CN102662464A - Gesture control method of gesture roaming control system - Google Patents
Gesture control method of gesture roaming control system Download PDFInfo
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- CN102662464A CN102662464A CN2012100818887A CN201210081888A CN102662464A CN 102662464 A CN102662464 A CN 102662464A CN 2012100818887 A CN2012100818887 A CN 2012100818887A CN 201210081888 A CN201210081888 A CN 201210081888A CN 102662464 A CN102662464 A CN 102662464A
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Abstract
The invention discloses a gesture control method of a gesture roaming control system. The gesture control method comprises the following steps: (1) a user obtains a control right of the gesture roaming control system, and the gesture roaming control system positions a shoulder joint corresponding to a hand of a person at the same time; (2) the user determines a comfortable movement area of the hand of the person by regarding the shoulder joint as a reference point; (3) the user carries out roaming control operation on the gesture roaming control system; (4) the gesture roaming control system detects an image transmitted by a video sensor, and determines a relative position of the comfortable movement area of the hand of the person; and (5) the relative position of the comfortable movement area of the hand of the person is mapped onto an interface of the gesture roaming control system.
Description
Technical field
The present invention relates to human-computer interaction technology, particularly a kind of gesture control method of gesture roaming control system.
Background technology
In the system of various man-machine interactions, along with the breakthrough that various technology realize, what much more more the design of interactive system was concerned about is the interactive experience aspect that how to improve the user at present.For this reason, the mutual scheme of various noncontact power-relations is arisen at the historic moment, and especially roams the scheme of controlling based on gesture and gesture.In addition, various control system based on gesture also progressively move to maturity, and under the impact of the kinect of Microsoft, more and more manufacturers begin the existing contact control mode is changed to contactless control mode.
Yet; In the design of current various gesture roaming control interaction schemes; Scheme is not considered the comfortable moving region of staff greatly; Perhaps do not provide a kind of system and the effectively system of selection in human hand movement zone, make the user in operating process easily each zone at roaming system interface or be difficult to accurately arrive the user and expect the point that reaches.
Ergonomics is the various factors of the aspects such as anatomy, physiology and psychology of research people in certain working environment; The work efficiency of people under various environment, people's the health, safety and the science of problem such as comfortable are studied in the interaction of research people and machine and environment.Ergonomics is that product design proposes friendly operation interface and comfortable configuration design, improves user's comfort level and the design factor that adds aesthetics with this.
Summary of the invention
For the above-mentioned shortcoming and deficiency that overcomes prior art, the object of the present invention is to provide a kind of gesture control method of gesture roaming control system, make the user in moving region that can be comfortable, roam each point on the control system interface at hand.
The object of the invention is realized through following technical scheme:
A kind of gesture control method of gesture roaming control system may further comprise the steps:
(1) user obtains the control of gesture roaming control system; Simultaneously, gesture roaming control system detects the image that video sensor transmits, and the shoulder joint corresponding to staff positions;
(2) shoulder joint that obtains with step (1) is a RP, confirms the comfortable moving region of staff according to ergonomics;
(3) user roams control operation to gesture roaming control system;
(4) gesture roaming control system detects the image that video sensor transmits, and confirms the relative position of staff in the determined comfortable moving region of step (2);
(5) relative position of staff in comfortable moving region of step (4) being confirmed is mapped to the interface of gesture roaming control system.
The said gesture roaming of step (1) control system detects the image that video sensor transmits; The shoulder joint corresponding to staff positions; Be specially: utilize the Adaboost algorithm earlier; Use is greater than the positive sample of 300 people's faces with greater than the negative sample of 800 people's faces, and training obtains people's face strong classifier of a cascade; End user's face strong classifier detects the image that video sensor transmits, and obtains the accurate position of people's face in video image; Draw the position of the user crown in video image by the accurate position of people's face in video image, the related data according to ergonomics draws the corresponding position of shoulder joint in video image of staff again;
Said ergonomics related data is: the distance between average adult's two shoulder joint is 340mm, and the crown is 355mm to the vertical range on plane, shoulder joint place.
Step (2) is said to be confirmed the comfortable moving region of staff to be specially according to ergonomics:
According to ergonomics; The rectangle that a size is 421.08mm * 522.25 mm is confirmed as in the comfortable motor area of staff; With the shoulder joint is the ratio cut-point; The rectangle left side is 1:1.41 with the ratio on rectangle right side on the horizontal direction, and the ratio of rectangle upside and rectangle downside is 1.92:1 on the vertical direction.
The said definite staff of step (4) is at the relative position of the determined comfortable moving region of step (2); Be specially: utilize the Adaboost algorithm earlier; Use is trained the gesture strong classifier of a cascade greater than the positive sample of 300 gesture with greater than 800 gesture negative samples; The strong classifier that uses gesture is detected the image that video sensor transmits; Detected gesture zone is set at area-of-interest, removes the noise in the background; In area-of-interest, combine Face Detection to carry out movable information and detect, staff is followed the tracks of;
(x2 y2), confirms the relative coordinate (x0 of staff in the comfortable moving region of staff to obtain the accurate position of staff in video image after the tracking; Y0): the coordinate of the upper left corner in video image of establishing comfortable moving region is (x1; Y1), x0=x2-x1 then, y0=y2-y1.
The said Face Detection that in area-of-interest, combines is carried out the movable information detection; Staff is followed the tracks of; Be specially: in area-of-interest, combine Face Detection, adopt frame difference and background difference to carry out the detection of movable information, and combine the Camshift algorithm that staff is followed the tracks of.
The said relative position of staff in comfortable moving region that step (4) is confirmed of step (5) is mapped to the interface of gesture roaming control system, is specially:
If the length of the determined comfortable moving region of step (2) and the wide a1 that is respectively; B1, the length of control system interface screen and the wide a2 that is respectively, b2; The staff that step (4) is confirmed is (x0 at the coordinate of the relative position of comfortable moving region; Y0), then be mapped to the position coordinates x at screen reference mark, relation below y satisfies:
Compared with prior art, the present invention has the following advantages and beneficial effect:
1, owing to set the comfortable moving region of staff; The user makes when roaming each point at the interface of roaming control cosily more naturally that uses gesture, and can effectively avoid the user phenomenons such as screen border and interface mouse roam speed be too fast when roaming, to occur beyond reach.
2, owing to when the user uses roaming system, confirmed the moving region of staff, can more effectively reduce background interference, less demanding to background for the track algorithm front end.
3, owing to confirmed the relative position of staff and the comfortable moving region of staff, make from the human hand movement position to the mapping of control interface location and become simple more and accurate.
Description of drawings
Fig. 1 is the process flow diagram of the gesture control method of a kind of gesture roaming of the present invention control system.
Embodiment
Below in conjunction with embodiment and accompanying drawing, the present invention is done to specify further, but embodiment of the present invention is not limited thereto.
Embodiment
As shown in Figure 1, a kind of gesture control method of gesture roaming control system may further comprise the steps:
(1) user obtains the control of gesture roaming control system; Simultaneously, gesture roaming control system detects the image that video sensor transmits, and the shoulder joint corresponding to staff positions, and is specially:
Utilize the Adaboost algorithm earlier, use greater than the positive sample of 300 people's faces with greater than the negative sample of 800 people's faces, training obtains people's face strong classifier of a cascade; End user's face strong classifier detects the image that video sensor transmits, and obtains the accurate position of people's face in video image; Draw the position of the user crown in video image by the accurate position of people's face in video image, the related data according to ergonomics draws the corresponding position of shoulder joint in video image of staff again;
Said ergonomics related data is: the distance between average adult's two shoulder joint is 340mm, and the crown is 355mm to the vertical range on plane, shoulder joint place.
(2) shoulder joint that obtains with step (1) is a RP; Confirm the comfortable moving region of staff according to ergonomics; According to ergonomics,, be the ratio cut-point with the shoulder joint with the comfortable motor area of the staff rectangle that to confirm as a size be 421.08mm * 522.2mm; The rectangle left side is 1:1.41 with the ratio on rectangle right side on the horizontal direction, and the ratio of rectangle upside and rectangle downside is 1.92:1 on the vertical direction.
(3) user roams control operation to gesture roaming control system.
(4) gesture roaming control system detects the image that video sensor transmits, and confirms the relative position of staff in the comfortable moving region of the determined staff of step (2), is specially:
Utilize the Adaboost algorithm earlier, use, the gesture strong classifier of a cascade of training greater than the positive sample of 300 gesture with greater than 800 gesture negative samples; The strong classifier that uses gesture is detected the image that video sensor transmits; Detected gesture zone is set at area-of-interest, removes the noise in the background; In area-of-interest, combine Face Detection, adopt frame difference and background difference to carry out the detection of movable information, and combine the Camshift algorithm that staff is followed the tracks of;
(x2 y2), confirms the relative coordinate (x0 of staff in comfortable moving region to obtain the accurate position of staff in video image after the tracking; Y0): the coordinate of the upper left corner in video image of establishing comfortable moving region is (x1; Y1), x0=x2-x1 then, y0=y2-y1.
(5) relative position of staff in comfortable moving region of step (4) being confirmed is mapped to the interface of gesture roaming control system, is specially:
If the length of the determined comfortable moving region of step (2) and the wide a1 that is respectively; B1, the length of control system interface screen and the wide a2 that is respectively, b2; The staff that step (4) is confirmed is (x0 at the coordinate of the relative position of comfortable moving region; Y0), then be mapped to the position coordinates x at screen reference mark, relation below y satisfies:
The foregoing description is a preferred implementation of the present invention; But embodiment of the present invention is not limited by the examples; Other any do not deviate from change, the modification done under spirit of the present invention and the principle, substitutes, combination, simplify; All should be the substitute mode of equivalence, be included within protection scope of the present invention.
Claims (6)
1. the gesture control method of a gesture roaming control system is characterized in that, may further comprise the steps:
(1) user obtains the control of gesture roaming control system; Simultaneously, gesture roaming control system detects the image that video sensor transmits, and the shoulder joint corresponding to staff positions;
(2) shoulder joint that obtains with step (1) is a RP, confirms the comfortable moving region of staff according to ergonomics;
(3) user roams control operation to gesture roaming control system;
(4) gesture roaming control system detects the image that video sensor transmits, and confirms the relative position of staff in the determined comfortable moving region of step (2);
(5) relative position of staff in comfortable moving region of step (4) being confirmed is mapped to the interface of gesture roaming control system.
2. the gesture control method of gesture roaming control system according to claim 1; It is characterized in that; The said gesture roaming of step (1) control system detects the image that video sensor transmits, and the shoulder joint corresponding to staff positions, and is specially: utilize the Adaboost algorithm earlier; Use is greater than the positive sample of 300 people's faces with greater than the negative sample of 800 people's faces, and training obtains people's face strong classifier of a cascade; End user's face strong classifier detects the image that video sensor transmits, and obtains the accurate position of people's face in video image; Draw the position of the user crown in video image by the accurate position of people's face in video image, the related data according to ergonomics draws the corresponding position of shoulder joint in video image of staff again;
Said ergonomics related data is: the distance between average adult's two shoulder joint is 340mm, and the crown is 355mm to the vertical range on plane, shoulder joint place.
3. the gesture control method of gesture according to claim 1 roaming control system is characterized in that, step (2) is said to be confirmed the comfortable moving region of staff to be specially according to ergonomics:
According to ergonomics; The rectangle that a size is 421.08mm * 522.25 mm is confirmed as in the comfortable motor area of staff; With the shoulder joint is the ratio cut-point; The rectangle left side is 1:1.41 with the ratio on rectangle right side on the horizontal direction, and the ratio of rectangle upside and rectangle downside is 1.92:1 on the vertical direction.
4. the gesture control method of gesture roaming control system according to claim 1 is characterized in that the said definite staff of step (4) is specially at the relative position of the determined comfortable moving region of step (2):
Utilize the Adaboost algorithm earlier, use, the gesture strong classifier of a cascade of training greater than the positive sample of 300 gesture with greater than 800 gesture negative samples; The strong classifier that uses gesture is detected the image that video sensor transmits; Detected gesture zone is set at area-of-interest, removes the noise in the background; In area-of-interest, combine Face Detection to carry out movable information and detect, staff is followed the tracks of;
(x2 y2), confirms the relative coordinate (x0 of staff in comfortable moving region to obtain the accurate position of staff in video image after the tracking; Y0): the coordinate of the upper left corner in video image of establishing comfortable moving region is (x1; Y1), x0=x2-x1 then, y0=y2-y1.
5. the gesture control method of gesture roaming control system according to claim 4; It is characterized in that; The said Face Detection that in area-of-interest, combines is carried out the movable information detection; Staff is followed the tracks of, be specially: in area-of-interest, combine Face Detection, adopt frame difference and background difference to carry out the detection of movable information, and combine the Camshift algorithm that staff is followed the tracks of.
6. the gesture control method of gesture roaming control system according to claim 4 is characterized in that, the said relative position of staff in comfortable moving region that step (4) is confirmed of step (5) is mapped to the interface of gesture roaming control system, is specially:
If the length of the determined comfortable moving region of step (2) and the wide a1 that is respectively; B1, the length of control system interface screen and the wide a2 that is respectively, b2; The staff that step (4) is confirmed is (x0 at the coordinate of the relative position of comfortable moving region; Y0), then be mapped to the position coordinates x at screen reference mark, relation below y satisfies:
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CN103400118A (en) * | 2013-07-30 | 2013-11-20 | 华南理工大学 | Gesture control method capable of adaptively adjusting mapping relation |
CN103793056A (en) * | 2014-01-26 | 2014-05-14 | 华南理工大学 | Mid-air gesture roaming control method based on distance vector |
CN104460976A (en) * | 2014-02-19 | 2015-03-25 | 同济大学 | Application of constant-heart-rate walking speed conversion in passive roam control module |
CN105912126A (en) * | 2016-04-26 | 2016-08-31 | 华南理工大学 | Method for adaptively adjusting gain, mapped to interface, of gesture movement |
CN105979330A (en) * | 2015-07-01 | 2016-09-28 | 乐视致新电子科技(天津)有限公司 | Somatosensory button location method and device |
CN106022211A (en) * | 2016-05-04 | 2016-10-12 | 北京航空航天大学 | Method using gestures to control multimedia device |
CN108040239A (en) * | 2017-12-06 | 2018-05-15 | 重庆欧派信息科技有限责任公司 | Knowledge training system and method based on image recognition |
CN108846442A (en) * | 2018-06-21 | 2018-11-20 | 吉旗物联科技(上海)有限公司 | A kind of gesture visual detection algorithm of making a phone call based on decision tree |
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CN103400118A (en) * | 2013-07-30 | 2013-11-20 | 华南理工大学 | Gesture control method capable of adaptively adjusting mapping relation |
CN103400118B (en) * | 2013-07-30 | 2017-09-29 | 华南理工大学 | The gestural control method that a kind of mapping relations are adaptively adjusted |
CN103793056A (en) * | 2014-01-26 | 2014-05-14 | 华南理工大学 | Mid-air gesture roaming control method based on distance vector |
CN104460976B (en) * | 2014-02-19 | 2017-01-11 | 同济大学 | Application of constant-heart-rate walking speed conversion in passive roam control module |
CN104460976A (en) * | 2014-02-19 | 2015-03-25 | 同济大学 | Application of constant-heart-rate walking speed conversion in passive roam control module |
CN105979330A (en) * | 2015-07-01 | 2016-09-28 | 乐视致新电子科技(天津)有限公司 | Somatosensory button location method and device |
WO2017000917A1 (en) * | 2015-07-01 | 2017-01-05 | 乐视控股(北京)有限公司 | Positioning method and apparatus for motion-stimulation button |
CN105912126A (en) * | 2016-04-26 | 2016-08-31 | 华南理工大学 | Method for adaptively adjusting gain, mapped to interface, of gesture movement |
CN105912126B (en) * | 2016-04-26 | 2019-05-14 | 华南理工大学 | A kind of gesture motion is mapped to the adaptive adjusting gain method at interface |
CN106022211A (en) * | 2016-05-04 | 2016-10-12 | 北京航空航天大学 | Method using gestures to control multimedia device |
CN106022211B (en) * | 2016-05-04 | 2019-06-28 | 北京航空航天大学 | A method of utilizing gesture control multimedia equipment |
CN108040239A (en) * | 2017-12-06 | 2018-05-15 | 重庆欧派信息科技有限责任公司 | Knowledge training system and method based on image recognition |
CN109196438A (en) * | 2018-01-23 | 2019-01-11 | 深圳市大疆创新科技有限公司 | A kind of flight control method, equipment, aircraft, system and storage medium |
CN108846442A (en) * | 2018-06-21 | 2018-11-20 | 吉旗物联科技(上海)有限公司 | A kind of gesture visual detection algorithm of making a phone call based on decision tree |
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