " and " head pose "；
Step3, the face critical point detection application that code calls backstage creation is write, the face key point for needing to detect is such as
Shown in Fig. 2, left eye state (left_eye_status), right eye state (right_eye_status), mouth states are obtained
(mouthstatus) and head pose angle as shown in Figure 3 (headpose) detected value；
Step4, the SDK file for downloading Leap Motion, and configure the environment of local system, can allow Leap in this way
Motion dynamically obtains gesture, the input source as gesture；
Step5, instantiation Controller object, and four kinds of gesture identifications of Leap Motion are opened, it enables a system to
The various gestures of Leap Motion are dynamically identified in code；
Step6, according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixing is handed over
Mutual gesture, such as cursor is controlled with a finger, " face expression " and head pose are interacted as input quantity；
Computer interactive command corresponding to Step7, customized mixing interaction gesture, including choose, right click, left click, under
The order such as sliding, upper cunning, left cunning, right cunning, amplification, diminution；
Step8, customized mixing gesture is carried out with customized interactive command corresponding, and tests whether gesture one by one
Whether success is corresponded to order；
Step9, design mixing interaction gesture are applied to mixing interaction gesture verifying, and a target is put into main interface,
According to the color of this target, size, position, whether selected fair state feeds back mixing gesture；
The accuracy of Step10, contrived experiment verifying mixing gesture.
Further, specific step is as follows by the Step10:
Step10.1, addition Correct parameter and Error parameter, every progress in interaction gesture code are mixed in Step9
Mixed once gesture identification, either correct or mistake, will all be recorded；
Step10.2, each gesture carry out 50 experiments, then the correct number with mistake of analysis obtains accuracy rate；
Step10.3, design accuracy experiment, design a main interface, the inside is put into five different targets in position, leads to
Cross the size for changing them and they the distance between, come test mixing gesture accuracy；
Step10.4, accuracy experimental result is analyzed, obtains the accuracy of mixing gesture.
The solution of the present invention is described in detail below with reference to specific example:
Example 1: specific step is as follows for a kind of amplifying operation of non-contacting mixing control method:
Step1, the official website Face++ is first logged into, then register account number and logs on to oneself console, then clicks
" application management " clicks " creation API key " creation face critical point detection application, generates " API key ": i9V7dr9ZuxT
JBwABQiqGLBGVDFqXR0Hi and " API Secret ": evEytGqlCDM_9dQsImM2KydJETuJS2fH；
Step2, camera environment of the configuration based on JMF frame, then pass through initialization CaptureDeviceManager
Then object generates Image object, while so that camera is constantly in work using timer to obtain the data flow of camera
In work, input source of the still photo as " face expression " and " head pose " is shot；
Step3, the face critical point detection application that code calls backstage creation is write, the face key point for needing to detect is such as
Shown in Fig. 2, the numerical value for obtaining the no_glass_eye_open under left eye state left_eye_status at this time is 95.225；It obtains
The numerical value of no_glass_eye_open under the right eye state right_eye_status got is 99.942；The mouth got
Open parameter values under bar state mouthstatus are 99.386 and head pose angle is as shown in figure 3, under headpose
" roll_angle ": -36.014675；
Step4, the SDK file for downloading Leap Motion, and configure the environment of local system, can allow Leap in this way
Motion dynamically obtains gesture, the input source as gesture；
Step5, instantiation Controller object, and four kinds of gesture identifications of Leap Motion are opened, it enables a system to
The various gestures of Leap Motion are dynamically identified in code, and the three dimensional space coordinate of LeapMotion is mapped to
Two-dimensional coordinate binds a finger as virtual mouse, is used for selection target；
Step6, the state value opened according to the left eye obtained in Step3 are 95.225, and the state value that right eye is opened is
99.942, the state value that mouth opens is 99.386, and head angle is -36.014675, it can be determined that current face expression is left
Eye is opened, and right eye is opened, and mouth opens；Head pose is negative, it can be determined that is torticollis to the left；It is advised according to customized gesture
Then it is judged as amplifying operation, target is amplified；
Step7, Step2-Step7, test accuracy rate and accurate rate are repeated；
Step8, amplifying gesture is carried out to 50 experiments, wherein correct number is the number 2 of 48 and mistake, accuracy rate is
96%.
The present invention using Face++ platform, Leap Motion as tool, according to Face++ platform face critical point detection and
Leap Motion gestures detection designs a set of new mixing interaction gesture, multimodal human-computer interaction is enriched, to computer
The development of human-computer interaction is of great significance.
In conjunction with attached drawing, the embodiment of the present invention is explained in detail above, but the present invention is not limited to above-mentioned
Embodiment within the knowledge of a person skilled in the art can also be before not departing from present inventive concept
Put that various changes can be made.
Claims (3)
1. a kind of non-contacting mixing control method based on " hand+face expression+head pose ", it is characterised in that: including as follows
Step:
(1) official website Face++ is first logged into, then register account number and logs on to oneself console, creation face key point inspection
Survey application；
(2) the camera environment based on JMF frame, the available picture stream to camera, as " face expression " and " head are configured
The input source of portion's posture "；
(3) the face critical point detection application that code calls backstage creation is then write, eye state, mouth states and head are obtained
The detected value of portion's posture；
(4) environment for configuring Leap Motion, can allow Leap Motion dynamically to obtain gesture, as the defeated of gesture in this way
Enter source；
(5) it writes code and realizes that the dynamic gesture of Leap Motion obtains in code；
(6) according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixes interaction gesture；
(7) computer interactive command corresponding to customized mixing interaction gesture；
(8) mixing gesture is carried out with customized interactive command corresponding, generates corresponding feedback effects；
(9) design mixing interaction gesture, which is applied, identifies mixing interaction gesture；
(10) accuracy and accuracy of contrived experiment verifying mixing interaction gesture.
2. the non-contacting mixing control method based on " hand+face expression+head pose " of one kind according to claim 1,
It is characterized by: specific step is as follows:
Step1, the official website Face++ is first logged into, then register account number and logs on to oneself console, then clicks " application
Management " is clicked " creation API key " creation face critical point detection application, is generated " API key " and " API Secret "；
Step2, camera environment of the configuration based on JMF frame, then write the data flow of Code obtaining camera and generation
Image object, the input source as " face expression " and " head pose "；
Step3, the face critical point detection application that code calls backstage creation is write, obtains left eye state left_eye_
The inspection of status, right eye state right_eye_status, mouth states mouthstatus and head pose angle headpose
Measured value；
Step4, the SDK file for downloading Leap Motion, and configure the environment of local system, can allow LeapMotion in this way
Gesture is dynamically obtained, the input source as gesture；
Step5, instantiation Controller object, and four kinds of gesture identifications of Leap Motion are opened, it enables a system in generation
The various gestures of Leap Motion are dynamically identified in code；
Step6, according to the state of the eyes of acquisition, head and hand, customized " hand+face expression+head pose " mixes interaction hand
Gesture；
Computer interactive command corresponding to Step7, customized mixing interaction gesture, including choose, right click, left click, downslide, on
Sliding, left cunning, right cunning, amplification, diminution order；
Step8, customized mixing gesture is carried out with customized interactive command corresponding, and tests whether gesture and life one by one
It enables and whether corresponds to success；
Step9, design mixing interaction gesture code are put into a target to mixing interaction gesture verifying in main interface, according to
The color of this target, size, position, whether Bei Xuanzhong state feeds back mixing gesture；
The accuracy of Step10, contrived experiment verifying mixing gesture.
3. the non-contacting mixing control method based on " hand+face expression+head pose " of one kind according to claim 2,
It is characterized by: specific step is as follows by the Step10:
Step10.1, addition Correct parameter and Error parameter in interaction gesture code are mixed in Step9, it is every to carry out once
Gesture identification is mixed, either correct or mistake will be all recorded；
Step10.2, each gesture carry out 50 experiments, then the correct number with mistake of analysis obtains accuracy rate；
Step10.3, design accuracy experiment, design a main interface, the inside is put into five different targets in position, by changing
Become they size and they the distance between, come test mixing gesture accuracy；
Step10.4, accuracy experimental result is analyzed, obtains the accuracy of mixing gesture.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110349268A (en) * | 2019-06-11 | 2019-10-18 | 华南理工大学 | A kind of reconstructing method of 3 D human body posture, expression and gesture |
| CN110472589A (en) * | 2019-08-19 | 2019-11-19 | 中国银行股份有限公司 | A kind of method, apparatus and system of behavior authentication |
| CN113391754A (en) * | 2021-06-28 | 2021-09-14 | 昆明理工大学 | Wrist rotation menu interaction technology based on LeapMotion sensor |
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| CN102117117A (en) * | 2010-01-06 | 2011-07-06 | 致伸科技股份有限公司 | System and method for control through identifying user posture by image extraction device |
| CN105653037A (en) * | 2015-12-31 | 2016-06-08 | 张小花 | Interactive system and method based on behavior analysis |
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2018
- 2018-09-13 CN CN201811066599.3A patent/CN109408037A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102117117A (en) * | 2010-01-06 | 2011-07-06 | 致伸科技股份有限公司 | System and method for control through identifying user posture by image extraction device |
| CN105653037A (en) * | 2015-12-31 | 2016-06-08 | 张小花 | Interactive system and method based on behavior analysis |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110349268A (en) * | 2019-06-11 | 2019-10-18 | 华南理工大学 | A kind of reconstructing method of 3 D human body posture, expression and gesture |
| CN110472589A (en) * | 2019-08-19 | 2019-11-19 | 中国银行股份有限公司 | A kind of method, apparatus and system of behavior authentication |
| CN113391754A (en) * | 2021-06-28 | 2021-09-14 | 昆明理工大学 | Wrist rotation menu interaction technology based on LeapMotion sensor |
| CN113391754B (en) * | 2021-06-28 | 2024-03-12 | 昆明理工大学 | Wrist rotation menu interaction technology based on leap motion sensor |
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Application publication date: 20190301 |